Skip to main content
main-content

Über dieses Buch

This book is based on the research papers presented during The Institute of Industrial Engineers Asian Conference 2013 held at Taipei in July 2013. It presents information on the most recent and relevant research, theories and practices in industrial and systems engineering. Key topics include:

Engineering and Technology Management

Engineering Economy and Cost Analysis

Engineering Education and Training

Facilities Planning and Management

Global Manufacturing and Management

Human Factors

Industrial & Systems Engineering Education

Information Processing and Engineering

Intelligent Systems

Manufacturing Systems

Operations Research

Production Planning and Control

Project Management

Quality Control and Management

Reliability and Maintenance Engineering

Safety, Security and Risk Management

Supply Chain Management

Systems Modeling and Simulation

Large scale complex systems

Inhaltsverzeichnis

Frontmatter

An Optimal Ordering Policy of the Retailers Under Partial Trade Credit Financing and Restricted Cycle Time in Supply Chain

The traditional EOQ (Economic Order Quantity) model assumes that retailers’ capitals are unrestricting and the retailer must pay for items as soon as the retailer receives them from suppliers. However, this may not be true. In practice, the supplier will offer the retailer a delay period. This period is known as the trade credit period. Previously published papers assumed that the supplier would offer the retailer a delay period and the retailer could sell goods and earn interest or investment within the trade credit period. They assumed that the supplier would offer the retailer a delay period but the retailer would not offer the trade credit period to his/her customer. We extend their model and construct new ordering policy. In this paper, the retailer will also adopt the partial trade credit policy to his/her customer. We assume that the retailer’s trade credit period offered by the supplier is not shorter than his/her customer’s trade credit period offered by the retailer. In addition, they assumed the relationship between the supplier and the retailer is one-to-one. One thing we want to emphasize here is that the supplier has cooperative relations with many retailers. Furthermore, we assume that the total of the cycle time is restricted. Under these conditions, we model the retailers’ inventory system to determine the optimal cycle times for

n

retailers.

Shin’ichi Yoshikawa

An Immunized Ant Colony System Algorithm to Solve Unequal Area Facility Layout Problems Using Flexible Bay Structure

The Facility Layout Problem (FLP) is a typical combinational optimization problem. In this research, clonal selection algorithm (CSA) and ant colony system (ACS) are combined and an immunized ant colony system algorithm (IACS) is proposed to solve unequal-area facility layout problems using a flexible bay structure (FBS) representation. Four operations of CSA, clone, mutation, memory cells, and suppressor cells, are introduced in the ACS to improve the solution quality of initial ant solutions and to increase differences among ant solutions, so search capability of the IACO is enhanced. Datasets of well-known benchmark problems are used to evaluate the effectiveness of this approach. Compared with preview researches, the IACS can obtain the close or better solutions for some benchmark problems.

Mei-Shiang Chang, Hsin-Yi Lin

Characterizing the Trade-Off Between Queue Time and Utilization of a Manufacturing System

Characterizing system performance is essential for productivity improvement. Inspired by the underlying structure of tandem queues, an approximate model has been derived to characterize the system performance. The model decomposes system queue time and variability into bottleneck and non-bottleneck parts while capturing the dependence among workstations.

Kan Wu

Using Latent Variable to Estimate Parameters of Inverse Gaussian Distribution Based on Time-Censored Wiener Degradation Data

To effectively assess the lifetime distribution of a highly reliability product, a degradation test is used if the product’s lifetime is highly related to a critical product characteristic degrading over time. The failure times, as well as the degradation values, provide useful information for estimating the lifetime in a short test duration. The Wiener process model has been successfully used for describing degradation paths of many modern products such as LED light lamps. Based on this model, the lifetime of a product would follow the Inverse Gaussian (IG) distribution with two parameters. To estimate the parameters, we propose a method using the latent variables to obtain Latent Variable Estimates (LVE) of the parameters of the IG lifetime distribution. The proposed LVEs have simple closed functional form and thus they are easy to interpret and implement. Moreover, we prove the LVEs are consistent estimates. Via simulation studies, we show that the LVEs have smaller bias and mean square error than existing estimates in the literature.

Ming-Yung Lee, Cheng-Hung Hu

Interpolation Approximations for the Performance of Two Single Servers in Series

Dependence among servers is the root cause of the analytic intractability of general queueing networks. A tandem queue is the smallest unit possessing the dependence. Understand its behavior is the key to understand the behavior of general queueing networks. Based on observed properties, such as intrinsic gap and intrinsic ratio, a new approximation approach for tandem queues is proposed. Across a broad range of examined cases, this new approach outperforms prior methods based on stochastic independence or diffusion approximations.

Kan Wu

On Reliability Evaluation of Flow Networks with Time-Variant Quality Components

In general, the reliability evaluation of a stochastic-flow network is with time-invariant quality components (including links or vertices). However, in practice, the quality of components for a stochastic-flow network may be variant due to deterioration or improvement by incomplete renewal. This paper presents a method to evaluate the two-terminal network reliability (2TNR) with time-variant quality components. A numerical example is presented to show the application of this method.

Shin-Guang Chen

Defect Detection of Solar Cells Using EL Imaging and Fourier Image Reconstruction

Solar power is an attractive alternative source of electricity nowadays. Solar cells, which form the basis of a solar power system, are mainly based on crystalline silicon. Many defects cannot be visually observed with the conventional CCD imaging system. This paper presents defect inspection of multi-crystalline solar cells in electroluminescence (EL) images. A solar cell charged with electrical current emits infrared light. The intrinsic crystal grain boundaries and extrinsic defects of small cracks, breaks, and finger interruptions hardly reflect the infrared light. The EL image can thus distinctly highlight barely visible defects as dark objects. However, it also shows random dark regions in the background, which makes automatic inspection in EL images very difficult. A self-reference scheme based on the Fourier image reconstruction technique is proposed for defect detection of solar cells in EL images. The target defects appear as line- or bar-shaped objects in the EL image. The Fourier image reconstruction process is applied to remove the possible defects by setting the frequency components associated with the line- and bar-shaped defects to zero and then back-transforming the spectral image into a spatial image. The defect region can then be easily identified by evaluating the gray-level differences between the original image and its reconstructed image. The reference image is generated from the inspection image itself and, thus, can accommodate random inhomogeneous backgrounds. Experimental results on a set of various solar cells have shown that the proposed method performs effectively for detecting small cracks, breaks, and finger interruptions. The computation time of the proposed method is also fast, making it suitable for practical implementation. It takes only 0.29 s to inspect a whole solar cell image with a size of 550 × 550 pixels.

Ya-Hui Tsai, Du-Ming Tsai, Wei-Chen Li, Shih-Chieh Wu

Teaching Industrial Engineering: Developing a Conjoint Support System Catered for Non-Majors

Previously, business managers and college students seem to have not given enough thought to the study of Industrial Engineering

(

IE). Increasingly, however, they have become conscious of the importance of IE. In fact, many have started to consider the topic to be useful and critical for their future career. This being the case, it seems highly valuable to develop an educational program which deals specifically with both operation and concept of IE. The program so developed will help improve those who have already studied IE; at the same time, the system would likewise enhance and broaden the knowledge of those whose focus has been confined only to business management. This study tries to create an educational program which conjoins two different faces of business management. On one hand, the program targets on those who have an extensive experience in business management. On the other hand, the system likewise centers on those who know little about business management but have studied IE in the past. By using this cross cutting support method, two different will equally enhance their total knowledge of business administration.

Yoshiki Nakamura

An Automatic Image Enhancement Framework for Industrial Products Inspection

Image enhancement methods play a key role in image preprocessing. In practical, to obtain product characteristics, image enhancement methods are usually selected by trial-and-error or by experience. In this chapter, we proposed a novel procedure to automatically select image enhancement procedures by using singular value decomposition to extract features of an image. Forty-five industrial product images from literature and local companies were used in the experiment. The results showed that the contrast values had no significant differences with the literature. The study results implied that the system could automatically applied and effectively improve the image quality.

Chien-Cheng Chu, Chien-Chih Wang, Bernard C. Jiang

Ant Colony Optimization Algorithms for Unrelated Parallel Machine Scheduling with Controllable Processing Times and Eligibility Constraints

In this paper, we consider the problem of scheduling jobs on unrelated parallel machines with eligibility constraints, where job-processing times are controllable through the allocation of a nonrenewable common resource, and can be modeled by a linear resource consumption function. The objective is to assign the jobs to the machines and to allocate the resource so that the makespan is minimized. We provide an exact formulation of the addressed problem as an integer programming model. As the problem has been proven to be NP-hard even for the fixed job-processing times, two ant colony optimization (ACO) algorithms based on distinct procedures, respectively, are also presented and analyzed. Numerical results show that both the proposed algorithms are capable of solving large-sized problems within reasonable computational time and accuracy.

Chinyao Low, Rong-Kwei Li, Guan-He Wu

General Model for Cross-Docking Distribution Planning Problem with Time Window Constraints

The research studies a cross-docking distribution planning problem that consists of manufacturers, cross-docking centers and customers. It is focused on how to distribute and receive products within time interval restrictions of each node. This means that the manufacturer has specific time intervals for releasing products to be shipped to destinations, the cross-docking centers have time intervals to receive products from manufacturers and to release them to customers, and the customers also have their time intervals for receiving the products. A mixed integer programming model is formulated to deal with this time interval restrictions by including time window constraints at each level in the network. Also, the multiple types of products and consolidation of customer orders are considered. The objective function is to minimize the total cost which combines the transportation cost and inventory cost. A LINGO program was improved from Jewpanya and Kachitvichyanukul (General model of Cross-docking distribution planning problem. In: Proceedings of the 7th international congress on logistics and SCM systems, Seoul, 2012) to efficiently handle the problem with time window constraints. Some example problems are solved to demonstrate the optimal distribution plan of the cross-docking distribution planning problem under the limitation of each time window.

Parida Jewpanya, Voratas Kachitvichyanukul

A New Solution Representation for Solving Location Routing Problem via Particle Swarm Optimization

This paper presents an algorithm based on the particle swarm optimization algorithm with multiple social learning terms (GLNPSO) to solve the capacitated location routing problem (CLRP). The decoding method determines customers clustering followed by depot location and ends with route construction. The performance of the decoding method is compared with previous work using a set of benchmark instances. The experimental results reveal that proposed decoding method found more stable solutions that are clustered around the best solutions with less variation.

Jie Liu, Voratas Kachitvichyanukul

An Efficient Multiple Object Tracking Method with Mobile RFID Readers

RFID (Radio Frequency Identification) technology originally is designed for object identification. Due to its relatively low cost and easy deployment, RFID technology becomes a popular approach for tracking the positions of objects. Many researchers proposed variant object tracking algorithms to quickly locate objects. Although these algorithms are efficient for certain applications, their tracking methods are limited on multiple objects with fixed RFID readers or single object with mobile RFID readers. None of them focus on tracking multiple objects with mobile RFID readers. To bridge this gap, this study develops an efficient multiple object tracking method with mobile RFID readers. First, the omni-directional antenna in a mobile RFID reader is used to judge the annular regions at which objects locate by adjusting the reader’s reading range. Second, the directional antenna in the mobile RFID reader is used to judge the circular sectors of objects according to the received signal strengths in each direction. Third, four picking strategies are proposed to decide whether an object is picked in current step or later step. Finally, the simulated annealing algorithm is performed for all objects in the list of current step to generate the picking sequence with shortest distance. The experiments show that the proposed tracking method can help users find multiple objects in shortest distance.

Chieh-Yuan Tsai, Chen-Yi Huang

A New Bounded Intensity Function for Repairable Systems

Lifetime failure data might have a bathtub-shaped failure rate. In this study, we propose a new model based on a mixture of bounded Burr XII distribution and bounded intensity process, to describe a failure process including a decreasing intensity phase, an increasing phase, and an accommodation phase for repairable systems. The estimates of the model parameters are easily obtained using the maximum likelihood estimation method. Through numerical example, the results show that our proposed model outperforms other existing models, such as superposed power law process, Log-linear process-power law process, and bounded bathtub intensity process with regard to mean square errors.

Fu-Kwun Wang, Yi-Chen Lu

Value Creation Through 3PL for Automotive Logistical Excellence

Change is the only constant in today’s business environment. Flexibility and adaptability have become key factors of organizational success. In today’s global business environment, organizations not only faced with issues of where to source their parts but also how to ship and store these parts effectively and efficiently. This issue is magnified as the complication of the products produced increases. Automotive industry has highly complicated parts which are sourced from around the globe. Through 3PL strategies, an automotive manufacturer can minimize downtime risk, reduce delivery lead time and ultimately improve its ability to adjust to the changing market demand. In this paper, we investigate the logistic factors affecting the automotive industry and discuss the challenges. An actual case study from DB Schenker, a German 3PL company, is used to illustrate the benefits of an effective VMI, information technology and inventory tracking in the supply chain. It can synchronize information and physical flow of goods across the supply chain. DB Schenker uses state-of-the-art storage and order-picking technologies in order to meet the very precise production time schedule, while keeping warehouse costs to a minimum.

Chin Lin Wen, Schnell Jeng, Danang Kisworo, Paul K. P. Wee, H. M. Wee

Dynamics of Food and Beverage Subsector Industry in East Java Province: The Effect of Investment on Total Labor Absorption

Gross Regional Domestic Product (GRDP) gives an overview of economic development performance in over time. The GRDP value in East Java province is increasing in every year, but this value cannot reduce unemployment rate. The existing of economic development condition is not able to absorb the large number of unemployment where the number of work force is also increasing in the period of time. These phenomena will influence social and economic problems in a region. Investment is one of ways that could be used in order to increase the field of business and reduce the unemployment rate. In this paper, describes the industrial development in food and beverage industries subsector in East Java. By using system dynamic approach, it will construct the change of business investment related to labor absorption in East Java which is affected by economic and climate change of industrial business factors. This research will consider several policy scenarios that have been taken by government such as changes in the proportion of infrastructure funds, the proportion of aid investment by government and licensing index. This scenario could reach the main objective of the system.

Putri Amelia, Budisantoso Wirjodirdjo, Niniet Indah Arvitrida

Solving Two-Sided Assembly Line Balancing Problems Using an Integrated Evolution and Swarm Intelligence

Assembly line balancing problem (ALBP) is an important problem in manufacturing due to its high investment cost. The objective of the assembly line balancing problem is to assign tasks to workstations in order to minimize the assembly cost, fulfill the demand and satisfy the constraints of the assembly process. In this study, a novel optimization method which integrates the evolution and swarm intelligence algorithms is proposed to solve the two-sided assembly line balancing problems. The proposed method mimics the basic soccer player movement where there are two main movements, the

move off

and the

move forward

. In this paper, the

move off

and the

move forward

are designed based on the specific features of two-sided assembly line balancing problems. Prioritize tasks and critical tasks are implemented in the

move off

and

move forward

respectively. The performance of the proposed method is compared to the heuristic and ant colony based method mentioned in the literature.

Hindriyanto Dwi Purnomo, Hui-Ming Wee, Yugowati Praharsi

Genetic Algorithm Approach for Multi-Objective Optimization of Closed-Loop Supply Chain Network

This paper applies multi-objective genetic algorithm (MOGA) to solve a closed-loop supply chain network design problem with multi-objective sustainable concerns. First of all, a multi-objective mixed integer programming model capturing the tradeoffs between the total cost and the carbon dioxide (CO

2

) emission is developed to tackle the multi-stage closed-loop supply chain design problem from both economic and environmental perspectives. The multi-objective optimization problem raised by the model is then solved using MOGA. Finally, some experiments are made to measure the performance.

Li-Chih Wang, Tzu-Li Chen, Yin-Yann Chen, Hsin-Yuan Miao, Sheng-Chieh Lin, Shuo-Tsung Chen

Replacement Policies with a Random Threshold Number of Faults

Most systems fail when a certain amount of reliability quantities have exceeded their threshold levels. The typical example is cumulative damage model in which a system is subjected to shocks and suffers some damage due to shocks, and fails when the total damage has exceeded a failure level

K

. This paper proposes the following reliability model: Faults occur at a nonhomogeneous Poisson process and the system fails when

N

faults have occurred, which could be applied to optimization problems in computer systems with fault tolerance, and we suppose that the system is replaced before failure at a planned time

T

. Two cases where the threshold fault number

N

is constantly given and is a random variable are considered, we obtain the expected cost rates and discuss their optimal policies.

Xufeng Zhao, Mingchih Chen, Kazunori Iwata, Syouji Nakamura, Toshio Nakagawa

A Multi-Agent Model of Consumer Behavior Considering Social Networks: Simulations for an Effective Movie Advertising Strategy

It is essential for a firm to understand consumer behavior in order to advertise products efficiently on a limited budget. Nowadays, consumer behavior is highly complex because consumers can get a lot of information about products from not only firm’s advertising but also social networking services. The purposes of this study are to construct consumer behavior model considering social networks and to demonstrate an effective weekly advertising budget allocation in order to increase the number of adopters of products. First, we developed a multi-agent model of consumer behavior taking the movie market as an example. In our model, each agent decides whether or not to watch a movie by comparing the weighted sum of “individual preference” and “effects of advertising and word-of-mouth (WOM)” with “individual threshold.” The scale-free network is used to describe social networks. Next, we verified the accuracy of the model by comparing the simulation results with the actual sales figures of 13 movies. Finally, we showed an effective weekly advertising budget allocation corresponding to movie type by simulations. Furthermore, it was demonstrated that the weekly advertising budget allocation gives greater impact on the number of adopters of products as social networks grow.

Yudai Arai, Tomoko Kajiyama, Noritomo Ouchi

Government Subsidy Impacts on a Decentralized Reverse Supply Chain Using a Multitiered Network Equilibrium Model

Government subsidies to reverse supply chains can play important roles in driving or curtailing the flows of recycled items. We examine the impacts of exogenous subsidies on recycled material flows in a decentralized reverse supply chains where each participant acts according to its own interests. We outline a multitiered model of the supply network from sources of scrap electronics, collectors, processors and demand markets. The individual behavior of each player is governed by participants’ optimality conditions, which are mathematically transformed into a variational inequality formulation. The modified projection method is utilized for solving the equilibrium quantities and prices of each participant. We investigate the impact of alternate schemes of government subsidies on decisions of the equilibrium quantities, prices and the total amount collected. For the case studied in this paper, the best tier selection between collectors and processors for government subsidies in terms of the total collected amount is located in collectors in laptop reverse supply chains.

Pin-Chun Chen, I-Hsuan Hong

A Capacity Planning Method for the Demand-to-Supply Management in the Pharmaceutical Industry

In the pharmaceutical industry, in order to secure a reliable supply of drags, the manufacturer tends to possess a production capacity much higher than the market demand. However, because of the severe competition and increasing product variety, the demand-to-supply management, which strategically supplies products to the market based on a collaborative strategy with the sales function and the production function in order to maximize profit, becomes a critical issue for any manufacturer in regards to improving his competitiveness and sustainability. In this paper, we propose a capacity planning method and a tool, developed with an engineering consulting company that can be used to support the demand-to-supply management in the pharmaceutical industry. The method synthesizes an initial manufacturing process structure and the capacity of each process unit based on the demand forecast and candidate equipment specifications at the first step. Then it improves the process structure in a step-by-step fashion at the second step. The developed tool supports the development and evaluation of the process structure from the perspective of the utilization of each process unit, investment cost, operation cost, and so on. We show the effectiveness of the developed method and the tool through a case study.

Nobuaki Ishii, Tsunehiro Togashi

Storage Assignment Methods Based on Dependence of Items

According to historical customer orders, some items tend to be ordered at the same time, i.e., in the same orders. The correlation of items can be obtained by the frequency of these items present at the same orders. When the dependent items are assigned to adjacent storage locations, order pickers will spend less time to complete customer orders, compared to the other storage assignment which treats items independently. This research provides optimization models to make sure that the storage locations of highly dependent items are nearby. Although the provided nonlinear integer programming can be transformed to a linear integer model, it is still too complex to deal with large problems. For a large number of items, two heuristic algorithms are proposed according to properties of optimal solutions in small problems. Numerical experiments are conducted to show the results of the proposed algorithms with the comparison of the random and class-based storage assignment.

Po-Hsun Kuo, Che-Wei Kuo

Selection of Approximation Model on Total Perceived Discomfort Function for the Upper Limb Based on Joint Moment

The aim of this study is to formulate the relationship between the total perceived discomfort of the upper limb and perceived discomforts of each degree of freedom (DOF). The perceived discomforts of each DOF were formulated as functions of the joint moment ratio based on the results of previous study, and then the function approximation model for the total perceived discomfort was investigated. The summary score of the rapid upper limb assessment (RULA), which is assumed as the total perceived discomfort, and the perceived discomforts of each DOF were taken as the objective and explanatory variables respectively. Three approximation models (i.e., the average, maximum, and radial basis function (RBF) network) were compared in terms of the accuracy of predicting the total perceived discomfort, and the RBF network was selected because its average and maximum error were lowest.

