Advances in Sustainable and Competitive Manufacturing Systems

In this paper, the design and development of productions systems is discussed. The role of production system is investigated as a part of life cycle of products as well as one of the players, an evolving entity fulfilling the strategic goals of a company. These two are then combined to discuss on how they effect on design, development, and operation of production systems. The study focuses on the flow of material, i.e., the transformation of raw material to finished products as well as the flow of information related to the realization of the products. Simulation of production systems is discussed on how it can be used to enhance the daily operations and investigating the alternative future solutions. Finally, the issues discussed in this paper are explained on how they can be utilized in university level education in engineering.

For many component sub-systems which make up the individual elements of a larger product system, the optimization of their performance in the system becomes more difficult through design modifications and/or manufacturing process improvements alone. The authors argue this can be improved if adequate field performance data has been fed back to the early stages of the product lifecycle. This paper presents a framework for an inclusive lifecycle approach to optimizing product performance through the effective use of field experience and knowledge to improve the design and manufacturing of sub-systems. The problem is presented alongside a taxonomic and captious review of literature of relevant subject areas, followed by a case study using wind turbine sub-system components as a basis to support the investigation. A framework is then developed through the combination of systems thinking and continuous improvement tools, applied to the conventional product lifecycle. The findings of the investigation indicate that sub-system performance can be improved through the accumulation of knowledge fed back to the design and manufacture stages of the product lifecycle using information from in-service product performance. The approach would be useful to practitioners and academics with an interest in applying an inclusive and holistic approach to product lifecycle management. This framework is particularly useful for companies that produce and/or operate systems whose sub-systems are manufactured by different suppliers.

Energy and resource efficiency is becoming an important factor in manufacturing, helping to avoid bottleneck situations in times of sparse resources. Sustainable products are promising new improvements and are attracting customers more than ever. In the automotive industry, the assessment of the environmental impact of a product in use phase is already common practice. In contrast, the manufacturing phase often lacks detailed data. Product and process designers can benefit from reference data serving assessments, whether improvements were achieved compared to theoretical average values. This is most relevant for complex manufacturing processes like injection molding with non-linear relationships toward the degree of optimality. The paper presents a systematic approach for realizing and using a knowledge base facilitating advanced product/process design decisions. This knowledge base can be used to verify energy related hypothesis, enabling to create design rules and identifying weak points in processes. With an increasing database, energy consumption of similar new/planned products can be forecasted. The approach facilitates to assess decisions and investments in efficiency measures from an ecological and economical point of view, also serving as basis for detailed internal and external reports. It was applied and validated for production of plastic parts in the automotive industry.

Disassembly is required for product repairing, component reusing, and material recycling in the product lifecycle. Existing research in the area mainly focus on the complete disassembly for process planning algorithms, operation evaluations, and guidelines of product design. This paper introduces the evaluation of product selective disassembly planning. Cost measures are introduced in the evaluation of product disassemblability. Operating tools and tool changes are included in the analysis. A hybrid product representation is proposed to improve the existing method for the product selective disassembly analysis. The proposed method is verified using a case study.

This paper deals with a new risk management methodology covering the entire product lifecycle. Since, no complex and lucid methodology involving all product lifecycle phases has ever occurred. Currently, not all phases are covered or different risk management methods are used for single phases. The proposed methodology copes with two types of risks which may occur during the life-cycle. Predictive risk are the first type and incident investigation the second. At the beginning of an each phase, all possible risks entering the process are considered. These risks are taken into consideration during the entire cycle. Nevertheless, some risk may stay undiscovered and impact. Then incident investigation starts in order to identify risks. The identified risks are treated and considered. Generally, it can be said the methodology makes a closed and never-ending circle of risk management. It is a part of universal process improvement.

In recent times, in the field of manufacturing, due to the continuously changing market demand, the concept of reconfigurable manufacturing systems emerged. This requires a process plan along with the machinery (kinematic configuration) to produce the part. When the product is changed, consequently the process plans and the kinematic configurations change accordingly as well. The change in the basic machinery seriously affects the overall profit of the industry. This paper presents an approach to minimize this cost while still providing a suitable process plan for the associated kinematic configuration. The algorithm to implement this approach is also the part of this paper. A sample part is taken as an example to illustrate the use of this approach. The results are compared with the existing data for the part. The applicability, uses and future trends have been discussed in conclusion.

Open Architecture Product (OAP) offers public interfaces beyond the individual product. The interface can be shared by other products to enrich the product function and adaptability. Adaptable design (AD) meets OAP objectives for different requirements through modification or adaptation of product modules in the product lifecycle. The product adaptability is achieved by adaptable design, adaptable modules and platforms, and interfaces. This paper introduces a miniature electric vehicle with open architecture developed using AD. The electric vehicle consists of common platforms, customized modules, and user personal components. The vehicle developed can easily meet the individualization of users’ requirements and requirement changes in its lifecycle.

Ergonomics is a science that is focused on the study of human fit, and decreased fatigue and discomfort through product design. This science is extensively applied to various furniture designs in home and office taken into consideration how the furniture is designed to fit to its users. This research work concentrates to problems faced by students at Shah Jalal University of Science and Technology, Sylhet, Bangladesh, who are using tabloid chair in their day to day classroom environment. The objective of this research is to identify ergonomics viewpoints by using tabloid chair for sitting in classroom environment and its associated limitations or problems. To find out the limitations or constraints in using the tabloid chair, a survey on 160 university students were carried out by using the chair for sitting position in the classroom more than 1 h per day and accompanying body discomfort was critically investigated. The outcomes from this survey showed that body discomforts are found at elbow, back, neck, and thigh of 46, 41, 31, 33 students respectively. Based on the anthropometric data taken from those 160 students, an updated tabloid chair was designed and developed and presented in this paper. The tabloid chair as fabricated considering the proposed ergonomics design was also validated with respect to its materials and overhead costs.

Low-value hardwoods are not used to its full potential because they possess a challenging economic proposition to entrepreneurs in search of profit. In particular, high extraction and processing costs for low-value and underutilized hardwoods are not offset by products that carry a high enough value to customers to assure favorable economics. Thus, the low-value biomass is not used sufficiently in U.S. forests to support sustainable quality forest management practices. Furthermore, economic opportunities are lost for rural economies and forest landowners. The main purpose of the project described is to design the manufacture of a high value product from low-value hardwood timber achieving positive economics, thereby assuring the efficient and effective use of the resource. In particular, the project assesses the markets and the technical potential for manufacturing solid, finger-jointed edge-glued hardwood panels from low-value hardwoods. In fact, the technical feasibility of manufacturing edge-glued panels has been proven and is a major product of wood components manufacturers in the U.S. However, the use of low-value hardwoods for this purpose has not received much attention. This study intends to fill this gap by conducting an exhaustive analysis of secondary sources to assess raw material availability for such panels from low-value hardwoods. Also, appropriate processing routes to achieve competitive target prices while assuring positive economics are investigated.

Modern communication and radar systems, especially if used for space or defense applications, need signal sources having high spectral purity and ultimate frequency stability. Most current and future designs must also include some way of frequency tuning. Digital synthesizers and multipliers are the conventional electronic solutions to these challenges, but unfortunately, they suffer from increased phase noise. The idea in the present survey was to study the feasibility and performance of fundamental frequency microwave dielectric resonator oscillators (DRO’s) as a substitute to frequency synthesis. If atomic frequency standards (such as cesium clocks or hydrogen masers) are excluded, all resonator-type oscillators (quartz