Takanori Chihara, Taiki Izumi, Akihiko Seo

Waiting as a Signal of Quality When Multiple Extrinsic Cues are Presented

While quality of a product or a service is considered one of the most important factors that influence consumer satisfaction, evaluating and determining product or service quality can be difficult for many consumers. People thus usually rely on extrinsic cues or surrogate signals of quality to tackle the information asymmetry problems associated with product/service quality. Unfortunately, research which has empirically documented the link between quality signals and perceived quality focus mainly on the situation where there exists only a single extrinsic cue. This study aims to investigate the interaction effect between multiple cues or signals on perceived quality. In particular, “waiting” or “queuing” in this study is no longer treated as a phenomenon that solicits disutility or negative emotions, but considered a signal of quality that has positive effect on consumer evaluation or satisfaction. Furthermore, this study hypothesized that the “waiting” can only be a positive signal under some specific situations especially when other quality signals (i.e., price and guidance) co-exist, and used experiments to rigorously test the hypotheses. By considering multiple cues simultaneously, this study lead to a better understanding of when and to what extent waiting can be use as a quality signal, and thus extend the original theory proposed by other researchers.

Shi-Woei Lin, Hao-Yuan Chan

Effect of Relationship Types on the Behaviors of Health Care Professionals

Human’s behavior and attitude can be highly influenced by two types of relationship, communal relationship and exchange relationship, and the moral-oriented social norms and the money-oriented market norms applied mechanically in these two relationships, respectively. While there is a great deal of general literature discussing the effect of relationship types on interpersonal interaction, there are limited number of studies focusing on the relationship types between organizations and their members and whether the introduction of monetary incentives affect the relationship types. Taking healthcare industry as an example, this study aims to explore how the types of relationship (communal vs. exchange relationship) between hospitals and medical staffs influence their attitude. Furthermore, we also want to investigate whether different types of reward (monetary vs. nonmonetary incentives) provided by hospitals affect or alter the types of relationships a medical staff originally had. We expect the results of this study can provide some suggestions for designing compensation plan in healthcare industry and important general managerial implications to managers in other industries.

Shi-Woei Lin, Yi-Tseng Lin

A Simulation with PSO Approach for Semiconductor Back-End Assembly

This paper studies a dynamic parallel machine scheduling problem in a hybrid flow shop for semiconductor back-end assembly. The facility is a multi-line, multi-stage with multi-type parallel machine group, and orders scheduled with different start time. As a typical make-to-order and contract manufacturing business model, to obtain minimal manufacturing lead time as main objective and find an optimal assignment of production line and machine type by stage for each order as main decisions. Nevertheless, some production behavior and conditions increase the complexity, and including order split as jobs for parallel processing and merged completion for shorten lead time. Complying quality and traceability requirement so each order only can be produced from one of qualified line(s) and machine type(s) and all jobs with the same order can only be produced in same assigned line and machine type with stochastic processing time. Lead time is counted from order start time to completion, including sequence dependent setup times. As a NP-hard problem, we proposed a simulation optimization approach, including an algorithm, particle swarm optimization (PSO) to search optimal assignment which achieving expected objective, a simulation model to evaluate performance, and combined with optimal computing budget allocation (OCBA) to reduce replications. It provides a novel applications using simulation optimization for semiconductor back-end assembly as a complex production system.

James T. Lin, Chien-Ming Chen, Chun-Chih Chiu

Effect of Grasp Conditions on Upper Limb Load During Visual Inspection of Objects in One Hand

Automated visual inspection systems based on image processing technology have been introduced to visual inspection processes. However, there are still technical and cost issues, and human visual inspection still plays a major role in industrial inspection processes. When a worker inspects small parts or products (e.g., lens for digital cameras, printed circuit boards for cell phones), they suffer from an upper limb load caused by handling objects in one hand and maintaining this awkward posture. Such workload causes damage to the hands, arms, and shoulders. So far, few studies have elucidated the effect of upper limb loads. Therefore, we conducted an experiment where the subjects were assumed to be visually inspecting small objects while handling them with one hand, and investigated the effect of grasp conditions on the upper limb load during tasks. We used electromyography, the joint angle, and subjective evaluation as evaluation indices. The results showed that the upper limb load due to the grasp condition differed depending on the upper limb site. Therefore, it is necessary to consider not only the muscle load but also the awkward posture, the duration of postural maintenance, and subjective evaluation when evaluating the upper limb load during such tasks.

Takuya Hida, Akihiko Seo

A Process-Oriented Mechanism Combining Fuzzy Decision Analysis for Supplier Selection in New Product Development

The selection of well-performed supplier involved in new product development (NPD) is one of the most important decision issues in the contemporary industrial field, in which the collaborative design is common. This paper proposes a systematical process-oriented mechanism combining fuzzy arithmetic operations for solving supplier selection problem in the NPD stage. In the proposed mechanism, the Design Chain Operations Reference model (DCOR) developed by Supply Chain Council (SCC) is adopted to describe NPD processes between the business and the candidate suppliers. These processes are deployed by four-level framework, including the top level, the configuration level, the process element level, and the implementation level. Then, the design structure matrix (DSM) is used to analyze the process relationship based on the results from the implementation level. The original DSM is partitioned by the Steward’s method to get reordered DSMs with the interactive process information with respect to the metrics provided by the DCOR. The fuzzy decision analysis is executed to obtain the weighted aggregated scores with respect to the DCOR metrics and to select the best suppliers for different components. Finally, a practical case in Taiwan is demonstrated to show the real-life usefulness of the proposed mechanism.

Jiun-Shiung Lin, Jen-Huei Chang, Min-Che Kao

Reliability-Based Performance Evaluation for a Stochastic Project Network Under Time and Budget Thresholds

This study develops a performance indicator, named project reliability, to measure the probability that a stochastic project network (SPN) can be successfully completed under both time and budget thresholds. The SPN is represented in the form of AOA (activity-on-arc) diagram, in which each activity has several possible durations with the corresponding costs and probability distribution. From the perspective of minimal path, two algorithms are proposed to generate upper and lower limit vectors which satisfy both time and budget, respectively. Next, the project reliability is evaluated in terms of such upper and lower limit vectors. The procedure of reliability evaluation can be applied to the SPN with arbitrary probability distribution. Such an indicator is a beneficial factor of the trade-off between the time and budget in a decision scenario.

Yi-Kuei Lin, Ping-Chen Chang, Shin-Ying Li

System Reliability and Decision Making for a Production System with Intersectional Lines

A three-phase procedure is proposed to measure the performance of a production system with intersectional lines by taking reworking actions into account. In particular, for a production system with intersectional lines, common station shares its capacity to all lines when processing. Hence, it is important to analyze the capacity of the common station while performance evaluation. This study addresses the system reliability as a key performance indicator to evaluate the probability of demand satisfaction. First, the production system is constructed as a production network (PN) by the graphical transformation and decomposition. Second, capacity analysis of all stations is implemented to determine the input flow of each station based on the constructed PN. Third, a simple algorithm is proposed to generate all minimal capacity vectors that stations should provide to satisfy the given demand. We evaluate the system reliability in terms of such minimal capacity vectors. A further decision making issue is discussed to decide a reliable production policy.

Yi-Kuei Lin, Ping-Chen Chang, Kai-Jen Hsueh

Customer Perceptions of Bowing with Different Trunk Flexions

Bowing has traditionally been used to signify politeness and respect. A chain of restaurants in Taiwan has recently required servers to bow at a 90° angle to increase the customers’ sense of being honored. Whether bowing at 90° is accepted by most consumers remains to be determined. This study analyzed 100 valid responses by questionnaire to determine consumer feelings regarding different degrees of trunk flexion when receiving bows. Results show that respondents typically believe that bowing at 30° was the most satisfactory, followed by 45°. Bowing at 45° or 60° causes customers to feel honored, and bowing at 90° induces the feelings of surprise and novelty but produces the lowest proportions of agreement to the at ease, necessary, and appropriate items. Previous studies had well validated that, when trunk is flexed to 90°, the posture is harmful because of the higher spinal loading. The finding of this study can be provided to the restaurant industry as a reference for service design from the perspective of server’s health.

Yi-Lang Chen, Chiao-Ying Yu, Lan-Shin Huang, Ling-Wei Peng, Liang-Jie Shi

A Pilot Study Determining Optimal Protruding Node Length of Bicycle Seats Using Subjective Ratings

This study preliminarily investigated the subjective discomfort and riding stability by requiring ten participants to ride straight-handles bicycles equipped with five seat-protruding node lengths (PNLs, 0–12 cm, in increments of 3 cm) of seats for 20 min. Results indicated that seat PNL caused differences in the participants’ subjective discomfort and stability scores. The various PNLs had significantly positive (r = 0.910,

p

< 0.01) and negative (r = −0.904,

p

< 0.05) correlations to the subjective discomfort rating for the perineum and ischial tuberosity, respectively. However, various PNLs did not affect riding stability during cycling. The findings of this study suggest that a 6 cm PNL is the optimal reference for bicycle seat designs.

Yi-Lang Chen, Yi-Nan Liu, Che-Feng Cheng

Variable Neighborhood Search with Path-Relinking for the Capacitated Location Routing Problem

The Location Routing Problem (LRP) integrates strategic decisions (facility location) and tactical decisions (vehicle routing) aimed at minimizing the total cost associated with location opening cost and routing cost. It belongs to the class of NP-hard problems. In this study, we present a variable neighborhood search with path-relinking (VNSPR) for solving the CLRP. The path-relinking procedure is integrated into the variable neighborhood search (VNS) framework. We tested our heuristic approach on three well-know CLRP data sets and the results were compared with those reported in the literature. Computational results indicate that the proposed VNSPR heuristic is competitive with existing approaches for the CLRP.

Meilinda F. N. Maghfiroh, A. A. N. Perwira Redi, Vincent F. Yu

Improving Optimization of Tool Path Planning in 5-Axis Flank Milling by Integrating Statistical Techniques

Optimization of the tool path planning in 5-axis flank milling of ruled surfaces involves search in an extremely high-dimensional solution space. The solutions obtained in previous studies suffer from lengthy computational time and suboptimal results. This paper proposes an optimization scheme by integrating statistical techniques to overcome these problems. The scheme first identified significant factors in the tool path planning that influence the machining error of a machined surface by a first sampling plan. We then conducted a series of simulation experiments designed by the two-level fractional factorial method to generate experimental data with various settings. A regression model was constructed with Response Surface Methodology (RSM) that approximates the machining error in terms of those identified factors. This simplified model accelerates estimation of the objective function, computed as a black-box function in previous studies, with less computation. Test results show that the proposed scheme outperforms PSO in both the computational efficiency and the solution quality.

Chih-Hsing Chu, Chi-Lung Kuo

A Multiple Objectives Based DEA Model to Explore the Efficiency of Airports in Asia–Pacific

Airport efficiency is an important issue for each country. The classical DEA models use different input and output weights in each decision making unit (DMU) that seems not reasonable. We present a multiple objectives based Data Envelopment Analysis (DEA) model which can be used to improve discriminating power of DEA method and generate a more reasonable input and out weights. The traditional DEA model is first replaced by a multiple objective linear program (MOLP) that a set of Pareto optimal solutions is obtained by genetic algorithm. We then choose a set of common weights for inputs and outputs within the Pareto solutions. A gap analysis is included in this study that can help airports understand their gaps of performances to aspiration levels. For this new proposed model based on MOLP it is observed that the number of efficient DUMs is reduced, improving the discrimination power. Numerical example from real-world airport data is provided to show some advantages of our method over the previous methods.

James J. H. Liou, Hsin-Yi Lee, Wen-Chein Yeh

A Distributed Constraint Satisfaction Approach for Supply Chain Capable-to-Promise Coordination

Order promising starts with the available-to-promise (ATP) quantities. The short is then promised by capable-to-promise (CTP) quantities. Supply chain CTP coordination can be viewed as a distributed constraint satisfaction problem (DCSP) composed of a series of constraints about slack capacity, materials and orders distributed among supply chain members. To solve this problem, supply chain members should consider and resolve their intra- and inter-constraints via supply chain coordination. This research has proposed a DCSP approach for supply chain CTP coordination. With this approach, supply chain members can collaboratively determine a feasible integral supply chain CTP production plan.

Yeh-Chun Juan, Jyun-Rong Syu

Design and Selection of Plant Layout by Mean of Analytic Hierarchy Process: A Case Study of Medical Device Producer

The objectives of this research are to design the alternatives of plant layout and to select the most appropriate layout in which many criteria, both qualitative and quantitative criteria, are taken into account by mean of Analytic Hierarchy Process. Proximity requirements between each pair of facilities are determined by taking density of flow, harmful effect to nearby facilities and appropriateness into consideration. Furthermore, simulation approach is employed in order to evaluate the performance of quantitative criteria such as number of work in process and time in system of each alternative. The result of this research provides guideline to facility planner in order to select the most appropriate layout subject to a set of decision criteria.

Arthit Chaklang, Arnon Srisom, Chirakiat Saithong

Using Taguchi Method for Coffee Cup Sleeve Design

The present study aims to design the coffee cup sleeve which can detect the temperature of coffee and notify the consumers. When consumers find that the coffee is going to become cool, then they can drink the coffee quickly before it become sour. Due to the limitation of cost, thermal label is adopted to cohere on the coffee cup sleeve for detecting and notifying the important temperature. However, the temperature of coffee and the coffee cup sleeve are different which have to be taken into consideration by the thermal label. Different thermal labels are suitable for different temperature detection. Taguchi method is used for optimizing the selection of thermal labels for the importation temperature. Finally the surface of coffee cup sleeve with thermal labels on it is well designed to be a real product.

Yiyo Kuo, Hsin-Yu Lin, Ying Chen Wu, Po-Hsi Kuo, Zhi-He Liang, Si Yong Wen

Utilizing QFD and TRIZ Techniques to Design a Helmet Combined with the Wireless Camcorder

The wireless transmission products become more important and popular in recent years because of their high efficiency and convenience. This study hopes to enhance its function and transform the product into a brand new one as well as to increase the added value of the wireless AV product substantially. In this study, a questionnaire designed with Likert scale is used to understand consumer’s demand when wearing a construction site helmet which is combined with the wireless camcorder. With the application of quality function deployment (QFD), the key elements of product design can be more consistent with the voices of consumers. Next in the process of design-conducting and problem-solving, some TRIZ methods, such as selecting pairs of improving and worsening parameter, applying the contradiction matrix and 40 innovative principles, are applied to achieve a creative thinking and innovative approach for the product design. At last, the study provides an innovative design for the wireless video/audio transmission construction site helmet, in which the wide-angle lens camcorder is mounted at the front of the site helmet internally and the asymmetric ventilation holes are designed in the exterior part of the helmet. Finally, the Pro/Engineer drawing software is applied to finish the design drawing.

Shu-Jen Hu, Ling-Huey Su, Jhih-Hao Laio

South East Asia Work Measurement Practices Challenges and Case Study

South-East-Asia has been producing wide range of products since decades ago, and hence it is often dubbed as the world’s manufacturing-hub. In terms of operation, physical size and capital investment, there are family-owned businesses and Fortune 100 companies’ biggest off-shore facilities co-existing. As for its workforce portfolio, the majority used to be of the kind that was non-skilled labor intensive. However, there had been workforce capability substantial upgrading, resulting in the niches and specialties development in automation. Nevertheless, the awareness of work measurement impact on productivity performance remained low. The literature shows that studies on work measurement practices in this region are very limited. It is an absolute waste if there have been tremendous improvements deployed in the machinery, systems, and tools, but they do not function to their maximum capacity because their interaction with the labor is not optimized, and if there is poor work measurement to understand the ‘productivity-leak-factor’ in the operation. This paper shares the literature on work measurement-related studies that are carried out in this region. It also discusses data collection and preliminary findings of the impact of work measurement method. It is found that much needs to be done to instill the appropriate awareness and understanding of work measurement.

Thong Sze Yee, Zuraidah Mohd Zain, Bhuvenesh Rajamony

Decision Support System: Real-Time Dispatch of Manufacturing Processes

This research has highlighted the role of real-time dispatching (RTD) tools in the development of 300 mm manufacturing machinery systems. Dispatching production and distribution in the real-world 300 mm manufacturing environment is an extremely complex task requiring the consideration of numerous constraints and objectives. Decision support system (DSS) created for this purpose can potentially be used to provide support for related tasks, such as real-time optimization, operational planning, quality certificated, service and maintenance. The DSS comprises the ability to reinforce the RTD system which support both process operator and manager in the decision making process, allowing them to take full-scale of the physical system to implement it in a way where the optimized process control variables are under statistical control, resulting in optimized output that, in turn, secure higher productivity and improved quality.

Chung-Wei Kan, An-Pin Chen

The Application of MFCA Analysis in Process Improvement: A Case Study of Plastics Packaging Factory in Thailand

This research aims to apply the Material Flow Cost Accounting (MFCA) for process improvement of the target product, 950 cc. plastic water bottles, a case study company in Thailand. The production line of this product consists of five processes, crushing, mixing, blow molding, printing, and packing. The data collection was carried out for all processes and analyzed based on MFCA procedure. During the process of MFCA, quantity of input and output material, material cost, system cost and energy cost were presented. Then, the cost of positive and negative products can be distinguished based on mass balancing for all processes. The results from MFCA calculation showed that the highest negative product cost occurred at blow molding process. Then, the operations flow at blow molding process was analyzed using motion study and ECRS concept in order to eliminate production defects. Finally, the improvement solution was proposed and the results showed that the defects were reduced 26.07 % from previous negative product cost.

Chompoonoot Kasemset, Suchon Sasiopars, Sugun Suwiphat

Discussion of Water Footprint in Industrial Applications

Economic growth in the past half century brought an unprecedented comfortable life, but also had over-consumed Earth’s natural resources. Species extinction and global warming caused by CO

2

emission make us start thinking highly of the surrounding environment. Therefore, the concepts of ecological footprint and carbon footprint have been proposed for assessing the extent of destruction on global environment. In year 2002, Dr. Hoekstra put forward the concept of water footprint for water consumption issues. The main concern is the freshwater used directly and indirectly by consumers or producers, including tracing the three key constituents as blue-, green-, and gray-water. Past studies of the water footprint have gathered a lot of information about agricultural water consumptions, but relatively few were studied for industrial applications. To face the possible shortage of water resources in the future, industries should take a serious attitude to water footprint issues. This study suggests that the water footprint in industrial applications can be used as a basis for improving process water usage, sewage treatment method, water cycle reuse and factories design. It will eventually help reach the objectives of saving water, reducing manufacturing costs, complying with international environmental protection requirements, and enhancing the corporate image and visibility.

Chung Chia Chiu, Wei-Jung Shiang, Chiuhsiang Joe Lin

Mitigating Uncertainty Risks Through Inventory Management: A Case Study for an Automobile Company

In recent years, global environment has changed dramatically due to unpredictable operational risks, disruption risks, natural and man-made disasters, global financial and European debt crisis. This greatly increases the complexity of the automotive supply chain. In this paper we investigate the inventory policy of the aftermarket parts for an automotive company. The key findings and insights from this study are: (1) to mitigate the risk of disruptive supply chain, enterprises need to reduce the monthly supplies of high priced products, (2) to improve profit, cash flow and fill rate, the use of A, B and C inventory management system is critical, (3) the case study provides managerial insights for other industries to develop an efficient inventory management system in a competitive and uncertain environment.

Amy Chen, H. M. Wee, Chih-Ying Hsieh, Paul Wee

Service Quality for the YouBike System in Taipei

In this study, we focused on the service quality for the public bicycle system, YouBike System, in Taipei, and used the station setting at the National Taiwan University of Science and Technology (NTUST) for the case study. YouBike System refers to the “rent-it-here, leave-it-there” bike sharing service provided by the Taipei City Government. We adopted the service quality models developed by Parasuraman, Zeithaml and Berry in 1970s to conduct the research. In the first stage before launching the station at the NTUST, a pre-using questionnaire was designed and distributed to the students at the NTUST to collect the opinions and their expectations about the YouBike System. Then, an after-using questionnaire was designed and distributed to the students at the NTUST to investigate whether the service quality of the YouBike System meet their expectations and what is the service level provided by the YouBike system. The after-using survey was conducted after one month of launching the station at the NTUST. The results analyzed from both sets of surveys would provide valuable information for the Taipei City Government to continuing improves their public transportation policy.

Jung-Wei Chang, Xin-Yi Jiang, Xiu-Ru Chen, Chia-Chen Lin, Shih-Che Lo

Replenishment Strategies for the YouBike System in Taipei

In this study, we focused on the bike replenishment strategies for the public bicycle system, YouBike System, in Taipei. YouBike System refers to the “rent-it-here, leave-it-there” bike sharing service provided by the Taipei City Government. Recently, the bicycle system has become popular and has been used by over one million riders. During the rush hours, when people go on or off duty, there would be: (1) no bicycle for renting at the particular rental stations; or (2) no space to park bicycles at the rental stations near schools or MRT stations. These problems can be troublesome to many users/members of the YouBike System. In order to mimic the YouBike System in Taipei, we used computer simulation software to simulate the movement of the bicycles from one bicycle station to other bicycle station. As a result, our goal is to build an on-line monitoring system to provide real-time usage of the bikes and parking space of all YouBike stations. Feasible solutions and optimal strategies were proposed in this study to move bicycles between bicycle rental stations to balance: (1) number of bicycles in the rental station; and (2) number of available parking space for the bicycles in the bicycle rental station.

Chia-Chen Lin, Xiu-Ru Chen, Jung-Wei Chang, Xin-Yi Jiang, Shih-Che Lo

A Tagging Mechanism for Solving the Capacitated Vehicle Routing Problem

The Vehicle Routing Problem (VRP) is one of the difficult problems in combinatorial optimization and has wide applications in all aspects of our lives. In this research, a tag-based mechanism is proposed to prevent the formation of subtours in constructing the routing sequences, while each tour does not exceed the capacity of the vehicles and the total distance travelled is minimized. For each node, two tags are applied, one on each end, and to be assigned with different values. Two nodes can be connected, only if the tag value at one end of a node matches one of the end tag values of another node. The model is formulated as a mixed integer linear programming problem. Some variations of the vehicle routing problems can also be formulated in a similar manner. If the capacity of the vehicles is infinite, i.e., capacity restrictions are removed, the VRP reduces to the multiple Travelling Salesman Problem (mTSP). Computational results indicate that the proposed model is quite efficient for small sized problems.

Calvin K. Yu, Tsung-Chun Hsu

Two-Stage Multi-Project Scheduling with Minimum Makespan Under Limited Resource

Project scheduling is one of the key components in the construction industry and has a significant effect on the overall cost. In business today, project managers have to manage several projects simultaneously and often face challenges with limited resources. In this paper, we propose a mixed integer linear programming formulation for the multiple projects scheduling problem with one set of limited resource to the identical activities within the same project or among different projects and minimum makespan objective. The proposed model is based on the Activity on Arrow (AOA) networks, a two-stage approach is applied for obtaining the optimal activities scheduling. At the first stage, the minimum makespan for completing all projects is computed. By fixing the minimum completion time obtained from the first stage, the second stage computation is then to maximize the slack time for each activity in order to obtain the effective start and finish time of each activity in constructing the multiple projects schedule. The experimental results have demonstrated practical viability of this approach.

Calvin K. Yu, Ching-Chin Liao

A Weighting Approach for Scheduling Multi-Product Assembly Line with Multiple Objectives

A flexible production scheduling in the assembly line is helpful for meeting the production demands and reducing the production costs. This paper considers the problem of scheduling multiple products on a single assembly line when multiple objectives exist. The specific objectives are to reduce the production changeovers and minimize overtime cost with the restrictions on production demands, due dates, and limited testing space. This system model derives from a real case of a company producing point of sale systems and a mixed integer programming model is developed. Different sets of weights that represent the priorities of specific objectives are applied to the model. By manipulating and adjusting these weights, it is capable to generate the desired production schedule that satisfies production managers’ need. An example has been solved for illustrating the method. Preliminary findings suggest that the weighting approach is practicable and can provide valuable information for aggregate planning.

Calvin K. Yu, Pei-Fang Lee

Exploring Technology Feature with Patent Analysis

The patent literature has documented 90 % of the world’s technological achievements, which are protected by the patent law of each country. But with the increasingly competitive technology, enterprises have started the patent strategy research and attached great importance to patent analysis. The patent analysis uses statistics, data mining, and text mining to convert the information into a competitive intelligence that facilitates corporate decision making and prediction. Thus, the patent analysis has become a corporate weapon for long-term survival and protection of commercial technologies. The patent analysis in the past, compared with the trend analysis, mostly conducted the predictive analysis of a number of keywords and patents through the statistical analysis approach. However, the keywords found were limited to the already mature technology and could not locate the implicit emerging terms, so the patent analysis in the past could only find the words of obvious importance, but fail to find the emerging words that are unobvious yet will have a major impact on future technologies. Therefore, how to find these words of a low-frequency nature to make prediction of the correct trend is an important research topic. This study used the Chinese word segmentation system to find the words of the patent documents and extracted the words according to the probability model of the Cross Collection Mixture Model. This model targets the words under changes in the time series. The background model and the common theme in the model will eliminate frequent words without the meaning of identification and collect words persistently appearing across time. This method can quickly screen enormous volumes of patent documents, extract from the patent summary emerging words of a low-frequency nature, successfully filter out the fashion words, and accurately detect the future trends of emerging technologies from the patent documents.

Ping Yu Hsu, Ming Shien Cheng, Kuo Yen Lu, Chen Yao Chung

Making the MOST® Out of Economical Key-Tabbing Automation

Industrial engineers observe and analyze movements and steps taken by a worker in completing a given task. The data obtained is defined and summed up through coded values to predetermine the motion time of process activities that occur within the production line. Although softwares have been developed to ease the recording and computation of such studies, they are expensive and require trainings to operate. The use of Maynard Operations Sequence Technique (MOST

®

) system has been recognized as one of the standards for predetermined time calculation. However, the sequential breakdown and movement analysis techniques of this system involving coded values can be complicated, time-consuming and tedious. This is worsened when the production line contains numerous activities with lengthy processes. The objective of this paper is thus to introduce an easy and cost-effective solution that uses simple Microsoft Excel macros key-in method which enables a trained analyst to record, determine and generate a MOST

®

time study within seconds. Case studies performed have shown that this method speeds up the calculation process at a 50–60 % rate faster than the ordinary individual code definition and tabulation recording method. As such, it has been proven to save time and eliminate the possibility of a miscalculation.

P. A. Brenda Yap, S. L. Serene Choo, Thong Sze Yee

Integer Program Modeling of Portfolio Optimization with Mental Accounts Using Simulated Tail Distribution

Since Markowitz introduced mean–variance portfolio theory, there have been many portfolio selection problems proposed. One of them is the safety-first portfolio optimization considering the downside risk. From behavioral portfolio theory, investors may not consider their portfolios as a whole. Instead, they may consider their portfolios as collections of subportfolios over many mental accounts. In this study, we present a mixed-integer programming model of portfolio optimization considering mental accounts (MAs). In this study, varied MAs are described by different level of risk-aversion. We measure the risk as the probability of a return failing to reach a threshold level, called the downside risk. An investor in each MA specifies the threshold level of return and the probability of failing to reach this return. Usually the portfolio’s returns are assumed as normally distributed, but this move may underestimate the downside risks. Accordingly, we estimate the downside risk by using models utilizing extreme-value theory and copula. We generate scenarios of the tail distribution based on this model, on which the mixed-integer program is applied. In the end, we use historical data to back test our model and the results are consistent with what they expected. These actions result in a better understanding of the relation between investor goals and portfolio production, and portfolio optimization.

Kuo-Hwa Chang, Yi Shou Shu, Michael Nayat Young

Simulated Annealing Algorithm for Berth Allocation Problems

Maritime transport is the backbone of global supply chain. Around 80 % of global trade by volume is carried by sea and is handled by ports worldwide. The fierce competition among different ports forces the container port operators to improve the terminal operation efficiency and competitiveness. This research addresses the dynamic and discrete berth allocation problem (BAP) which is critical to the terminal operations. The objective is to minimize the total service times for vessels. To solve the NP-hard BAP problem, we develop a simulated annealing (SA) algorithm to obtain the near optimal solutions. Benchmark instances from the literature are tested for the effectiveness of the proposed SA and compared with other leading heuristics in the literature. Computational results show that our SA is competitive and find the optimal solutions in all instances.

Shih-Wei Line, Ching-Jung Ting

Using Hyperbolic Tangent Function for Nonlinear Profile Monitoring

For most of the Statistical process control (SPC) applications, the quality of a process or product is measured by one or multiple quality characteristics. In some particular circumstances, quality characteristics depend on the relationship between the response variable and one and/or explanatory variables. Therefore, such a quality characteristic is represented by a function or a curve, which is called a ‘profile’. In this paper, a new method of using the hyperbolic tangent function will be addressed for modeling the vacuum heat treatment process data. The hyperbolic tangent function approach is compared to the smoothing spline approach when modeling the nonlinear profiles. The vector of parameter estimates is monitored by using the Hotelling’s

T

2

for the parametric approach and by the metrics method for the nonparametric approach. In Phase I, the proposed hyperbolic tangent approach is able to correctly identify the outlying profiles.

Shu-Kai S. Fan, Tzu-Yi Lee

Full Fault Detection for Semiconductor Processes Using Independent Component Analysis

Nowadays, semiconductor industry has been marching toward an increasingly automated, ubiquitous data gathering production system that is full of manufacturing complexity and environmental uncertainty. Hence, developing an effective fault detection system is virtually essential for the semiconductor camp. This paper focuses on the physical vapor deposition (PVD) process. In order to rectify the aforementioned difficulties that could realistically take place, an independent component analysis approach is proposed that decomposes every process parameter of interest into the basis data. A fault detection method is presented to identify the faults of the process and construct a process monitoring model by means of the obtained basis data.

Shu-Kai S. Fan, Shih-Han Huang

Multi-Objective Optimal Placement of Automatic Line Switches in Power Distribution Networks

The installation of automatic line switches in distribution networks provides major benefits to the reliability of power distribution systems. However, it involves an increased investment cost. For distribution utilities, obtaining a high level of reliability while minimizing investment costs constitutes an optimization problem. In order to solve this problem, the present paper introduces a computational procedure based on Non-dominated Sorting Genetic Algorithm (NSGA-II). The proposed methodology is able to obtain a set of optimal trade-off solutions identifying the number and placement of automatic switches in distribution networks for which we can obtain the most reliability benefit out of the utility investment. To determine the effectiveness of the procedure, an actual power distribution system was considered as an example. The system belongs to Taiwan Power Company, and it was selected to drive comparisons with a previous study. The result indicates improvements in system reliability indices due to the addition of automatic switching devices in a distribution network, and demonstrates the present methodology satisfies the system requirements in a better way than the mentioned previous study.

Diego Orlando Logrono, Wen-Fang Wu, Yi-An Lu

The Design of Combing Hair Assistive Device to Increase the Upper Limb Activities for Female Hemiplegia

Many researches show that the progress of the upper limb function of patients with more than one year apoplexy appears to be Learned Nonuse. This research takes concepts of the Constraint-induced Movement Therapy and User-Centered Design and develops the combing hair assistive device to increase the upper limb activities for female Hemiplegia. We adopt the AD-TOWS (Assistive Devices-Threats, Opportunities, Weaknesses, and Strengths) matrix to develop 33 design concepts among which 4 concepts are screened to make models, and then invite 5 participators in the experiment. By analyzing the results of upper limb lifting angle, the upper limb movement angle forced by the “Joint Adjustable Device” is the biggest, which is followed by the “Comb Convertible Device”, and then is the “Comb Convertible Lengthening Device”. The upper limb average angle of operating the above mentioned three assistive devices are bigger than that of operating the existing devices. By the result of the part unable to be combed, we find that the most difficult action to users who use the existing long-handled comb is to comb their sutural bone and occipital bone, however, the “Double-Handled Device” is good at improving the action unable to be done.

Jo-Han Chang

Surgical Suites Scheduling with Integrating Upstream and Downstream Operations

Surgical operations are a critical function for hospitals because they are responsible for almost two-thirds of all profits. Hence, medical resources associated with surgical operations and operation rooms (OR) should be utilized efficiently. Conducting an overall plan for the allocation of medical resources and capacities used in surgical operations is complicated because numerous types of resources are involved in an OR scheduling problem. Furthermore, the upstream and downstream operations of a surgery, such as the number of beds for preoperative examination and intensive care unit, also significantly affect OR schedule performance. The objective of OR scheduling is to minimize the overtime cost of surgical operations and the idle cost of ORs. Using the concept of OR suites and modes, we construct a mixed integer linear programming model by considering surgical resources and the corresponding upstream and downstream operations. A five-stage heuristic method is proposed to solve large-scale problems effectively and efficiently. A numerical study is conducted, and the results show that the proposed method can reduce the total cost of managing operation rooms and improve the quality of surgical services.

Huang Kwei-Long, Lin Yu-Chien, Chen Hao-Huai

Research on Culture Supply Chain Intension and Its Operation Models

In recent years, China has become the cultural industry toward highly centralized, with the rapid development of international direction. Between the competitions of the 21st century, not a business enterprise competition, but competition in the supply chain and supply chain, supply chain is the development trend of industry chain as the value chain of cultural products. Supply chain functions, like integration, and optimization, are gradually reflected in the cultural industries. The cultural characteristics of the supply chain are proposed in this paper. From the perspective of the cultural industry and supply chain’s intension, several cultural supply chain operating models are given in this paper. From the angle of the supply chain finance and capital flow, the supply chain operation mechanism is presented for how to promoting the culture of the supply chain, which is provided a reference for increasing the cultural development of the supply chain.

Xiaojing Li, Qian Zhang

Power System by Variable Scaling Hybrid Differential Evolution

In this paper, the variable scaling hybrid differential evolution (VSHDE) used to solve the large-scale static economic dispatch problem. Different from the hybrid differential evolution (HDE), the concept of a variable scaling factor is used in the VSHDE method. The variable scaling factor based on the 1/5 success rule of evolution strategies (ESs) is embedded in the original HDE to accelerate the search for the global solution. The use of the variable scaling factor in the VSHDE can overcome the drawback of the fixed and random scaling factor used in HDE. To alleviate the drawback of the penalty method for equality constraints, the repair method is proposed. One 40-unit practical static economic dispatch (SED) system of Taiwan Power Company is used to compare the performance of the proposed method with HDE. Numerical results show that the performance of the proposed method combining with the repair method is better than the other methods.

Ji-Pyng Chiou, Chong-Wei Lo, Chung-Fu Chang

Investigating the Replenishment Policy for Retail Industries Under VMI Strategic Alliance Using Simulation

Recently, retail industries are booming rapidly because of the convenience and low price. However, as the competition increases, inventory shortage becomes a serious problem for both retailer and supplier. Therefore, developing a suitable inventory management for retailer and supplier has been a pertinent area of study in recent years. Some strategies such as Quick Response (QP), Continuous replenishment (CR), and Vendor Managed Inventory (VMI) have been proven to have impact on retailer-supplier inventory. However, only qualitative research are devoted in these strategies which might not provide detailed insights of the usefulness for using these strategies. Therefore, this paper investigates VMI strategies using simulation models and develops the replenishment policy for implementing VMI. Furthermore, this research uses Automatic Pipeline Inventory Order Based Production Control System (APIOBPCS) to identify the factors of using VMI in retailer-supplier inventory management and a simulation model based on these factors is developed to achieve the replenishment policy. The results show that total cost will be reduced and inventory turnover can be increased using this replenishment policy in VMI.

Ping-Yu Chang

Applying RFID in Picker’s Positioning in a Warehouse

As the RFID technology gradually matures, the research on the RFID technology-based positioning system has attracted more attention. The RFID technology applied to positioning can be used for orientation recognition, tracking moving trajectories, and optimal path analysis, as well as information related to the picker’s position. According to previous literatures, warehousing management consumes high cost and time in business operation, more specifically; picking is one of the most costly operations in warehousing management, which accounts for 55 % of total warehousing cost. Therefore, this study constructed an actual picking environment based on the RFID technology. This system uses the back-propagation network method to analyze the received signal strength indicator (RSSI), so as to obtain the position of the picker. In addition, this study applied this locating device to picking activities, and discussed the effects of the positioning device on different picking situations.

Kai Ying Chen, Mei Xiu Wu, Shih Min Chen

An Innovation Planning Approach Based on Combining Technology Progress Trends and Market Price Trends

Innovation planning is important for manufactures to maximize the payoffs of their limited research and development expenditures. The key to the success of such innovation planning relies on a valid approach to estimate the value of each R&D project can produce. The purpose of this research is to build a model that considers a broad spectrum of trends in technology development and market price trends. Base on the assumption that the market prices can be a good indication of customer values, this modeling method collects historical product feature data, as well as their historical market prices and trains a neural network to track how electronic product specifications evolutions affect market prices. Predictions can be made from the behavior of the trained model to evaluate the value of each product improvement and, therefore, effective innovation plan can be made based on this model. The structure of this paper is threefold. First, it describes the evolutionary patterns of electronic products and their market prices. Second, it proposes artificial neural network methods to model the evolutionary processes; predictions concerning digital cameras to prove the validity of the model. Third, this research discusses the implications of these findings and draws conclusions.

Wen-Chieh Chuang, Guan-Ling Lin

Preemptive Two-Agent Scheduling in Open Shops Subject to Machine Availability and Eligibility Constraints

We address the scheduling problem in which two agents, each with a set of preemptive jobs with release dates, compete to perform their jobs on open shop with machine availability and eligibility constraints. The objective of this study is to minimize make span, given that one agent will accept a schedule of time up to Q. We proposed a heuristic and a network based linear programming to solve the problem. Computational experiments show that the heuristic generates a good quality schedule with a deviation from the optimum of 0.25 % on average and the network based linear programming model can solve problems up to 110 jobs combined with 10 machines.

Ming-Chih Hsiao, Ling-Huey Su

Supply Risk Management via Social Capital Theory and Its Impact on Buyer’s Performance Improvement and Innovation

Today’s supply chain managers are facing plenty of risks due to uncertainties of inbound supplies. Buyer must learn how to mitigate those unexpected risks. In this study, we explore supply risk management via structural, relational, and cognitive approaches from a buying firm’s perspective based on the social capital theory. We also propose that the three forms of social capitals are positively related to buyer–supplier performance improvements. Consequently, the performance improvement of buyer–supplier will positively influence the innovation performance.

Yugowati Praharsi, Maffie Linda Araos Dioquino, Hui-Ming Wee

Variable Time Windows-Based Three-Phase Combined Algorithm for On-Line Batch Processing Machine Scheduling with Limited Waiting Time Constraints

In this paper, a variable time windows-based three-phase combined algorithm is proposed to address the scheduling problem of on-line batch processing machine for minimizing total tardiness with limited waiting time constraints and dynamic arrivals in the semiconductor wafer fabrication system (SWFS). This problem is known to be NP-hard. In the first phase, the on-line information of scheduling parameters is preserved and sent. In the second phase, the computational results of reforming and sequencing are obtained. In the third phase, the super-hot batch is loaded. With the rolling horizon control strategy, the three-phase combined algorithm can update solution continually. Each interval of rolling horizon is a time window. The length of each time window is variable. The experiments are implemented on the real-time scheduling simulation platform of SWFS and ILOG CPLEX to demonstrate the effectiveness of our proposed algorithm.

Dongwei Yang, Wenyou Jia, Zhibin Jiang, You Li

Optimal Organic Rankine Cycle Installation Planning for Factory Waste Heat Recovery

As Taiwan’s industry developed rapidly, the energy demand also rises simultaneously. In the production process, there’s a lot of energy consumed in the process. Formally, the energy used in generating the heat in the production process. In the total energy consumption, 40 % of the heat was used in process heat, mechanical work, chemical energy and electricity. The remaining 50 % were released into the environment. It will cause energy waste and environment pollution. There are many ways for recovering the waste heat in factory. Organic Rankine Cycle (ORC) system can produce electricity and reduce energy costs by recovering the waste of low temperature heat in the factory. In addition, ORC is the technology with the highest power generating efficiency in low-temperature heat recycling. However, most of factories are still hesitated because of the implementation cost of ORC system, even they generate a lot of waste heat. Therefore, this study constructed a nonlinear mathematical model of waste heat recovery equipment configuration to maximize profits, and generated the most desirable model and number of ORC system installed by using the particle swarm optimization method.

Yu-Lin Chen, Chun-Wei Lin

Evaluation of Risky Driving Performance in Lighting Transition Zones Near Tunnel Portals

Driving behavior is affected by rapidly varying lighting conditions that frequently occur in transition zones near tunnel portals. When entering a tunnel in daytime, car drivers might encounter various difficulties in keeping high performance for safety concerns: (1) Physiological issues caused by high-level glare—the adaptation of the eye requires recovery time, during which time there will be impaired vision and reduced visibility of on-road objects; (2) Psychological issues caused by visual discomfort and distraction—limited resources for performing information processing are shared by the distracting and disturbing sensation; (3) Behavioral issues caused by driving patterns of the driver and other road users—many drivers reduce their speeds when entering the tunnel; thus a car driver must react to the sudden speed change. This study investigated the records of traffic accidents on Zurich highways in tunnel areas and conducted experiments using a driving simulator. The analysis of accident records shows that the frequency of accidents increases near tunnel portals. Experimental results show that discomfort glare impairs both peripheral visual attention and motion discrimination in simulated driving tasks. In conclusion, we suggest considering tunnel portals as a key factor causing elevated risk in traffic safety. Lighting designs and road layout near tunnel portal areas should be carefully defined.

Ying-Yin Huang, Marino Menozzi

Application of Maple on Solving Some Differential Problems

This article takes the mathematical software Maple as the auxiliary tool to study the differential problem of some types of functions. We can obtain the infinite series forms of any order derivatives of these functions by using differentiation term by term theorem, and hence greatly reduce the difficulty of calculating their higher order derivative values. On the other hand, we propose some functions to evaluate their any order derivatives, and calculate some of their higher order derivative values practically. The research methods adopted in this study involved finding solutions through manual calculations and verifying these solutions by using Maple. This type of research method not only allows the discovery of calculation errors, but also helps modify the original directions of thinking from manual and Maple calculations. For this reason, Maple provides insights and guidance regarding problem-solving methods.

Chii-Huei Yu

Six Sigma Approach Applied to LCD Photolithography Process Improvement

Liquid Crystal Display (LCD) makes to pursue light and thin trend, and towards high resolution development. To promote the LCD high resolution, the process requires more precise micromachining. The major key is lithography, but also generally known as the photolithography process. This research uses Six Sigma DMAIC steps (Define, Measure, Analyze, Improve, Control) to an empirical study of the pattern pitch machining process in a domestic optoelectronic manufacturer. Constructed in the photolithography process, the pattern pitch machining process capability improves and a process optimization prediction mode. Taguchi method is used to explore the parameters combination of photolithography process optimization and to understand the impact of various parameters. The findings of this research show that C

pk

can upgrade from 0.85 to 1.56 which achieve quality improvement goals and to enhance the LCD photolithography process capability.

Yung-Tsan Jou, Yih-Chuan Wu

A Study of the Integrals of Trigonometric Functions with Maple

This paper uses Maple for the auxiliary tool to evaluate the integrals of some types of trigonometric functions. We can obtain the Fourier series expansions of these integrals by using integration term by term theorem. On the other hand, we propose some related integrals to do calculation practically. Our research way is to count the answers by hand, and then use Maple to verify our results. This research way can not only let us find the calculation errors but also help us to revise the original thinking direction because we can verify the correctness of our theory from the consistency of hand count and Maple calculations.

Chii-Huei Yu

A Study of Optimization on Mainland Tourist Souvenir Shops Service Reliability

Recently, Taiwan government launched tourism for mainland tourists, who have become the largest inbound tourists. Business opportunities burst, especially a souvenir shop. With rapid growths of souvenir shops, they compete with each other intensely. In order to survive in the competition market, a shop has to promote its service system. The best practice is to assess and optimize the current status of service quality to maintain a high reliability on its service systems. Reliability is a key indicator for the service quality, which is often applied to manufacturing and service. Failure Mode and Effects Analysis (FMEA) is an important tool for analyzing the reliability to forecast a system failure risk. This study applies FMEA to establish a failure risk evaluation model for a mainland tourist souvenir shop. Store H is validated by this approach, which can prioritize the potential failure items of Store H to improve the service quality and suggest persuasive corrective actions. The proposed model essentially ameliorates service level, effectively reduces the mainland tourist souvenir shops failure risks, and enhance the reliability of service. This approach is not only for the mainland tourist souvenir shops, but also be widely used in the general souvenir shops.

Kang-Hung Yang, Li-Peng Fang, Z-John Liu

The Effects of Background Music Style on Study Performance

Due to the increasing popularity of personal digital devices, many students listen to music while they study. It is however a controversial issue whether music listening is helpful to study performance. This study investigates the effects of different types of background music on study performance among college students through lab experiments. Two major categories of study activities (i.e., reading comprehension and mathematical computation) are examined for four different treatments of background music style (i.e., soft music, rock music, heavy metal music, and no music). For each student subject, objective measures, such as test scores and heart rates, were recorded for all conditions of the experiment design. Subjective measures concerning treatment evaluations along with personal preference and behaviors on music listening were instrumented in the individual interviews after the experiments. Data analysis on the objective measures indicates that neither test scores nor heart rates of reading comprehension and mathematic computation for different styles of background music are with statistical significance. By further cross-referencing with the subjective measures, our results suggest that, for a better studying performance, college students may choose to listen to background music with preferred music for reading activities but non-preferred music for mathematic computation.

An-Che Chen, Chen-Shun Wen

Using Maple to Study the Multiple Improper Integral Problem

Multiple improper integral problem is closely related with probability theory and quantum field theory. Therefore, the evaluation and numerical calculation of multiple improper integrals is an important issue. This paper takes the mathematical software Maple as the auxiliary tool to study some types of multiple improper integrals. We can obtain the infinite series forms of these types of multiple improper integrals by using integration term by term theorem. On the other hand, we propose some examples to do calculation practically. Our research way is to count the answers by hand, and then use Maple to verify our results. This research way can not only let us find the calculation errors but also help us to revise the original thinking direction because we can verify the correctness of our theory from the consistency of hand count and Maple calculations. Therefore, Maple can bring us inspiration and guide us to find the problem-solving method, this is not an exaggeration.

Chii-Huei Yu

On Reformulation of a Berth Allocation Model

Over the last decade, Ports’ operations have been a focal point for global supply chain management and logistics network structures around the world. The berth allocation problem (BAP) is closely related to the operational performance of any port. BAP consists of optimally assigning ships to berthing areas along the quay in a port. A good allocation of ships to berths has a positive impact on terminal’s productivity and customer’s satisfaction. Therefore, finding valid formulations which captures the nature of the BAP and accounts for the interest of ports operation management is imperative for practitioners and researchers in this field. In this study, various arrival times of ships are embedded in a real time scheduling system to address the berth allocation planning problem in a dynamic environment. A new mix integer mathematical formulation (MBAP) that accounts for two objectives—total waiting time and total handling time is proposed. The MBAP model is further evaluated in terms of computational time, and has demonstrated to be competitive compared to another well-known BAP formulation in the literature.

Yun-Chia Liang, Angela Hsiang-Ling Chen, Horacio Yamil Lovo Gutierrezmil

Forecast of Development Trends in Cloud Computing Industry

This paper presents a study on the future development of Taiwan’s Cloud Computing industry. The forecast of development trends was made through interviews and focus group discussions of industry professionals. We construct an analysis framework for analyzing value chain and production value for the emerging Cloud Computing industry. Based on the analysis of recent Cloud Computing business models and the value activities of Cloud Computing vendors, the result provides a reference for IT business developers and innovative vendors interested in entering the emerging Cloud Computing market.

Wei-Hsiu Weng, Woo-Tsong Lin, Wei-Tai Weng

Self-Organizing Maps with Support Vector Regression for Sales Forecasting: A Case Study in Fresh Food Data

Many food stores face the same problem, “how many products should we make and how much ingredients should we order?” For most managers, they cannot predict a specific quantity of sales for upcoming week. If their prediction is not accurate, it will cause lots of products waste or the opposite, products shortage. Fresh food products have time limit. When consumers buy food, they would first consider if the foods are fresh or has been expired. As a result, customer demand forecasting is an important issue in food product market. With the recent development of artificial intelligence models, several methods have been employed in order to conduct forecasting model to be more effective than the conventional one. This research presents a two-stage forecasting model. The noise detecting and the removing will be considered first, and then all data will be clustered to increase the accuracy and practicability of the model.

Annisa Uswatun Khasanah, Wan-Hsien Lin, Ren-Jieh Kuo

State of Charge Estimation for Lithium-Ion Batteries Using a Temperature-Based Equivalent Circuit Model

This study investigates battery state-of-charge (SOC) estimation under different temperature conditions. A battery modeling approach is developed aiming to improve the accuracy of the SOC estimation when ambient temperature is taken into account. Firstly, a widely used equivalent circuit model with the one-order resistance-capacitor (RC) network is modified to capture battery dynamics at different temperatures. Secondly, since the open-circuit voltage verse SOC (OCV-SOC) incorporated into the battery model is also influenced by the temperature, OCV-SOC-Temperature (OCV-SOC-T) table is constructed to replace the original table based on our experimental data. The experiments with two dynamic load tests, dynamic stress test (DST) and federal urban driving schedule (FUDS) are run on the battery. The purpose of DST profile is to identify the battery model, while FUDS data is used to emulate the operation conditions and evaluate the performance of our proposed model by unscented Kalman filtering. Finally, the comparative results indicate that our temperature-based model provide more accurate SOC estimation with root mean square estimated errors than the original model without regard to temperature dependence.

Yinjiao Xing, Kwok-Leung Tsui

Linking Individual Investors’ Preferences to a Portfolio Optimization Model

When optimizing a portfolio, individual investors today already knew potential returns from the capital are often offset by the amount of risk willing to take; hence, to lower the risk associated with the investment, they’ll have to diversify through a pool of portfolio from different asset classes (such as stocks, bonds, mutual funds, and cash, etc.). Since most studies have disregarded preferences of individual investors and selections of different asset classes in model formulations, this study provides a systematic approach to set priorities among multi-criteria and trade-off among objectives for Taiwanese individual investors. For that, the Analytic Network Process (ANP) is suggested to determine an asset allocation scheme tailored to the specific requirements of individual investors. Such scheme is then applied to the Markowitz model of portfolio optimization. The Variable Neighborhood Search (VNS) algorithm is constructed to build an efficient frontier of multiple portfolios which offer investors more alternatives on asset selections.

Angela Hsiang-Ling Chen, Yun-Chia Liang, Chieh Chiang

Models and Partial Re-Optimization Heuristics for Dynamic Hub-and-Spoke Transferring Route Problems

The major advantages of hub-and-spoke network are the reduction of the number of routes and the effect of economies of scale, which can effectively save the shipping cost of the transportation industry. In the landside pick-up services of the international express industry, the application of such a model has achieved high efficient transit operations. The entire operational area is divided into numbers of partitions. Each partition sets up a station as the cargo collection place (meeting point). Vehicle routes meet here to consolidate goods that collected from customers into truckload shipment and transfer those to regional centers by larger trucks. In this study, the dynamic vehicle routing problem are extended to this type of hub-and-spoke network architecture, which make it different from the Vehicle Routing Problem (VRP), and is formulated as the Dynamic Hub-and-Spoke Problem with Transferring Route (DHSPTR). Test problems with dynamic pickup flows of export goods under H-S networks are designed to evaluate the proposed hybrid ACO solution methods. Partial re-optimization heuristics are realized by ACO for its ability to keep the solution status while new demands keep coming during the process and are inserted to existing routes dynamically.

Ming-Der May

Hazards and Risks Associated with Warehouse Workers: A Field Study

This study evaluated risk factors of manual material jobs performed in the field using questionnaire and NIOSH 1991 lifting guide. Discomfort assessment survey was used to investigate the risk of musculoskeletal injury in the warehousing operations. The questionnaire contains basic personal information, medical history, working hour and discomfort symptoms of the body such as pain, soreness, numbness at the end of the working day. Work analysis and ergonomic evaluation was also conducted to understand how workers engaged in their work. The results found the musculoskeletal risk factors for workers in warehouses were the overweight of objects lifted, awkward postures, static working postures, and long working duration. Awkward working postures such as lifting involved forward bending or twisting would increase the risk of lower back pain. Static working postures such as prolonged sitting or standing were also associated with the occurrence of low back pain and other discomfort.

Ren-Liu Jang, An-Che Chen

Green Supply Chain Management (GSCM) in an Industrial Estate: A Case Study of Karawang Industrial Estate, Indonesia

Increasing the pollution drive government and people consider about environment, therefore green issues become the hot topic lately, especially industrial sector. There are two reasons drive the industries to consider for applying green aspect in their supply chain, which are regulation, Financial and supply chain pressure. This paper intends to introduce the GSCM pressure, describe the GSCM practices, performance in Karawang city, Indonesia and compare the result with previous literature. Survey questionnaire is be conducted in which consist of 3 sections and using five-point scale. The questions are be mainly based on literature review and developed to the conceptual circumstance. The factorial analysis is be used to aggregate the factors, then multiple regression analysis is used to know the relation for each variable. The research provides that Karawang has not considered the GSCM pressure yet. Industries are considering carrying out GSCM practice like improving the quality of environment friendly goods. However, those practices are not enough to prevent their pressure. Nevertheless, those practices did not give huge affect to the performance, especially operation performance.

Katlea Fitriani

Limits The Insured Amount to Reduce Loss?: Use the Group Accident Insurance as an Example

Property-Liability insurance Industry pays much attention to the loss ratio of accident insurance. From 2005 to 2011, average loss ratio is 45.24 % in Property-Liability insurance industry and 34.31 % in Life insurance Industry. Most important to achieve the maximum benefit for reducing losses based on the minimum cost of underwriting for property-liability insurer’s underwriters. The purpose of this research is to examine limit insured amount can reduce the loss or not and whether business quality control by underwriting system. We complied data on group accident insurance from a Property-Liability Company in Taiwan from 2009 to 2010. There are 4,504 samples in group features. We use

$$ \chi^{2} $$

test, test analysis and ordered logistic regression verify the relevance of the insured amount and loss, business quality control effect and the factor impact the loss. The results of the analysis show that the there was a correlation between insured amount and loss, business quality control that effectively reduce medical loss, Variables of AD&D, MR/AD&D and DHI/AD&D have a significant influence for the loss. The result of the analysis not only help underwriter to adjust underwriting guidelines but also reduce loss amount. Moreover, our results have practical implications for the Property-Liability insurance industry in Taiwan.

Hsu-Hua Lee, Ming-Yuan Hsu, Chen-Ying Lee

Manipulation Errors in Blindfold Pointing Operation for Visual Acuity Screenings

We developed a self-testing device for screening visual acuity, in which patients used a joystick to enter the responses. Since patients kept fixation of the test chart throughout the test, the joystick was operated blindfold. Pointing errors as function of the orientation of the Landolt ring were computed by analyzing records of 457 patients. In 97 % of errors, patients misestimated the orientation of the Landolt ring by 45°, which is the orientation next to the one presented. Mismatches in counter clockwise direction were 3 times more frequent as in clockwise direction. Findings are compared to results recorded in 25 subjects who performed acuity tests by reporting verbally the orientation of presented Landolt rings. In the verbal reporting condition, error rates for orthogonal and diagonal orientations were similar. We suggest considering the limited accuracy of motor response as a major issue in the blindfolded operation of a joystick which is used in combination with a vision screener. Furthermore we suggest a statistical procedure accounting for manipulation errors in an acuity test. The combination of previous findings (Menozzi

2013

,

1995

) to findings reported here suggests that computerized screening devices enabling self-testing are a reliable and convenient method for large scale vision screenings.

Ying-Yin Huang, Marino Menozzi

3-Rainbow Domination Number in Graphs

The k-rainbow domination is a location problem in operations research. Give an undirected graph G as the natural model of location problem. We have a set of k colors and assign an arbitrary subset of these colors to each vertex of G. If a vertex which is assigned an empty set, then the union of color set of its neighbors must be k colors. This assignment is called the k-rainbow dominating function, abbreviate as kRDF, of G. The weight of kRDF is the sum of numbers of assigned colors over all vertices of G. The minimum weight of kRDF is defined as the k-rainbow domination number of G. In this paper, we present an exact algorithm and a heuristic algorithm to obtain the 3-rainbow domination number and the weight of 3RDF in graphs, respectively. Then, we test the practical performances of these algorithms, including their run times and solution qualities.

Kung-Jui Pai, Wei-Jai Chiu

A Semi-Fuzzy AHP Approach to Weigh the Customer Requirements in QFD for Customer-Oriented Product Design

In this paper, a new analytic hierarchy process (AHP) is proposed to determine the importance weights of customer requirements (CRs) in quality function deployment (QFD) for customer-oriented product design. The new approach combines conventional and fuzzy AHP. It takes into account one’s uncertainty in comparing different pairwise CRs to improve the imprecise rankings in conventional AHP. By employing semi-fuzzy matrices, it guarantees that the final pairwise comparison matrices based on fuzzy scales are positive reciprocal. The problem of imprecise pairwise comparisons in conventional AHP is ameliorated and more accurate results are provided. Finally, a case study of new sports earphones design is given as an example to illustrate this approach.

Jiangming Zhou, Nan Tu

An Optimization Approach to Integrated Aircraft and Passenger Recovery

In this paper, the allocation of aircrafts to each rescheduled flight with passengers concerns is considered. The problem consists of a recovered flight schedule within a recovery period, a pool of affected passengers with their initial itineraries, and a fleet of available aircrafts of various configurations. The objective is to route the suitable aircrafts to operate the suitable rescheduled flight legs, and at the same time, generating the corresponding itineraries for affected passengers. This paper proposes a new optimization formulation that integrates the recovery of aircrafts and passengers simultaneously to minimize the sum of passenger delay cost and airline operation cost. With the proposed algorithms, airlines will be able to assign suitable aircrafts to support flight recovery under disruptions within a short time-period, and at the same time reduce passenger delays.

F. T. S. Chan, S. H. Chung, J. C. L. Chow, C. S. Wong

Minimizing Setup Time from Mold-Lifting Crane in Mold Maintenance Schedule

The integration of production scheduling and maintenance planning has received much attention in the past decade. However, most of the studies only focused on the availability constraint of machines. Other critical resources such as injection molds are usually assumed to operate without breakdown. In fact, the frequency of mold breakdown is even higher than the machine breakdown. It is therefore necessary to consider the availability constraint of injection molds during scheduling. Extending the preliminary study of the production-maintenance scheduling model in (Wong, International J Prod Res 50:5683–5697, 2011), this study aims to solve a new mold maintenance scheduling problem with the consideration of the setup time of using a mold-lifting crane. A Joint Scheduling (JS) approach is proposed to minimize the weighted sum of the makespan and the setup time. The approach is implemented in genetic algorithm to solve five hypothetical problem sets. The results show that the JS approach outperforms the traditional approach.

C. S. Wong, F. T. S. Chan, S. H. Chung, B. Niu

Differential Evolution Algorithm for Generalized Multi-Depot Vehicle Routing Problem with Pickup and Delivery Requests

This paper presents a Differential Evolution (DE) algorithm for solving generalized multi-depot vehicle routing problem with pickup and delivery requests (GVRP-MDPDR). The GVRP-MDPDR does not require the restricted assumptions of CVRP, VRPSPD, etc. and it contains nearly all characteristics of real world vehicle routing problems. The solution is represented as a multidimensional vector where each dimension is filled with random number and a population of vectors is evolved via the mechanism of differential evolution. A decoding scheme (SD1) is applied to decode the vector into priority of requests and construct the routes of vehicles under the restricted constraints. Five groups of test problem instances, A, B, C, D, and E, with differences geographical data and number of requests are used to evaluate the performance of the algorithm. Each group of instance composes of three different location scenarios of requests: clustered (c), randomly distributed (r), and half-random-half-clustered (rc). The computational results demonstrated that DE algorithm is very competitive when compared to the results obtained by using Particle Swarm Optimization (PSO).

Siwaporn Kunnapapdeelert, Voratas Kachitvichyanukul

A Robust Policy for the Integrated Single-Vendor Single-Buyer Inventory System in a Supply Chain

To find the best production quantity for the vendor and the order quantity for the buyer, the integrated single-vendor single-buyer inventory model is proposed with the aim to minimize the total costs of the entire supply chain. In the Traditional supply chain, the most of integrated inventory is to develop a model that assumes that the input data is deterministic and equal to some nominal values. However, few researches have considered data uncertainty such as in demands, lead times, or even setup/ordering costs. Instead of solving for the optimal solution under the assumption of deterministic demands, here we provide a prescriptive methodology for constructing uncertainty sets within a robust optimization framework for integrated inventory problems with uncertain data. We accomplish this by taking as primitive the decision maker’s attitude toward risk. A numerical study and sensitive analysis are conducted to examine the integrated inventory model.

Jia-Shian Hu, Pei-Fang Tsai, Ming-Feng Yang

Cost-Based Design of a Heat Sink Using SVR, Taguchi Quality Loss, and ACO

This study proposed a cost-based procedure for resolving multi-response parameter design problems using support vector regression (SVR), Taguchi quality loss and ant colony optimization (ACO). A case study aiming to optimize the design of a heat sink applied in a high-power MR16 LED lamp was used to demonstrate the proposed procedure. The experimental results indicated that the proposed procedure can provide highly robust settings of design parameters which can maximize the thermal performance, as well as can minimize the actual material cost of a heat sink. Furthermore, decision makers no longer need to determine the relative weight of each response subjectively. Therefore, the proposed approach in this study can be considered as feasible and effective, and can be popularized to be a useful tool for resolving general multi-response parameter design problems in the real world.

Chih-Ming Hsu

Particle Swarm Optimization Based Nurses’ Shift Scheduling

The nurse scheduling is a multifaceted problem with the extensive number of constraints requires. In the past, many researchers tried to find the high-quality nursing schedule by analyzing their different aspects and targets, including the lowest cost and the highest efficiency. However, the study lacks of the consideration for nurses’ happiness. The nurses with bad mood will feel distracted in their working time, and even quit their jobs in the end. This thesis not only contains the scheduling constraints by the Administrative Regulations and the Hospital Regulations to construct the mathematical models, but also includes the consideration of nurses’ happiness. The main algorithm of this research is the Particle Swarm Optimization (PSO). We used PSO to look for the most suitable schedule for nursing staffs to maximize their working happiness.

Shiou-Ching Gao, Chun-Wei Lin

Applying KANO Model to Exploit Service Quality for the Real Estate Brokering Industry

This research applies Kano model to exploit service quality for the REB industry in Taiwan. The study, firstly, collected data about the importance degree of each REB quality requirements through a questionnaire survey. Meanwhile, the Kano questions and evaluation criteria were designed in the functional and dysfunctional questions of the questionnaire to collect data for further classifications of the two-dimensional quality model of REB industry. Then, a factor analysis was used to group the quality requirements into quality dimensions. Finally, a satisfaction-dissatisfaction matrix analysis was performed to confirm what quality attribute that each quality dimension of REB belongs to in the Kano’s two dimensional model. Results show that quality dimensions of security and dependability are confirmed as the “must-be” attributes of Kano model. Reliability is the “one-dimensional” attribute. Profession and information belong to the “attractive” attributes. Whereas, tangibility, communication, and empathy are identified as the “indifference” attributes of Kano model. Managerial suggestions are also provided.

Pao-Tiao Chuang, Yi-Ping Chen

Automated Plastic Cap Defect Inspection Using Machine Vision

Plastic caps are the most commonly seen bottle caps used in beverage and food containers. They are widely used to seal freshness of beverage or liquids in bottles. Threads are usually grooved inside the caps for easy twist-off caps and sealing rings prevent the liquids from bacterial infection. Companies print logos or pictures on the top surface of plastic cap, such that the quality of printing also indirectly affects the customers purchase. Inspection of plastic caps, including the surface printing, thread, and sealing ring, is a great issue during the caps production currently. The objective of this study is to use machine vision to inspect the defect of the sealing area and the printing surface of a plastic cap. An automated inspection system, which includes two CCD camera, lighting source, sensors, and a cap transporter, is constructed, and a digital image processing software is designed to learn good caps and screen out the defective ones. The experimental results show that the proposed inspection system can self-learn the features of a good surface printing, and effectively detect the defective caps under very few parameters setting, while the major defects in the sealing ring and thread area such as malformation, contamination, overfill, incomplete, scratches, can be successfully identified under the rate of 1,200 piece per minute.

Fang-Chin Tien, Jhih-Syuan Dai, Shih-Ting Wang, Fang-Cheng Tien

Coordination of Long-Term, Short-Term Supply Contract and Capacity Investment Strategy

This research studies contract design and capacity investment problem in a two-echelon supply chain consisting of a supplier and a downstream retailer who has in-house capacity. After building in-house capacity, the retailer would use his own capacity first. Under such situation, the risk of the variance of capacity utilization would be transferred to suppliers. The objective of this research is to protect the suppliers’ profit by exploring the coordination of supply contract (combining long-term and short-term contract) and capacity investment strategies. At the beginning of each period, the demand uncertainty would be realized, and then the supplier would offer both long-term and short-term contracts. In long-term contract, the retailer makes a reservation for the next two successive periods; in short-term contract, the retailer orders products to fulfill the reserved deficiency. Additionally, both parties would make capacity investment decision in every period. The supplier has higher market power, making the capacity investment decision first and deciding the contracts. To solve the problem, we build a mathematical model, using game theory to decide the short-term decisions and exercising the dynamic programming to obtain the optimal policy in long-term.

Chiao Fu, Cheng-Hung Wu

An Analysis of Energy Prices and Economic Indicators Under the Uncertainties: Evidence from South East Asian Markets

It is well known that the worldwide financial crisis has caused various international issues. For instance, it is pointed out that the Euro-crisis has spread the financial instability to the other markets e.g. equity, oil, gold, etc. In addition, the energy and the commodity market are known as major factors which influence the decision making of investors in currency market or stock market in both long and short term. Thus it is an important thing for the decision making for investors to find out the relationships among various markets. There are two scenarios in this paper. In the first one, we analyze the future forecasts by applying Vector Error Collection Model (VECM) to economic indicators which have influential power all over the world, and then, we get the relationship among these markets via Granger Causality test. On the other hand, it is also important to predict which factors would be market driven in the future. Then in the second one, since South East Asian market is known as the potential markets for driving the market in the future, we add the variables which belong to South East Asian markets to the variables in the first scenario. This outcome will give some opportunity to get the interest to the investors.

Shunsuke Sato, Deddy P. Koesrindartoto, Shunsuke Mori

Effects of Cooling and Sex on the Relationship Between Estimation and Actual Grip Strength

Handgrip strength is essential in manual operations and activities of daily life, but the influence of cold on estimation of handgrip strength is not well documented. Since direct measurement of force is often somewhat difficult, estimations are frequently applied, and these estimations are sometimes used as a criterion for employee selection and screening. Therefore, the aim of the present study is to investigate the relationship between estimated and actual handgrip strength at various target force levels (TFLs, in percentage of MVC) for both sexes under hand was cooled or not. A cold pressor test in a 14 °C-water bath was used to lower the hand skin temperature, and this served as the cooled condition. The uncooled condition, without cold immersion, was the control condition. Ten males and 10 females were recruited. The results indicated that cooling the hand could result in lighter estimation, which could increase the risk of musculoskeletal disorders. Furthermore, females tended to be less reliable than males in the estimation, and greater absolute deviations occurred in the middle range of TFLs for both sexes.

Chih-Chan Cheng, Yuh-Chuan Shih, Chia-Fen Chi

Data Clustering on Taiwan Crop Sales Under Hadoop Platform

Hadoop is one of the most promising cloud computing platforms to execute a Big Data analytics task which is a process of discovering hidden patterns, unknown correlations, and other valuable information from an extremely large distributed dataset. In this paper, a data clustering was implemented under Hadoop platform to study a large crop sales dataset collected distributedly in Taiwan. Hadoop infrastructure was built to give access of the distributed data centers. An online clustering algorithm utilizing Mahout, a scalable machine learning library, was performed to analyze crop price and yield data from the distributed datasets. This clustering analysis is usually exhausting and time consuming if a single machine is in charge of the whole process. Therefore, in this research, the clustering jobs will be handled under an experimental distributed Hadoop environment. The result can be used to help decision making of crop planning by forecasting or detecting demand changes in the market as early as possible.

Chao-Lung Yang, Mohammad Riza Nurtam

Control with Hand Gestures in Home Environment: A Review

With many advances made in the area of automatic gesture recognition, gestural control has gradually gained its acceptance and popularity. However, the research to date has tended to focus on recognition technologies rather than human behaviors. With an emphasis on users, this paper reviews recent research literature on hand gestural control in home environment. The aim is to summarize and analyze current development processes of gesture vocabularies for commanding home appliances. A semiotic dual triadic model is proposed for the review of the control commands for the appliances, the types of hand gestures, the derivation processes of designer-defined and user-defined gestures. A typical derivation process for a user-defined gesture set was first collecting raw data by inquiring potential users to perform the most suitable gestures that they thought for triggering the given commands or functions, and then applying algorithms for the selection of final gesture vocabularies. A brief comparison among the research results of user-defined freehand gestures for TV control commands was provided as an example to show a need of research in this area. Further research direction includes the exploration of broader user population and the refinement of current gesture selection algorithms.

Sheau-Farn Max Liang

An Integrated Method for Customer-Oriented Product Design

This paper introduces a customer-oriented design method in new product development (NPD). This method comprises of persona creation, analytic hierarchy process (AHP), quality function deployment (QFD) and usability engineering. Persona creation based on fuzzy cluster analysis is first employed to identify the typical behaviors and motivations of a broader range of customers. The customer requirements (CRs) are extracted from the persona profiles and then prioritized with a semi-fuzzy AHP approach. Using the QFD method, the prioritized CRs are translated into measurable design requirements (DRs) to set the design targets. After product prototyping, scenario-based usability testing techniques are employed to access and make recommendations to improve usability in product redesign. The above process may be repeated with several iterations until a product that more closely matches the customer needs with high usability can be designed. A new sports earphones design is given as an example to illustrate the implementation of this method.

Jiangming Zhou, Nan Tu, Bin Lu, Yanchao Li, Yixiao Yuan

Discrete Particle Swarm Optimization with Path-Relinking for Solving the Open Vehicle Routing Problem with Time Windows

This paper presents a discrete version of the particle swarm optimization with additional path-relinking procedure for solving the open vehicle routing problem with time windows (OVRPTW). In OVRPTW, a vehicle does not return to the depot after servicing the last costumer on its route. Each customer’s service is required to start within a fixed time window. To deal with the time window constraints, this paper proposed a route refinement procedure. The result of computational study shows that the proposed algorithm effectively solves the OVRPTW.

A. A. N. Perwira Redi, Meilinda F. N. Maghfiroh, Vincent F. Yu

Application of Economic Order Quantity on Production Scheduling and Control System for a Small Company

Struggling to live in the 21 century, lots of small companies of which the production scheduling and control system (PSCS) are based on a rule of thumb. Without the precise mathematic model, the rule of thumb method may lead to inventory shortages and excess inventory. For reaching better controls of PSCS, this study intends to simulate a material requirement planning (MRP) production system with adopting an economic lot-sizing (EOQ) model to diminish varieties of costs for small sized companies under job-shop environments. The proposed EOQ adopting MRP approach is supposed to have better economics of PSCS than rule-of-thumb methods. A case analysis of a small company X in Thailand is conducted for verifying this proposition. Company X regularly relied on rules-of-thumb to handle PSCS. In this study, two kinds of materials and three types of products are traced top-down from production planning (PP), master production schedule (MPS), to MRP along a period of two months since July 2012. This study undertakes a series of data collection in the field. The analyzed results indicate that the presented model really reach more economics than rule-of-thumb methods for company X.

Kuo En Fu, Pitchanan Apichotwasurat

CUSUM Residual Charts for Monitoring Enterovirus Infections

We consider the syndromic surveillance problem for enterovirus (EV) like cases. The data used in this study are the daily counts of EV-like cases sampled from the National Health Insurance Research Database in Taiwan. To apply the CUSUM procedure for syndromic surveillance, a regression model with time-series error-term is used. Our results show that the CUSUM chart is helpful to detect abnormal increases of the visit frequency.

Huifen Chen, Yu Chen

A Study on the Operation Model of the R&D Center for the Man-Made Fiber Processing Industry Headquarter

The global strategy layout for the activities of R&D is naturally the important decision making for the survival and competition of business entities in Taiwan. Based on these background and motives, this research aims to investigate and construct the reference models for the operation of R&D center within the business headquarters and we also focus our effort onto the textile sub-industry—Man-made fiber processing industry. This research is adopted with IDEF0 for processing analysis and model construction methodology. During the construction, the processes associated with the R&D center within business headquarters is constructed via literature survey and practical expert interview. By means of the factor analysis, we can extract the key items of ICOM (Input, Control, Output, Mechanism) from the activities related to the R&D processes. This research result will be meant to depict the overall profile for the operation of R&D centers from the textile industries. Hopefully, we can offer the reference basis for the planning phase of business headquarter R&D center so that the planning can thoroughly meet the demand of business strategy execution and management characteristics.

Ming-Kuen Chen, Shiue-Lung Yang, Tsu-Yi Hung

Planning Logistics by Algorithm with VRPTWBD for Rice Distribution: A Case BULOG Agency in the Nganjuk District Indonesia

This paper addresses a vehicle routing problem with time windows encountered in BULOG (Government National Agency) specialized for distribution of rice with subsidy by government in Nganjuk East Java. It concern the delivery of rice with subsidy from central BULOG to home family that have been chosen by government as poor family in Nganjuk, delivery from central to warehouse, and from warehouse to government district also from district to village (the poor family target living). The problem can be considered as a special vehicle routing problem with time windows, with bender’s decomposition as solver to minimize the total cost of distribution with still consider about time delivery and total of vehicle used. Each village is visited by more than one vehicle at one time delivery. Two mixed-integer programming models are proposed. We then proposed a Genetics Algorithm (GA) and exact method of VRPTWBD, and these approaches are tested with compare the result from four experiments with real data from BULOG, such as: Exact VRPTW, exact VRPTW-BD, Naïve GA, and Genetics Algorithm-BD.

Kung-Jeng Wang, Farikhah Farkhani, I. Nyoman Pujawan

A Systematic and Innovative Approach to Universal Design Based on TRIZ Theories

Continual expansion of the population and its diversity has increased the demand for products that take into account the elements of universal design. Universal design has been widely studied; however, a lack of all-encompassing systematic design processes makes it difficult for designers and engineers to transform universal design intent into product realization. This paper proposes a systematic approach to UD based on TRIZ theories. We begin with a UD assessment to identify design problems, followed by a PDMT analysis to determine possible directions through which to resolve the problems. The directions were mapped directly to Effects for appropriate resolutions. For complex problems, it is suggested that Functional Attribute Analysis be employed to analyze the problems, before searching for resolutions from the effects. A case study was conducted to demonstrate the effectiveness and efficiency of the proposed approach in the design and development of products with greater usability, accessibility, and creativity.

Chun-Ming Yang, Ching-Han Kao, Thu-Hua Liu, Hsin-Chun Pei, Yan-Lin Lee

Wireless LAN Access Point Location Planning

With the fast-growing demand for mobile services, where to place the access points (APs) for providing uniformly and appropriately distributed signals in a wireless local area network (WLAN) becomes an important issue in the wireless network planning. Basically, AP placement will affect the coverage and strength of signals in a WLAN. The number and locations of APs in a WLAN are often decided on the basis of the trial-and-error method. Based on this method, the network planner first selects suitable locations to place APs through observation, and then keeps changing the locations to improve the signal strength based on the received signal. Such process is complicated, laborious and time-consuming. To overcome this problem, we investigate the back-propagation neural network (BPNN) algorithm to improve over the traditional trial-and-error method. Without increasing the number of APs, our approach only needs to adjust AP locations to overcome weak signal problems and thus increase the signal coverage for the Internet connection anywhere within the area. In our experiment, we established a WLAN on a

C

campus. Our experiments also indicate that placing APs according to the BPNN provided better signal coverage and met the students’ demands for connecting to the Internet from anywhere in the classroom.

Sung-Lien Kang, Gary Yu-Hsin Chen, Jamie Rogers

The Parametric Design of Adhesive Dispensing Process with Multiple Quality Characteristics

In recent years, electronic industry trend moves toward miniaturizing its electronic components. Nevertheless, the functionality of these electronic components has grown stronger in order to keep up with the world’s technology advances and demand. The electronics manufacturing companies are always searching for new and better ways to make their products more efficiently, while protecting the environment in accordance to the restriction of hazardous substance (RoHS) directive, which was announced by the European Union. However, the implementation of such directive generated some setbacks in the electronics assembly process with surface-mount technology. This paper focuses on the quality performance of the component’s glue adhesion strength, considering multiple quality characteristics such as the vertical and horizontal thrusts at low and high temperatures. The Taguchi method assisted in designing and implementing the experiments. Process factors considered include the dispensing position, thermoset temperature and reflow conveyor speed. The multi-criteria analysis methods, the order preference by similarity to the ideal solution (TOPSIS) together with the principal component analysis (PCA), are employed to analyze the experimental data acquired. The optimal process parameters are thus determined. Lastly, a confirmation test is conducted to verify the results of the optimal process scenario.

Carlo Palacios, Osman Gradiz, Chien-Yi Huang

The Shortage Study for the EOQ Model with Imperfect Items

The traditional economic order quantity (EOQ) model assumes that all the ordered items are “perfect” enough to be consumed by the customers, but some of these items could be impaired or damaged in the process of production or transportation. For such items, we might call them “imperfect items” and they need to be considered in the EOQ model. In this paper, we focus the study on the shortage problem for the EOQ model with imperfect items since the shortages are inevitably caused by the imperfect items. Consider that the imperfect probability

p

is a random variable with probability density function

f

(

p

)

and the good quantity

Y

comes from the Hypergeometric distribution. Consequently, the sufficient condition to ensure the occurrence of non-shortages is obtained and a mathematical discussion is provided to construct an optimal inventory model for dealing with the possibilities of the shortage problem.

Chiang-Sheng Lee, Shiaau-Er Huarng, Hsine-Jen Tsai, Bau-Ding Lee

Power, Relationship Commitment and Supplier Integration in Taiwan

This research extends power-relationship commitment theory to investigate the impact of power and relationship commitment on supplier integration from manufacturers’ perception toward their major suppliers in supply chain context in Taiwan. The power sources include expert power, referent power, legitimate power, reward power and coercive power, which can be categorized as non-mediated power and mediated power. Two types of the relationship commitment are studied, including normative relationship commitment and instrumental relationship commitment. The integration between manufacturers and suppliers (supplier integration) is measured by information integration and strategic integration. Based on a survey using data on 193 manufacturers in Taiwan, results indicate that coercive power has a positive influence on instrumental relationship commitment; however, reward power has no significant impact on any type of relationship commitment. Expert and referent power have positive impact on normative relationship commitment, while legitimate power has no significant influence on relationship commitment. Both normative and instrumental relationship commitment have positive impact on supplier integration and the former has a stronger influence than the latter. The findings can help companies enhance their supply chain integration by developing appropriate relationships with their suppliers.

Jen-Ying Shih, Sheng-Jie Lu

A Search Mechanism for Geographic Information Processing System

Geographic data is becoming a critical part of mobile applications. Public and private sectors agencies create and make geographic data available to the public. Applications can make request to download maps to help the user navigate her/his surroundings or geographic data may be downloaded for use in the applications. The complexity and richness of geographic data create specific problems in heterogeneous data integration. To deal with this type of data integration, a spatial mediator embedded in a large distributed mobile environment (GeoGrid) has been proposed in earlier work. The present work looks at a search mechanism used in the spatial mediator that utilizes an algorithm to support the search of the data sources in response to application’s request for maps. The algorithm dynamically evaluates uncovered region of the bounding box of the request in an attempt to search for a minimal set of data sources.

Hsine-Jen Tsai, Chiang-Sheng Lee, Les Miller

Maximum Acceptable Weight Limit on Carrying a Food Tray

This study was to simulate two ways to carry a food tray, waist-level carry and shoulder-high carry, to determine their maximum acceptable weight of load (MAWL) and to suggest a proper weight for banquet servers or workers in restaurants. Twenty college students were participated in this study. The MAWL on shoulder-high carry was 3.32 ± 0.47 kg for male and 2.78 ± 0.35 kg for female, respectively. The MAWL on waist-level carry were 2.57 ± 0.26 kg for male and 2.21 ± 0.35 kg for female. There were significantly differences between gender and carry methods. On average, the MAWL on waist-level carry was 22 % less than that on shoulder-high carry. The MAWL of female on waist-level carry was 14 % less than that for male while the MAWL of female on shoulder-high carry was 16 % less than that for male. The results suggested banquet servers or workers in restaurants should consider the proper way to deliver the food when it gets heavy.

Ren-Liu Jang

Fatigue Life and Reliability Analysis of Electronic Packages Under Thermal Cycling and Moisture Conditions

Many previous researches on electronic packages focused on assessment of package lives under a single state of stress such as vibration, thermal cycling, drop impact, temperature and humidity. The present study considers both effects of thermal cycling and moisture on the fatigue life of electronic packages. The influence of moisture on thermal fatigue life of a package is investigated in particular. A Monte Carlo simulation algorithm is employed to make the result of finite element simulation close to reality. Samples of variables consisting of different package sizes and material parameters from their populations are generated and incorporated into the finite element analysis. The result of a numerical example indicates the thermal-fatigue failure mechanism of the electronic packages is not affected very much by the moisture. However, the mean time to failure of the package does decrease from 1,540 cycles to 1,200 cycles when moisture is taken into consideration.

Yao Hsu, Wen-Fang Wu, Chih-Min Hsu

Clustering-Locating-Routing Algorithm for Vehicle Routing Problem: An Application in Medical Equipment Maintenance

This research is aimed to solve a vehicle routing problem for medical equipment maintenance of 316 health promoting hospitals in Ubon Ratchathani which conducted by maintenance department of Ubon Ratchathani Provincial Health Office by using clustering-locating-routing technique (CLR). We compared two different methods for clustering. The first method applied the sweep algorithm (SW-CLR) for clustering the health promoting hospital to 4 clusters and each cluster includes 79 hospitals. The second method used district boundary (DB-CLR) for clustering the hospital to 25 clusters. After that, load distance technique was used to determine a location of maintenance center in each cluster. Finally, saving algorithm was applied to solve the vehicle routing problem in each cluster. Both SW-CLR and DB-CLR can reduce transportation cost effectively compared with traditional route. The SW-CLR reduced overall annually maintenance cost 52.57 % and DB-CLR reduced cost 37.18 %.

Kanokwan Supakdee, Natthapong Nanthasamroeng, Rapeepan Pitakaso

Whole-Body Vibration Exposure in Urban Motorcycle Riders

Twenty-two male and twenty-three female motorcycle riders performed ninety test runs on six 20-km paved urban routes. Root mean square of acceleration, 8-hour estimated vibration dose value (

VDV

(8)

), and 8-hour estimated daily static compression dose (

S

ed

) were determined in accordance with ISO 2631-1 (1997) and ISO 2631-5 (2004) standards. The analytical results indicated that over 90 % of the motorcycle riders revealed

VDV

(8)

exceeding the upper boundary of health guidance caution zone (17 m/s

1.75

) recommended by ISO 2631-1 or

S

ed

exceeding the value associated with a high probability of adverse health effects (0.8 MPa) according to ISO 2631-5. Over 50 % of the motorcycle riders exceeded exposure limits for

VDV

and

S

e

within 3 h. Significantly greater exposure levels were observed in male participants than in female participants for

VDV

(8)

(

p

< 0.05) and

S

ed

(

p

< 0.005). The health impacts of WBV exposure in motorcycle riders should be carefully addressed with reference to ISO standards.

Hsieh-Ching Chen, Yi-Tsong Pan

Analysis of Sales Strategy with Lead-Time Sensitive Demand

Nowadays, more and more customers order products through non-conventional direct sales channel. Instead of purchasing from retail stores, customers place orders directly with the manufacturer and wait for a period of lead-time for the ordered items to be delivered. With limited production capacity, it is possible that the manufacturer is unable to deliver all the orders in regular delivery time if too many orders are placed in a period of time. The delivery lead-time may become longer than expected and that can have an impact on future demand. This study assumes customer demand is sensitive to the length of lead-time. That is, demand decreases as the actual delivery lead-time in the previous period becomes longer. Mathematical models are constructed for the considered multiple-period problem. Numerical experiments and sensitivity analysis are conducted to examine how lead-time sensitive demand affects system behaviors. It is observed that the system behaviors heavily depend on the size of initial demand. It is also found that when initial demand is greater than the fixed capacity, the cumulated profit of the manufacturer may increase in the beginning. However, it will decline in the long run.

Chi-Yang Tsai, Wei-Fan Chu, Cheng-Yu Tu

Order and Pricing Decisions with Return and Buyback Policies

This paper considers application of return and buyback policies in a supply chain system. The system contains a manufacturer and a retailer. The manufacturer produces and sells a single product to the retailer and promise to buy back all the remaining units from the retailer at the end of the selling season. The retailer orders from the manufacturer before the season and applies a return policy to its customers with full refund. Customer demand is assumed to be sensitive to the retail price. Before the beginning of the selling season, the manufacturer offers the wholesale price and the buyback to the retailer. The retailer then determines the order quantity and the retailer price. Two types of control are investigated. Under decentralized sequentially decision making, both the manufacturer and the retailer make their decisions to maximize their own profit. Under centralized control, all the decisions are jointly made to maximize the profit of the whole system. Mathematical models under the two types of control are constructed and optimal order and pricing decisions are derived. The optimal decisions and the resulting profits are compared. We show that centralized control always generates higher overall profit.

Chi-Yang Tsai, Pei-Yu Pai, Qiao-Kai Huang

Investigation of Safety Compliance and Safety Participation as Well as Cultural Influences: Using Selenginsk Pulp and Cardboard Mill in Russia as an Example

The aim of this study was to assess the effectiveness of the job demands–resources (JD–R) model in explaining the relationship of job demands and resources with safety outcomes (i.e., workplace injuries and near-misses). We collected self-reported data from 203 pulp and paper production workers from Pulp and Cardboard Mill which is located in Russia during the period 2000–2010. The results of a structural equation analysis indicated that job demands (psychological and physical demands) and job resources (decision latitude, supervisor support and coworker support) could affect safety performance and safety compliance, and thus influence the occurrence of injuries and near-misses and whether the cultural influences play a significant role in both safety compliance and safety participation.

Ekaterina Nomokonova, Shu-Chiang Lin, Guanhuah Chen

Identifying Process Status Changes via Integration of Independent Component Analysis and Support Vector Machine

Observations from the in-control process consist of in-control signals and random noise. This paper assumes that the in-control signals switch to different signal types when the process status changes. In these cases, process data monitoring can be formulated as a pattern recognition task. Time series data pattern recognition is critical for statistical process control. Most studies have used raw time series data or extracted features from process measurement data as input vectors for time series data pattern recognition. This study improves identification by focusing on the essential patterns that drive a process. However, these essential patterns are not usually measurable or are corrupted by measurement noise if they are measurable. This paper proposes a novel approach using independent component analysis (ICA) and support vector machine (SVM) for time series data pattern recognition. The proposed method applies ICA to the measurement data to generate independent components (ICs). The ICs include important information contained in the original observations. The ICs then serve as the input vectors for the SVM model to identify the time-series data pattern. Extensive simulation studies indicate that the proposed identifiers perform better than using raw data as inputs.

Chuen-Sheng Cheng, Kuo-Ko Huang

A Naïve Bayes Based Machine Learning Approach and Application Tools Comparison Based on Telephone Conversations

This paper investigates the application of hybrid Bayesian based semi-automated task analysis machine learning tool, Text Miner. The tool is still in its developing stage. Telephone’s dialog conversation between call center agent and customer was used as training and testing dataset to feed in parsing based Text Miner. Preliminary results extracted from Text Miner based on the naïve Bayes approach was further compared to one open sourced machine learning program, tokenizing based Rapid Miner. Fifteen prediction words combinations were compared and the study finds that both tools are capable of processing large dataset with Text Miner performs better than Rapid Miner in predicting the relationship between prediction words and main subtask categories.

Shu-Chiang Lin, Murman Dwi Prasetio, Satria Fadil Persada, Reny Nadlifatin

Evaluating the Development of the Renewable Energy Industry

While the world is increasingly concerned with the utilization of fossil energy and carbon emission, renewable energies have been promoted by many governments as alternatives worldwide. Wind power is currently the most mature renewable energy technology. Although Taiwan is located in a region of abundant wind power, this energy industry still faces big challenges in effectively growing the market. This study employs a variation of the hidden Markov model (HMM) to analyze the development of wind power industry in Taiwan, because the renewable energy development is determined by multiple time-series-related factors. The methodology may assist industry in making correct investment decision and provide recommendations to the government for setting suitable green energy policy.

Hung-Yu Huang, Chung-Shou Liao, Amy J. C. Trappey

On-Line Quality Inspection System for Automotive Component Manufacturing Process

The automotive industry in a nation not only forms an economic base, but also plays an important role for safety and convenience in the society. In average, a vehicle is composed of more than thousands components, and the quality of each component is definitely critical. Automotive component manufacturers, as suppliers to automotive manufacturers, are forced to emphasize the quality inspection for their products. Hence, this research proposes an online quality inspection system for vehicle component manufacturing industries. The system is composed of three subsystems, which are real-time machine condition monitoring, supply chain management, and production information management. The transparency of the production process can further be analysed to infer the quality of product on production line. The proposed system is introduced to a Taiwanese vehicle component manufacturing industry for validating its capability to reduce the effort spent on inspection work, the rate of waste, and to improve overall equipment efficiency (OEE).

Chun-Tai Yen, Hung-An Kao, Shih-Ming Wang, Wen-Bin Wang

Using Six Sigma to Improve Design Quality: A Case of Mechanical Development of the Notebook PC in Wistron

Wistron has transformed from private brand to OEM/ODM after reorganizing in 2003, witnessing phenomena that profits of personal computer and its peripherals decline day by day, and domestic manufacturers had gradually moved to China mainland because unit cost is not competitive, continued to survive with the help of low processing cost and then expanded the production base. Therefore, companies of this case considered to fully carry out Six Sigma program to improve the plan in order to solve their troubles in 2005. The company of the case in 2007/Q2 grew quickly in NB business, but its defective products caused a huge loss to the company. Consequently, a project team was established to consider carrying out preventive measures and design improvement during product R&D. As a whole, the individual case will discuss subjects as follows: (1) The core processes of Six Sigma and the opportunity of using tools shall be understood in order to get the maximum benefit and enhance the capability of solving problems. (2) Performance comparisons before and after Six Sigma design are imported. (3) The process mode and standard design norms of new product R&D are constructed through research of actual cases.

Kun-Shan Lee, Kung-Jeng Wang

Estimating Product Development Project Duration for the Concurrent Execution of Multiple Activities

Many companies adopt concurrent engineering for their product development projects to reduce time to market. It is often the case that the multiple activities are overlapped in a concurrent engineering environment, while most of the product development research covers only the two-activity problems. The concept of degree of evolution has been proposed in literature to represent how close the unfinalized design of the downstream activity is to its final one, which is actually a measure of the real progress, reflecting the rework requirement due to overlapping. When more than three activities are concurrently executed, it is midstream activity whose degree of evolution is important, since it affects the rework duration for downstream and consequently the overall project duration. It is difficult to estimate the degree of evolution for midstream since involves has two uncertainties, one derived from incomplete information from upstream while the other from changing design information of itself. This paper models the degree of evolution for midstream activity taking into account the two uncertainties. On top of the model, this paper develops a methodology to calculate the project duration, which depends on the project managers’ decision on information transfer frequency and overlapping ratio, when three activities are concurrently executed. This paper is expected to help firms forecast the effect of management decision about concurrent engineering dealing with overlapping among multiple activities.

Gyesik Oh, Yoo S. Hong

Modeling of Community-Based Mangrove Cultivation Policy in Sidoarjo Mudflow Area by Implementing Green Economy Concept

One of the environmental damages in Indonesia is Sidoarjo mudflow disaster causing impact significantly in various sectors. These problems of course could lead to instability for the local social dynamics and the environment as well as the global economy. Cultivating mangrove vegetation is one of the answers to overcome these problems, especially to neutralize the hazardous waste contained in the mud and definitely to rebuild the green zone in the observed area. It is necessary to conduct a research on mangrove cultivation policy in Sidoarjo mudflow area in order to support green economy concept giving benefits to the economy, environment and society. Considering several numbers of variable which have complex and causal relationships in mangrove cultivation policy in line with green economy concept, and also the developing pattern of line with the changing time make the problem to be solved appropriately with system dynamics approach which is able to analyze and assess the mangrove cultivation policy in accordance with the principles of green economy concept. Therefore, by modeling the policy of mangrove cultivation based on the concept of green economy is expected to be able to reduce carbon emissions and to create a new ecosystem that could be used by communities to give added value and selling for Sidoarjo mudflow area.

Diesta Iva Maftuhah, Budisantoso Wirjodirdjo, Erwin Widodo

Three Approaches to Find Optimal Production Run Time of an Imperfect Production System

This paper considers an Economic Production Quantity (EPQ) model where a product is to be manufactured in batches on an imperfect production system over infinite planning horizon. During a production run of the product, the production system is dictated by two unreliable key production subsystems (KPS) that may shift from an in-control to an out-of-control state due to three independent sources of shocks. A mathematical model describing this situation has been developed by Lin and Gong (

2011

) in order to determine production run time that minimizes the expected total cost per unit time including setup, inventory carrying, and defective costs. Since the optimal solution with exact closed form of the model cannot be obtained easily, this paper considered three approaches of finding a near-optimal solution. The first approach is using Maclaurin series to approximate any exponential function in the objective function and then ignoring cubic terms found in the equation. The second approach is similar with first approach but considering all terms found. The third approach is using Golden Section search directly on the objective function. These three approaches are then compared in term computational efficiency and solution quality of through some numerical experiments.

Jin Ai, Ririn Diar Astanti, Agustinus Gatot Bintoro, Thomas Indarto Wibowo

Rice Fulfillment Analysis in System Dynamics Framework (Study Case: East Java, Indonesia)

Food fulfillment is one of the things that affect the stability of a country. The rapid population growth but not matched by the ability of food production will be a threat in the future, there is no balance between supply and demand. In 2011, there was rice shortage in East Java, which also resulted in the rice shortage at the national level, this phenomenon is caused anomaly weather, pests, land mutation, weak network Supply Chain Management, distribution, transportation, etc. that cause dependence on rice imports higher. This research purposes are to identify the holistic process of rice fulfillment in the context of supply chain system and analyzing possible risk raised as an important variables and provide a projection capabilities in the future by using a simulation scenario. The complexity of interaction between variables and the behavior of the system considered the selection of System Dynamics methods to solve problems. The advantages using System Dynamics as tools analysis is combine qualitative and quantitative method, also model can provide reliable forecast and generate scenarios to test alternative assumptions and decisions. Finally, the research contribution is formulated policy improvements in rice fulfillment, also provide more robust sensitivities and scenarios, so this research predict the impact of major changes in strategy accurately in uncertainty condition.

Nieko Haryo Pradhito, Shuo-Yan Chou, Anindhita Dewabharata, Budisantoso Wirdjodirdjo

Activity Modeling Using Semantic-Based Reasoning to Provide Meaningful Context in Human Activity Recognizing

As rapid increasing of World-Wide Web technology, ontology and pervasive/ubiquitous concept become one of the most interesting parts recently. According to ubiquitous issue, activity modeling which has capability to provide proper context information of the user becomes important part of context awareness. In order to develop required services in intelligence environment; to get deep knowledge provision framework; and precise activities relationship; context of knowledge should be determined based on socio-environment situation. Based on that background, this paper is aimed to develop activity model through activity recognition by implementing semantic based reasoning to recognize human activity.

AnisRahmawati Amnal, Anindhita Dewabharata, Shou-Yan Chou, Mahendrawathi Erawan

An Integrated Systems Approach to Long-Term Energy Security Planning

While heavy attempts have been made to evaluate energy systems, few can gain wide acceptance or be applied to various jurisdictions considering their lack of comprehensiveness and inability to handle uncertainties. This paper first proposes a MCDM approach using Fuzzy Analytic Hierarchy Process (FAHP) to assess security status in energy system. An Energy Security Index I

ES

making comprehensive yet clear reference to the current scope of energy security is introduced as the indicator. Next, the paper proposes an integrated framework to develop long-term security improvement plan in energy system. The framework is constructed with a holistic planning cycle to evaluate energy security policies’ effectiveness, project estimated I

ES

with optimized energy portfolio, and verify the results generated. The framework is established with integrated analytical process incorporating FAHP, which better accommodates the complexities and uncertainties throughout planning. Meanwhile, the complete planning cycle enhances the tool validity. This framework would be useful in helping policy makers obtain a helicopter view of the security level of their energy system, and identify the general improvement direction. An application of the proposed framework to Singapore context shows “Reduce and Replace” strategy should be implemented and 77 % improvement in I

ES

is expected by 2030 comparing to business-as-usual scenario.

Ying Wang, Kim Leng Poh

An EPQ with Shortage Backorders Model on Imperfect Production System Subject to Two Key Production Systems

This paper is an extension of the work of Lin and Gong (

2011

) on Economic Production Quantity (EPQ) model on an imperfect production system over infinite planning horizon, where the production system is dictated by two unreliable key production subsystems (KPS). While any shortage on the inventory of product was not allowed in the model of Lin and Gong (

2011

), planned shortage backorders is considered in the model proposed in this paper. The mathematical model is developed in order to determine production run time (τ) and production time when backorder is replenished (

T

1

) that minimizes the expected total cost per unit time including setup, inventory carrying, shortage, and defective costs. Approaches to solve the model are also being proposed in this paper, altogether with some numerical examples.

Baju Bawono, The Jin Ai, Ririn Diar Astanti, Thomas Indarto Wibowo

Reducing Medication Dispensing Process Time in a Multi-Hospital Health System

The process of prescribing, ordering, transcribing, and dispensing medications is a complex process and should efficiently service the high volume of daily physician orders in hospitals. As demand for prescriptions continues to grow, the primary issue confronting the pharmacists is overloading in dispensing the medication and tackling the mistakes caused by misinterpretation of the prescriptions. In this paper, we compared two prescribing technologies, namely no carbon required (NCR) and digital scanning technologies to quantify the advantages of the medication ordering, transcribing, and dispensing process in a multi-hospital health system. NCR technology uses a four parts physician order form with no carbon required copies, and digital scanning technology uses a single part physician order form. Results indicated a reduction of 54.5 % in queue time, 32.4 % in order entry time, 76.9 % in outgoing delay time, and 67.7 % in outgoing transit time in digital scanning technology. Also, we present the cost analysis to justify the acquisition of the Medication Order Management System (MOMS) to implement digital scanning technology.

Jun-Ing Ker, Yichuan Wang, Cappi W. Ker

A Pareto-Based Differential Evolution Algorithm for Multi-Objective Job Shop Scheduling Problems

This paper presents a multi-objective differential evolution algorithm (MODE) and its application for solving multi-objective job shop scheduling problems. Five mutation strategies with different search behaviors proposed in the MODE are used to search for the Pareto front. The performances of the MODE are evaluated on a set of benchmark problems and the numerical experiments show that the MODE is a highly competitive approach which is capable of providing a set of diverse and high-quality non-dominated solutions compared to those obtained from existing algorithms.

Warisa Wisittipanich, Voratas Kachitvichyanukul

Smart Grid and Emergency Power Supply on Systems with Renewable Energy and Batteries: An Recovery Planning for EAST JAPAN Disaster Area

This paper describes the design method of smart grid energy systems based on the simulation for introducing renewable energy (RE) and secondary batteries. The emergency power is also available. Managing RE systems and battery storage can minimize the cost of electricity by optimization balance between supply and demand as well as can reduce environmental impacts. Also the systems enable us to use emergency power supply for accidents and disasters, and to enhance robustness of electric power systems. To actualize the electricity management systems, the object-oriented and time-marching energy management simulator is developed which simulates power production, transmission and distribution, charge and discharge, and consumption of electricity every half hour. By using that simulator, peak and amount of power supply can be decreased. As a case study, we applied the systems with photovoltaic power (PV) generation and secondary batteries to reconstructed elementary schools that were damaged by Tohoku earthquake and tsunami on March 11, 2011, and consequently the validity of the analysis was obtained. Furthermore, it was verified the case that the systems were applied to business, which involves more profits than public facilities, and we examined requirements for business.

Takuya Taguchi, Kenji Tanaka

Establishing Interaction Specifications for Online-to-Offline (O2O) Service Systems

Information technology products such as smart phones, tablet PCs, eBooks and the intelligent-interactive digital signage have evolved and perfectly merged with the service systems to provide user-friendly user-interfaces and innovative service patterns. Online-to-offline (O2O) service model is one of the newest developments in the service systems where users in the physical world can interact with service providers in the cyberspace through various devices. Although traditional HCI studies have provided various research frameworks to describe interfaces and activities involved, there is a lack of interaction specifications which can clearly describe HCI in the realm of O2O service systems. This study developed a formal language that facilitates establishment of HCI specifications for O2O applications in proximity commerce based on interaction styles consisting of 4 interaction types represented in an interaction diagram. The formal language thus provides a common ground for service provider and service implementer to communicate and develop a concrete prototype effectively.

Cheng-Jhe Lin, Tsai-Ting Lee, Chiuhsiang Lin, Yu-Chieh Huang, Jing-Ming Chiu

Investigation of Learning Remission in Manual Work Given that Similar Work is Performed During the Work Contract Break

According to literature, when a worker performs a task repeatedly, the time it takes to do the task decreases. This is based on the concept of learning curve. When the worker spends time away from work, there is usually an observed time decrement, as described by learning remission. A question may be “in case the worker does not completely stop working during the work break but performs ‘similar work’, how much remission can be expected?” Similar work may be work that share operations with the work prior to the break, but not completely the same. To investigate on learning remission, this research worked with a semiconductor and a hockey glove sewing business. The objective was to find the amount of similar work needed to be done during the work break to possibly reduce or avoid learning remission. The finding for the test case is, when at least 21 % of the supposed work break is spent doing the previous work, learning remission may not result. It is possible that for other industries, researchers may find similar results. This will help organizations transferring workers from one kind of work to another, not have increase in work time as a result of learning remission.

Josefa Angelie D. Revilla, Iris Ann G. Martinez

A Hidden Markov Model for Tool Wear Management

Determining the best time of tool replacement is critical to balancing production quality and tool utilization. A machining process would gradually produce defective parts as a tool wears out. To avoid additional production costs, replacing a tool before the yield drops below a minimum requirement is essential. On the other hand, frequent tool replacement would cause additional setup and tool costs. This paper proposes a hidden Markov model (HMM) to study the unknown nature of a tool wear progress by monitoring the quality characteristic of products. With the constructed model, the state of tool wear is diagnosed by using the Viterbi Algorithm. Then, a decision rule that evaluates the yield of the next machining part is proposed to determine the initiation of tool replacement. The simulation analysis shows that the proposed method could accurately estimate the model and the status of tool wear. The proposed decision rule can also make good use of tools whereas controlling yield.

Chen-Ju Lin, Chun-Hung Chien

Energy Management Using Storage Batteries in Large Commercial Facilities Based on Projection of Power Demand

This study provides three methods for projection of power demand of large commercial facilities planned for construction, for the operation algorithm of storage batteries to manage energy and minimize power costs, and for derivation of optimal storage battery size for different amounts of power demand and building use. The projection of power demand is derived based on statistics of building power demand and floor area. The algorithm for operating storage batteries determines the amount of purchased electricity on an hourly timescale. The algorithm aims to minimize the cost of power through two approaches: first by reducing the basic rate determined by the peak of power demand, and second by utilizing the power purchased and charged at nighttime when the price of power is lower. Optimization of storage battery size is determined by calculating internal rate of return, which is derived by considering the profit from energy management, cost, and storage battery lifetime. The authors applied these methods to commercial facilities in Tokyo. The methods successfully helped the facility owners to determine appropriate storage battery size and to quantify the profit from their energy management system.

Kentaro Kaji, Jing Zhang, Kenji Tanaka

The Optimal Parameters Design of Multiple Quality Characteristics for the Welding Thick Plate of Aerospace Aluminum Alloy

The welding of different metal materials such as aerospace aluminum alloy has superior mechanical characteristics, but the feasible setting for the welding parameters of the TIG has many difficulties due to some hard and crisp inter-metallic compounds created within the weld line. Normally, the setting for welding parameters does not have a formula to follow; it usually depends on experts’ past knowledge and experiences. Once exceeding the rule of thumb, it becomes impossible to set up feasibly the optimal parameters, and the past researches focus on thin plate. This research proposes an economic and effective experimental design method of multiple characteristics to deal with the parameter design problem with many continuous parameters and levels for aerospace aluminum alloy thick plate. It uses TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and Artificial Neural Network (ANN) to train the optimal function framework of parameter design for the thick plate weldment of aerospace aluminum alloy. To improve previous experimental methods for multiple characteristics, this research method employs ANN and all combinations to search the optimal parameter such that the potential parameter can be evaluated more completely and objectively. Additionally, the model can learn the relationship between the welding parameters and the quality responses of different aluminum alloy materials to facilitate the future applications in the decision-making of parameter settings for automatic welding equipment. The research results can be presented to the industries as a reference, and improve the product quality and welding efficiency to relevant welding industries.

Jhy-Ping Jhang

Synergizing Both Universal Design Principles and Su-Field Analysis to an Innovative Product Design Process

To promote developing more usable and accessed, daily-used products that could meet the rigorous requirements from diverse consumers at the present time, this research proposed an innovative product design process by synergizing both universal design (UD) principles and TRIZ tools. This newly developed process started with stating the design problems via a UD evaluation, followed by PDMT analysis to develop the preliminary design directions. The directions were then analyzed by using Su-Field models in order to locate the potential resolutions from TRIZ’s 76 Standard Solutions. Finally, a case study was conducted to demonstrate how this innovative design process works. Study result shows that this approach can help identify the core of the problem and locate the improved product concepts effectively, resulting in generating more creative and usable product design.

Chun-Ming Yang, Ching-Han Kao, Thu-Hua Liu, Ting Lin, Yi-Wun Chen

The Joint Determination of Optimum Process Mean, Economic Order Quantity, and Production Run Length

In this study, the author proposes a modified Chen and Liu’s model with quality loss and single sampling rectifying inspection plan. Assume that the retailer’s order quantity is concerned with the manufacturer’s product quality and the quality characteristic of product is normally distributed. Taguchi’s symmetric quadratic quality loss function will be applied in evaluating the product quality. The optimal retailer’s order quantity and the manufacturer’s process mean and production run length will be jointly determined by maximizing the expected total profit of society including the manufacturer and the retailer.

Chung-Ho Chen

Developing Customer Information System Using Fuzzy Query and Cluster Analysis

Customer information is critical to customer relationship management. The goal of this research is to improve the efficiency of customer relationship management through developing a customer information system. Fuzzy terms with linguistic variables can help specific queries to be more versatile and user friendly for customer data mining. In this paper, we propose a method integrating cluster analysis with linguistic variables in the context of fuzzy query logistics. Based on the proposed method, we constructed a customer information system that can offer the user useful information as regards with strategy, decision making, and better resource allocation methods. We expect to decrease total execution time and to increase the practicability with the feature of customer information cluster analysis.

Chui-Yu Chiu, Ho-Chun Ku, I-Ting Kuo, Po-Chou Shih

Automatic Clustering Combining Differential Evolution Algorithm and k-Means Algorithm

One of the most challenging problems in data clustering is to determine the number of clusters. This study intends to propose an improved differential evolution algorithm which integrates automatic clustering based differential evolution (ACDE) algorithm and

k

-means (ACDE-

k

-

means

) algorithm. It requires no prior knowledge about number of clusters.

k

-means algorithm is employed to tune cluster centroids in order to improve the performance of DE algorithm. To validate the performance of the proposed algorithm, two well-known data sets, Iris and Wine, are employed. The computational results indicate that the proposed ACDE-

k

-means algorithm is superior to classical DE algorithm.

R. J. Kuo, Erma Suryani, Achmad Yasid

Application of Two-Stage Clustering on the Attitude and Behavioral of the Nursing Staff: A Case Study of Medical Center in Taiwan

The purpose of this study was to probe into and organizing personnel representing attitude and behavior that the function should possess, a case study of medical center nursing categories of employees for the study, due to the professionalism of nursing staff for the establishment of a good nurse-patient relationship as well as to demonstrated the attitude of an important condition, in this study was with Situational judgment test the collect a nursing staff in the true working situational, the view on the function importance. Testing the materials is obtained by the database of this case hospital, carry on Two-stage clustering method hiving off laws (Self-Organizing Maps and K-means) secondary analysis, will be importance of “situational judgment test functions questionnaire” that the information collected, analyze attitude and behavior that nursing staff should possess. According the analysis results found that personnel in different posts and ranks between two groups of ‘staff’ and ‘executive’, to the attitude and behavioral cognition, think ‘responsible for seriously’ with ‘quality leading’ the most important, cultivation of the future nursing staff, should strengthen the cultivation of professional attitude, and implement the rigorous of standard operation procedure, period of to reduce the gap between of health professional education and clinical/nursing practice.

Farn-Shing Chen, Shih-Wei Hsu, Chia-An Tu, Wen-Tsann Lin

The Effects of Music Training on the Cognitive Ability and Auditory Memory

Previous research indicated a link between music training and cognitive ability. Despite some positive evidence, there is a different point about which abilities are improved. In this study, one experiment was conducted to investigate the effect of music training on memory retention. Two input modalities (visual and auditory) and delay time (0, 4, 6, 8, and 10 s) were manipulated. Participants were asked to finish prime task (memory retention) and distraction task (press the direction key to match the word or arrow). The result showed that music trained group performed better than the non-music trained one. For music trained group, their performance showed no significant difference between visual and auditory modalities. Participants without music training performed much better on visual than on auditory modality. This result of this experiment may support the idea that the music training influences participant’s performance on memory retention. This research shows that music training is an important part of adolescent education and can help improve children’s cognitive abilities.

Min-Sheng Chen, Chan-Ming Hsu, Tien-Ju Chiang

Control Scheme for the Service Quality

This research constructs a novel quality control scheme for monitoring the service quality. Providing high-quality services can enhance company’s productivity and strengthen its competitiveness. Due to the diversity of service operation, measuring and monitoring the service quality becomes very difficult. PZB’s SERVQUAL is a commonly used scale to measure the service quality. The SERVQUAL scale has been shown to measure five underlying dimensions with 22 quality elements. After a questionnaire investigation, the collected information of service quality is often not monitored continually. If the service quality has variation, there will be no way for immediate correction. Precise instruments for measuring quality and accomplishing quality control have been developed and widely used in the manufacturing sector. The quality control chart is one of the commonly used tools of statistical process control for on-line control. Applying the control chart in the service quality can improve the control effect. In this work, the Ridit analysis is used to transform the collected data, which are mostly in Likert-scale, and to find the priority of quality elements. Some more important elements can be selected for the construction of control chart.

Ling Yang

Particle Swam Optimization for Multi-level Location Allocation Problem Under Supplier Evaluation

The aim of this paper is to propose the method for solving multi-level location allocation problems under supplier evaluation. The proposed problem is solved by particle swarm optimization (PSO). Generally, the multi-level location allocation problem considers the suitable locations to service customers or to store inventory from the suppliers. The proposed problem is to determine the suitable location to store and produce the product from the selected suppliers and then delivers product to the customers. The selected suppliers are determined by the capability of them. The capability of the suppliers means the quality of the material delivered and the reliability of delivery date which gather from their past statistics. The problem solving can be divided into two steps: the first step is to evaluate each potential supplier using fuzzy approach and second step is to selects the locations in order to serve the customer demand with minimum cost using PSO by calculating the amount of material shipped to location by a specified supplier closeness coefficient (CC

h

). As the results, the percentage error is between 0.89 and 16.90 % and the average runtime is 4.2 s.

Anurak Chaiwichian, Rapeepan Pitakaso

Evaluation Model for Residual Performance of Lithium-Ion Battery

This study suggested the evaluation model for Lithium-ion battery life. Considering the trend that eco-system has become serious concern against the global environment, Lithium-ion battery is most promising represented by Electric Vehicle. However, estimation method for residual battery performance has not been established. Therefore, asset value and payout period are forced to be unsure, namely, the spread of Lithium-ion battery has been prevented. This evaluation model developed in this study can calculate the residual battery performance by degradation rate database and assumed battery use pattern. The degradation rate database was established using charge–discharge test of Lithium-ion battery cell. By applying the database, the residual battery performance can be calculated under any battery use scenario. This model was validated by comparing the experimental data with the simulation result.

Takuya Shimamoto, Ryuta Tanaka, Kenji Tanaka

A Simulated Annealing Heuristic for the Green Vehicle Routing Problem

Nowadays, the encouragement of the use of green vehicle is greater than it previously has ever been. In the United States, transportation sector is responsible for 28 % of national greenhouse gas emissions in 2009. Therefore, there have been many studies devoted to the green supply chain management including the green vehicle routing problem (GVRP). GVRP plays a very important role in helping organizations with alternative fuel-powered vehicle fleets overcome obstacles resulted from limited vehicle driving range in conjunction with limited fuel infrastructure. The objective of GVRP is to minimize total distance traveled by the alternative fuel vehicle fleet. This study develops a mathematical model and a simulated annealing (SA) heuristic for the GVRP. Computational results indicate that the SA heuristic is capable of obtaining good GVRP solutions within a reasonable amount of time.

Moch Yasin, Vincent F. Yu

Designing an Urban Sustainable Water Supply System Using System Dynamics

This paper addresses the issue on designing an effective sustainable water supply system both in quantity and quality side, which is considered as a prerequisite for a sustainable development strategy. In order to achieve a sustainable water supply system, System Dynamics, which is an effective system analysis and development tool, is employed in modeling and simulating the system. The study presents a decision platform, where a quantified expected resilience model is built to measure water supply satisfaction rate, and to meet the requirements of sustainability indicators firstly. After determining the sustainability requirements, namely customer requirements, water supply system is constructed using system dynamics approach, through which the threats of the system such as demand boosting, pipeline aging, and other events that cause supply disruptions are illustrated subsequently. Further, prevention strategies will be taken into account to achieve the resilience ratio in the water system. Finally, a case study of water system in Shanghai is demonstrated to show the effectiveness of the proposed method.

S. Zhao, J. Liu, X. Liu

An Evaluation of LED Ceiling Lighting Design with Bi-CCT Layouts

Light-emitting diodes (LEDs) became an important home-lighting device. Due to the property of high efficiency LED lighting sources, thus we expected to apply high efficiency LED lighting to improve or enhance our lighting environment. The purpose of this study is to design LED ceiling lightings layout based on evaluating human’s physiological responses and subjective feelings, where the experiments were conducted in the office-like laboratory. We had four experimental combinations included two Correlated Color Temperature (CCT) and two different types of lighting sources (lower Blue-value and high-efficiency). Two different types of lighting sources, one was that the lower Blue-value lighting sources was equipped at the center of the device, the other was that high-efficiency equipped around the lower Blue-value lighting source. Six participants were recruited in this study to perform sheet, laptop-typing, and tablet-searching tasks under the four experimental combinations. In addition to working performance measures, heart rate, Galvanic Skin Response (GSR), eyes blink duration, blink time, and critical fusion frequency (CFF) values were measured as well. The results showed that CCT 4,000 K-high efficiency lightings design would affect human’s physiological alert and stress. Thus we suggested the CCT 4,000 K-high efficiency participants had lower Tablet-searching error rate higher physiological alert and less eye fatigue.

Chinmei Chou, Jui-Feng Lin, Tsu-Yu Chen, Li-Chen Chen, YaHui Chiang

Postponement Strategies in a Supply Chain Under the MTO Production Environment

Postponement strategies that decrease the impact of uncertainty of demand and improve customization have implemented for a long time in the supply chain. Postponement is to start to perform some operations until the customized order is received, and it does not go by forecast like the traditional approach. In modeling postponement, most researchers focus on manufacturing postponement and they do not consider production environment. This study considers the production environment of make to order to develop a supply chain network and to study the optimal combination of postponement operations in the supply chain, such as manufacturing, packaging, and logistics. We take notebook computer as an example to show the optimal combination of postponement strategies when the minimum total cost is reached. We believe that the results of this study would provide suggestions to managers for their supply chain operational decisions.

Hsin Rau, Ching-Kuo Liu

Consumer Value Assessment with Consideration of Environmental Impact

In response to climate change, environmental issues, such as greenhouse gas emissions and carbon footprint, become important. Products are required to take into account of life-cycle thinking in their product design phase. In the past, enterprises only pursued the quality improvement and technology development of green products, but they ignored the value of consumers in those eco-design products. This ignorance results in weak competition; however, it gives the motivation of this study. This study is based on the concept of eco-efficiency to develop a consumer value assessment model with consideration of environmental impact. Several different types of laptop computers are used as examples to illustrate the application of our assessment model. This model simultaneously considers the value of functional performance, the total cost of ownership, and the environmental impact for the product. The environmental impact includes the assessment of energy consumption, pollution and non-recyclability. We believe that our proposed model can be served as a guidance of product improvement or innovation for the designer, and a reference of purchasing products for consumers.

Hsin Rau, Sing-Ni Siang, Yi-Tse Fang

A Study of Bi-criteria Flexible Flow Lines Scheduling Problems with Queue Time Constraints

This paper considers the scheduling problems in a flexible flow line (FFL) with queue time constraints. The objective of the scheduling problems is to minimize the primary criterion which is exceeding queue time constraint times and the secondary criterion which is makespan. The problem considered in the paper is a NP-hard in a strong sense. It requires much computation time to find the optimal solution; therefore, heuristics are an acceptable practice for finding good solutions. In this paper, a meta-heuristic is proposed to solve the candidate problems. In order to evaluate the performance of the proposed heuristics, a conventional tabu search algorithm is examined for comparison purposes. The results show the proposed meta-heuristic performs effective.

Chun-Lung Chen

Modeling the Dual-Domain Performance of a Large Infrastructure Project: The Case of Desalination

The performance of a large infrastructure project depends on not only technical design choices, but also contractual and other economic arrangements. These choices and arrangements interact in the context of uncertainty to result in the project’s realized performance. Large infrastructure projects such as desalination plants are thus multi-dimensional design problems in which the dimensions can be broadly categorized into either the technical or institutional domains, creating the need for “dual-domain design”. This paper describes the concept of dual-domain design for infrastructure in the context of desalination projects in the Kingdom of Saudi Arabia. It demonstrates the results of an analytical model that relates design choices along some technical and institutional design dimensions to plant economic performance. The analysis shows that plant design can be optimized subject to an uncertainty profile of water demand, and is sensitive to technology type, output capacity and potentially to price/contractual terms embedded in the delivery mode. The lens of dual-domain design thus provides a richer understanding of the relationship between project design and potential performance. Next steps can include multi-attribute assessments of performance (energy, environmental impact, etc.) as well as a greater variation in contractual forms in the institutional domain of design.

Vivek Sakhrani, Adnan AlSaati, Olivier de Weck

Flexibility in Natural Resource Recovery Systems: A Practical Approach to the “Tragedy of the Commons”

“As overuse of resources reduces carrying capacity, ruin is inevitable” (Hardin

1998

). In his controversial paper of 1968, Garrett Hardin introduced the concept of the

tragedy of the commons

in which the freedom of individuals to maximize their personal utility of common resources/goods (water, air, land, and so forth) leads to the destruction of those resources. While this problem is initially one of economic, socio-political, and ecological systems, in the end, it also an engineering problem since many current and future solutions depend on engineering systems design and implementation. Focusing on a single area of concern—construction and demolition (C&D) waste—I examine current U.S. practices in waste management and resource recovery. I then present a case study demonstrating the real-world use of flexibility in C&D natural resource recovery systems and explore its practical implications for a proposed paradigm shift that could resolve this one aspect of the

tragedy of the commons

.

S. B. von Helfenstein

The Workload Assessment and Learning Effective Associated with Truck Driving Training Courses

Present study examined the workload and applied the theory of learning curve to evaluate the learning effective for training of driving courses. The trainees’ workloads were assessed by the NASA-TLX twice, one on the 10th and the other on the last (28th) practice. Forty healthy male solders with an average age 23.2 years participated in this study, and a HINO 10.5T trunk was used for training in a standard training field. Five driving tasks evaluated were “going up and down a hill (up/down hill)”, “three-point turn on a narrow road (3-point turn)”, “moving forward and backward on an S curve (S-curve)”, “reversing the car into a garage (reversing-into-garage)”, and “parallel parking”. For learning cures, the values of among 40 participants were averaged within each practice for each task, and the overall Wright’s learning curves model for each driving task was fitted. Results showed all R

2

s were significantly high with a range of 0.88–0.97. This implied that these learning curves of trunk driving tasks were able to be fitted by power function very well. Specifically, the learning rate was 0.9162 for up/down hill, 0.8912 for 3-point turn, 0.8802 for parallel parking, 0.8736 for reversing-into-garage, and 0.8698 for S-curve. For workload, the results indicated that the second measure (on 28th practice) was lower than the first measure (on 10th practice) for all evaluated tasks. This implied that practice was also able to reduce the overall workloads. Additionally for the task effect, S-curve task had the highest workload, 3-point-turn task had the lightest workload, and the rest three were not significantly different from each other. After practices, there were more reduction in workload for the tasks of S-curve, reversing-into-garage, and parallel parking.

Yuh-Chuan Shih, I-Sheng Sun, Chia-Fen Chi

Prognostics Based Design for Reliability Technique for Electronic Product Design

Techniques that can effectively reduce failure rate, control life span and predict product life are highly expected in modern electronic products. Design for Reliability (DFR) technique introduced in this study, applies various robust design and system reliability modeling methods to evaluate whether reliability target can be met in product development stage. However, DFR technique often faces challenges mainly on insufficient accuracy of system reliability prediction. Prognostics and Health Management (PHM) technique applies failure precursors and their impact on product real failure to improve accuracy of reliability prediction in design phase. This study integrates DFR and PHM techniques for reliability prediction. Hard disk drive is selected as a case study for PHM application in design phase. A failure precursor of drive is selected and its statistical distribution of time-to-failure-precursor is established. Applying conditional reliability and residual mean-time-to-failure, remaining useful life (RUL) estimation is proposed. The prognostic based DFR developed in this study plays a key role in predicting product reliability during development stage as well as catastrophic failure prevention in maintenance stage.

Yingche Chien, Yu-Xiu Huang, James Yu-Che Wang

A Case Study on Optimal Maintenance Interval and Spare Part Inventory Based on Reliability

An engine fuel supply subsystem for particular type of aircraft plays an important role in providing, controlling, and distributing the fuel during engine operation. Failure on this subsystem will affect the readiness of the aircraft for operations. Therefore, for system experienced an aging characteristic or wear-out period, determining of the optimal preventive maintenance and optimal preventive replacement interval by considering the total cost of maintenance per unit time is important. In order to support the replacement activity, available number of spare parts required and must be well controlled to avoid either over stock or shortage. In this study, we attempt to determine the preventive maintenance interval and preventive replacement interval and its required inventory spare parts as well. We deliberate the cost structure, failure field data, and the reliability along the designing and managing the maintenance activity. We also examine the implication of the designed maintenance interval on reliability and availability of the system.

Nani Kurniati, Ruey-Huei Yeh, Haridinuto

Developing Decision Models with Varying Machine Ratios in a Semiconductor Company

In a semiconductor manufacturing, operators are usually faced with simultaneous activities and therefore it is a requirement that they should have adequate decision making skills. While their main responsibility is to ensure that the machines are continuously running, they are also expected to perform other activities during their assigned working hours. For cases of machine breakdown, one methodology being used is the recognition-primed decision model which is a pattern recognition problem diagnosis procedure. This methodology, however, is appropriate only for single machine breakdown. Thus, a revised decision model is developed to incorporate multiple decision points.

Rex Aurelius C. Robielos

New/Advanced Industrial Engineering Perspective: Leading Growth Through Customer Centricity

Inside Out to Outside In Through Expert Systems.

The expert-system-based automated process planning systems are prevalent in Manufacturing and become state of the art tool of successful Industrial Engineers. The author attempted to utilize the concepts of New/advanced Industrial Engineering to apply the capabilities of information technology to redesign business processes in educational institution to reduce the cost, time, and improve quality of its processes by embedding the knowledge of its best decision makers/experts in a “Teaching/learning expert system including scholarship authorization” as part of overall Director Academics Software. The author proposes a concept of software realization of an expert system by assembling experts experience in Personal Computer as knowledge base on the hypothesis that ‘knowledge never dies’, once we adopt the knowledge of some experts and use it in our system, this knowledge works more efficient than a simple work routine. Director Academics is a tool designed and created for Head of institutions. Here author explored his work in the field of Expert System development, especially what he experiences by working in the Institute and what he learns while he worked under professors. The proposed paper is based on the Rule Based and Case Based Reasoning. In the last author explored his and his senior’s experiences.

Suresh Kumar Babbar

Scheduling a Hybrid Flow-Shop Problem via Artificial Immune System

This paper investigates a two-stage hybrid flowshop problem with a single batch processing machine in the first stage and a single machine in the second stage. In the problem, each job has an individual release time and the jobs are grouped into several batches. To be more practical in real applications, the waiting time between the batch machine and the single machine is restricted. Since the problem is NP-hard, an immunoglobulin-based artificial immune system (IAIS) algorithm is developed to find an optimal or near-optimal solution. To verify IAIS, comparisons with two lower bounds in the second problem are made. Computational results show that the proposed IAIS algorithm is quite stable and efficient.

Tsui-Ping Chung, Ching-Jong Liao

Modeling and Simulation on a Resilient Water Supply System Under Disruptions

We address the resilient water supply system against disruptions in megacities. The study is aimed at developing a quantitative approach for assessing the resilience of water supply system to disruptions. In this context, we propose a decision model incorporates two determinants of system resilience both in robust level and recovery time, and discuss their relationship towards the occurrence of disruptions. Furthermore, a simulation-based model is proposed that incorporates resilience into the proper performances of water supply system, which leads to the impacts of the loss caused by those disruptions. We also present a case study in which the resource scheduling strategies are taken into account to increase the resilience level of water supply system, such as the level of inventory, pipeline-dispatched water, and dispatched water by transportation.

X. Liu, J. Liu, S. Zhao, Loon Ching Tang

A Hybrid ANP-DEA Approach for Vulnerability Assessment in Water Supply System

Vulnerability reflects the potential of disrupting the whole system to some extent when the system is exposed to hazard. One of the most important issues of the indicator-based vulnerability assessment problem is to determine the weights of vulnerability indicators, especially when they are correlated with each other in multiple dimensions (i.e., physical, functional and organizational). In this paper, a framework for assessing vulnerability of critical infrastructure system is identified and applied to the evaluation in a water supply system. A complete critical infrastructure system vulnerability index is developed, which contains dimensions of “protection and defense”, “quick response after disaster”, “maintenance and recovery capacity” and “possible damage to system”. A quantitative method, integrating analytic network process (ANP) and game cross-efficiency data envelopment analysis (DEA) model, is proposed to analyze the vulnerability of interdependent infrastructures. Finally, the assessed vulnerability level of each infrastructure in water supply system is graded into four classes.

C. Zhang, X. Liu

An Integrated BOM Evaluation and Supplier Selection Model for a Design for Supply Chain System

In a supply chain, the design of a product can affect the activities in the forward and reverse supply chains. Given a product requirement, the components of the product can be designed with different specifications. As a result, the bill of material and the manufacturing activities will be different. Therefore, in different design alternative cases, there can be different decisions of supplier selection for producing the product. In this research, a new model for supplier selection and order assignment in a closed-loop supply chain system is presented. First, the design information of the design alternative cases are analyzed and represented in the form of a bill of material model. Next, a mathematical model is developed for supplier selection and order assignment by evaluating the design and closed-loop supply chain costs. Finally, a solution model using the particle swarm optimization method with a new encoding scheme is presented. The new model is developed to determine the decisions of design evaluation and supplier selection under the constraints of capacity and capability to achieve a minimized total cost objective. In this paper presentation, an example product is illustrated. The test results show that the model and solution method are feasible and practical.

Yuan-Jye Tseng, Li-Jong Su, Yi-Shiuan Chen, Yi-Ju Liao

Estimation Biases in Construction Projects: Further Evidence

Construction projects are characterized by their unique and temporary features. Very limited data, if any, would be available and readily transferable for the analysis of subsequent projects. Hence most project analysts would depend on intuitions and gut feelings to make judgment and estimations. This experimental study is a follow-up study on investigating the possible existence of systematic estimation errors (biases in estimations) in an Indonesian context. It is focused on the two suspected types of biases; the anchoring accuracy and overconfidence biases in project time duration estimates. Two groups of estimators (experienced, n = 20 vs. non-experienced, n = 20) were involved in the study. A hypothetical project case based on an actual construction project was developed. The estimators were then individually requested to provide duration estimates (for each project activity and overall) for the project case. The estimates were then compared against the actual duration of the project. The result of suggests that anchoring bias is not statistically observable for both non-experienced and experienced estimators. This study finds that overconfidence bias is identifiable when making the range estimation of the project duration.

Budi Hartono, Sinta R. Sulistyo, Nezar Alfian

Exploring Management Issues in Spare Parts Forecast

According to literature, we know that research in spare parts forecast is a very popular topic in recent years due to the need of higher service level of customer demand. Most approaches in these researches focus on how to forecast spare parts more accurately under various conditions with some mathematical techniques. However, few attentions are paid to the management issues to control or maintain some factors to keep the spare parts forecast useful. For example, Engineering Change (EC) often introduce lots of planed items no longer valid and consume mass efforts trying to continue the spare parts support. This motivates our study. This study starts from service process, spare parts requirement, and spare parts forecast flow. When we come to investigate management issues in spare parts forecast, besides EC, such as issues like different service models for OEM, ODM or Brander, spare parts information correctness and service organization structures are worth exploring.

Kuo-Hsing Wu, Hsin Rau, Ying-Che Chien

Artificial Particle Swarm Optimization with Heuristic Procedure to Solve Multi-Line Facility Layout Problem

The facility layout problem (FLP) has an important effect on the efficiency and the profitability of the manufacturing system from the standpoint of the cost and time. This research has objective to minimize total material handling cost. Multi-line facility layout problems (MLFLP) is FLP that assigns a few facilities in the two or more lines into industrial plant, where the number of the facilities is less than the number of the locations with no constraint for placing the facilities. This study present Heuristic Artificial Particle Swarm Optimization (HAPSO) a hybrid meta-heuristic algorithm to solve MLFLP and it consider the multi-products. The proposed algorithm applied to the case study from other paper. The computational results indicate that the proposed algorithm more effective and efficient to solve the case.

Chao Ou-Yang, Budi Santosa, Achmad Mustakim

Applying a Hybrid Data Preprocessing Methods in Stroke Prediction

Stroke has always been highlighted as big threat of health in the worldwide. Brain image examination and ultrasound are some alternatives to discover stroke disease. Data mining has been used widely in many areas, include medical industry. The uses of data mining methods can help doctors to make prediction of certain diseases. Therefore, in this research, a hybrid model integrating imbalance data preprocessing, feature selection, and back propagation network, decision tree for stroke prediction. The dataset used is brain examination data which collected from 2004 to 2011. However, highly imbalance dataset available can impact the performance of prediction as well as feature selected. The study firstly “rebalance” the dataset by comparing sampling methods; RUSboost and MSmoteBoost. In addition, important features of balance training dataset would be selected by information gain, stepwise regression based feature selection. Towards the end, selected features would be processed using Back Propagation Network and Decision Tree to predict the stroke. These hybrid methods can assist doctor to provide some possibilities information to the patient.

Chao Ou-Yang, Muhammad Rieza, Han-Cheng Wang, Yeh-Chun Juan, Cheng-Tao Huang

Applying a Hybrid Data Mining Approach to Develop Carotid Artery Prediction Models

This paper performs a hybrid method for imbalanced medical data set with many features on it. A synthetic minority over-sampling technique (SMOTE) is used to solve two-class imbalanced problems. This method enhanced the significance of the small and specific region belonging to the positive class in the decision region. The SMOTE is applied to generate synthetic instances for the positive class to balance the training data set. Another method that used is Genetic Algorithm for feature selection. The proposed of this method is to receive the reduced redundancy of information among the selected features. On the other hand, this method emphasizes on selecting a subset of salient features with reduced number using a subset size determination scheme. Towards the end, selected features would be processed using back Propagation Network (NN) and Decision Tree to predict the accuracy of Carotid Artery Disease. Experimental results show that these methods achieved a high accuracy, so it can assist the doctors to provide some possibilities information to the patient.

Chao Ou-Yang, Inggi Rengganing Herani, Han-Cheng Wang, Yeh-Chun Juan, Erma Suryani, Cheng-Tao Huang

Comparing Two Methods of Analysis and Design Modelling Techniques: Unified Modelling Language and Agent Modelling Language. Study Case: A Virtual Bubble Tea Vending Machine System Development

The developing of internet worldwide encourages the research in Software Engineering fields in the development of numerous analysis and design methods used in Software Development. Among these methods, Unified Modelling Language (UML) has been known to Software developers as a popular object-oriented tool to analyze and design a system. On the other hand, a less known tool, Agent Modeling Language (AML), is a semi-formal visual modeling language for specifying, modelling and documenting system that incorporate features drawn from multi-agent system theory. This paper presents an overview of UML and AML using the case of Virtual Bubble Tea Vending Machine Software development. This paper also compares UML and AML methods in analyzing phase and designing phase in system development.

Immah Inayati, Shu-Chiang Lin, Widya Dwi Aryani

Persuasive Technology on User Interface Energy Display: Case Study on Intelligent Bathroom

Computing products for creating persuasive technology are getting easier to use with innovations in online video, social networks, and metrics, among others. As a result, more individuals and organizations can utilize different media to influence people’s behaviour via technology channels. In-home displays (IHDs) are one of these trendy and powerful media that have the potential to communicate energy usage feedback and to persuade energy saving action to householders. By providing real-time information on energy consumption, IHDs can persuade householders to change into target behaviour. IHDs user interface design plays a significant role in the success of persuading user behaviour change. This paper presents a laboratory study to investigate how the user interface design of IHDs might persuade people to save energy. A model was proposed, questionnaires, including open-ended questionnaire and closed-ended questionnaire, were created at a first phase of the lab study to gather information regarding user preference among 35 information displays and icon displays. In the second phase study, two user interface prototypes, one with target behaviour feedback and one without, will be developed to investigate user’s behaviour change in intelligent bathroom with regard to energy conservation.

Widya Dwi Aryani, Shu-Chiang Lin, Immah Inayati

Investigating the Relationship Between Electronic Image of Online Business on Smartphone and Users’ Purchase Intention

The extensive popularity of smartphones has been recently providing online business practitioners with an alternative useful channel to communicate product information with potential and existing customers. Previous research on Internet shopping suggests that electronic image, the quality of product information within the shopping website, plays a critical role in influencing online shoppers’ purchase decisions substantially. Therefore, by leveraging prior studies on website quality and web customer behavior, this study aims to identify the influential factors that contribute to the electronic image of shopping websites on smartphones, and investigates the effect of smartphone users’ perception of the electronic image upon their intended purchases. The arguments proposed for this study were empirically validated by using the data from a web survey of 321 smartphone users in the context of two online bookstores. The findings suggest that users’ perception of the electronic image on a smartphone related to the usefulness and scope of product information influences their purchase intention.

Chorng-Guang Wu, Yu-Han Kao

Forecast of Development Trends in Big Data Industry

Big Data technology is used to store, convert, transmit and analyze large quantities of dynamic, diversified data, which may be structured or unstructured data, for the purpose of commercial or social benefit. Big data technology applications need to be able to undertake real-time, high-complexity analysis of vast amounts of data, to help business enterprises perform decision-making within the shortest possible timeframe. With the rapid pace of development in cloud computing applications, both public cloud and private cloud data centers are continuing to accumulate enormous volumes of data. As a result, big data technology applications are becoming ever more important. This paper will analyze recent development trends in the field of big data industry for the reference of interested parties.

Wei-Hsiu Weng, Wei-Tai Weng

Reliability Analysis of Smartphones Based on the Field Return Data

In recent years, smartphones have become indispensable tools and media for obtaining information. Consequently, investigation and data analysis studies exploring smartphone reliability and failure rates have become increasingly important for mobile phone retailers and manufacturers. The design capabilities and manufacturing technologies for smartphones are continuously upgraded, and customer requirement for reliability increase correspondingly. Therefore, this study investigated after-sales repair and maintenance data obtained from a Taiwanese mobile phone maintenance provider for three brands of smartphones (A, B, and C). We assumed that the quality of the different models of the three brands is consistent. Statistical analysis techniques and software were used to calculate the parameter values of four failure probability distribution functions (i.e., exponential, log-normal, log-logistic, and Weibull). The maximum likelihood estimation (MLE) method was also employed to assess the log-likelihood value and determine the most appropriate failure probability distribution for each smartphone. Finally, we calculated the predicted market failure rate for the three smartphone brands. The results and conclusions obtained in this study can benefit important market players, such as consumers, mobile phone retailers, and manufacturers, regarding smartphone quality, sales strategies, after-sales warranty service packages, and manufacturing process improvements.

Fu-Kwun Wang, Chen-I Huang, Tao-Peng Chu

The Impact of Commercial Banking Performance on Economic Growth

The financial sector and economic growth spark hot debates. This paper addresses the question of whether commercial banking performance in Nepal reasons to economic growth. In order to answer this question, the present study focuses on analyzing the relationship between deposit, loan and advances and assets as proxy for performance of commercial banks while gross domestic product proxies economic growth over the period of 1975–2010. Using Augmented Dickey Fuller and Ordinary Least Square, the regression results indicated that deposits and assets have significant impact on the economic growth of Nepal while loan and advances has insignificant impact on the economic development. Furthermore, the Granger-Causality test suggests that there was no causality with deposit, loan and advances and assets with the economic acceleration. It can be concluded that not only commercial banking performance but also other variables political stability and technology play the important role in the economic advances in Nepal.

Xiaofeng Hui, Suvita Jha

Data and Information Fusion for Bio-Medical Design and Bio-Manufacturing Systems

This paper presents methods of data analysis and information fusion in bio-medical design and bio-manufacturing system performance improvement. Technical methods of data and information fusion and the new industrial engineering role in bio-medical design and bio-manufacturing systems development are discussed in this paper. A case study in regenerative medicine is presented to validate the product development lead time estimation, and to demonstrate that the total processing time can be significantly reduced through integrated approach. In overview, this research develops a method for transforming uncontrolled biological procedures into reproducible, controlled manufacturing processes.

Yuan-Shin Lee, Xiaofeng Qin, Peter Prim, Yi Cai

Evaluating the Profit Efficiency of Commercial Banks: Empirical Evidence from Nepal

This study offered an application of a non-parametric analytic technique, namely data envelopment analysis for measuring the performance of the Nepalese commercial banking sector. It explored the efficiency of the Nepalese commercial banks with the use of interest expenses and loan loss provision as inputs and net interest income, commission income and other operating income as outputs for the period of 2005–2010. It was also observed the effects of scale and of the mode of ownership (public sector, joint venture and domestic private sector) on bank behavior and therefore, on bank performance in the Nepalese banking industry. The public sector banks most recently in the analyzed period were observed to perform relatively more efficient than joint venture banks and domestic private banks with respect to their profit efficiency due to the large scale of branch networks.

Suvita Jha, Xiaofeng Hui, Baiqing Sun

Explore the Inventory Problem in a System Point of View: A Lot Sizing Policy

This article presents a study on the make-to-order inventory management problem in an anonymous manufacturer which produces precision screw and bolt for European customers. Seeing that this company keeps about 800 active wide varieties of screw and bolt items, of which the manufacturing normally undergoes six processing steps each requires 1–4 h setup before production proceeds, the company is forced to keep inventory-item in their make-to-order production. In this clear and certain inventory problem setting, we can make a study from system point of view to effectively reduce the inventory and meet customers’ requirements. Although the operations of business are preceded by the operation mechanism, it is easily found that we still can enhance inventory performance by some control factors such as lot-size policies and parameters. To facilitate the study we develop a system simulator according to the company’s SOP as the tool to visualize the inventory problem then achieve effective management.

Tsung-Shin Hsu, Yu-Lun Su

Global Industrial Teamwork Dynamics in China and Southeast Asia: Influence on Production Tact Time and Management Cumulative Effect to Teamwork Awareness-1/2

This research is international comparative survey on the teamwork awareness (TA) of China (four plants/Dalian, Shanghai: two, Guanzhou) and, Malaysia, Thailand and Vietnam in Southeast Asia. TA of the first line workers is compared between plants through country according to same category products.

A

nd those seven plants are surveyed from the production tact time (PTT) and the cumulative management effect (CME) from point of view. It clears TA are different by PTT and CME even if same category products. PTT effects on task orientation (TO) positively and CME effects on people orientation (PO) positively in the teamwork appraisal factors (TAF), respectively. And it confirms TA has stronger TO in Chinese workers, but has stronger PO in Southeast Asian workers.

Masa-Hiro Nowatari

Global Industrial Teamwork Dynamics in Malaysia—Effects of Social Culture and Corporate Culture to Teamwork Awareness—2/2

Research purpose is to verify how social culture and corporate culture effect into teamwork awareness (TA), respectively. Answerer is native employee on Japanese-owned local electrical plants in multi-racial nation Malaysia. Confirmation on TA difference caused by social culture bases on propagated religion in born country on each employee, and by corporate culture confirms as corporate attributes based on management cumulative effect (MCE). It clears that effect of corporate culture is stronger than social culture, and that corporate culture as social group process has been growing up glocalization (global-localization) while working time. This is second research related to Global Industrial Teamwork Dynamics (GITD) after first Chinese social survey. Propagated religions are Islam has Malaysia, Indonesia, Buddhism has China, Vietnam and Hinduism has India. Here, awareness concerning teamwork in daily production activity is caught as a group process in social psychology, and the internal structure is considered. Finally, the hypothesis is tested through statistical tests and discriminant analysis, principal component analysis.

Masa-Hiro Nowatari

Relaxed Flexible Bay Structure in the Unequal Area Facility Layout Problem

In this paper, relaxed flexible bay structure (RFBS) is introduced to represent the facility layout problem (FLP) with unequal area departments, which is a very hard problem to be optimally solved. The flexible bay structure (FBS), which is a very common layout in many manufacturing and retail facilities, makes the problem restrictive as departments have to be placed in parallel bays with no empty spaces allowed. The RFBS, however, relaxes the FBS representation by allowing empty spaces in bays, and therefore, it results in more flexibility while assigning departments in bays. In addition, departments are allowed to be located more freely within the bays, and they can have different side lengths as long as they are within the bay boundaries and do not overlap. The effectiveness of the new representation is shown using it in a hybrid probabilistic tabu search-linear programming (PTS-LP) approach. The comparative results show that improvements have been achieved by allowing partially filled bays using the RFBS.

Sadan Kulturel-Konak

Comparisons of Different Mutation and Recombination Processes of the DEA for SALB-1

This paper aims to propose comparisons of mutation and recombination processes of differential evolutionary algorithm (DEA) to solve a simple assembly line balancing problem in which the cycle time is given, in order to minimize a number of workstations (SALBP-1). Firstly, we apply general DEA to solve SALBP-1 which has following steps: (1) generating an initial set of solutions, (2) applying mutation, (3) recombination, and (4) selection process. To extend our general DEA, we present 5 different types of mutations and 3 recombination processes to enhance the search capability of DEA. From the computational results we can conclude that the proposed heuristics can find 100 % optimal solution out of 64 test instances which is better than the algorithm proposed in the literature.

Rapeepan Pitakaso, Panupan Parawech, Ganokgarn Jirasirierd

An Exploration of GA, DE and PSO in Assignment Problems

The optimum solution of assignment problem might not be found by using exact method for a large size assignment problem. The heuristic methods that will take acceptable time should be introduced to solve the problem. The common and well-known methods that are used in this study are genetic algorithm (GA), differential evolution (DE), and Particle Swarm Optimization (PSO). The goal of these three algorithms is the best solutions with appropriate time. We believe one of these three algorithms stands out from the others. We will focus on the best solution and shortest time consuming. In this study, we will classify our study into 3 parts. Firstly, we investigate similarities and differences of each heuristic. Secondly, test our theory by using the same assignment cost matrix. Finally, we compare the results and make conclusions. However, different problem might get different results and conclusions.

Tassin Srivarapongse, Rapeepan Pitakaso

Backmatter

Weitere Informationen

Premium Partner

    Bildnachweise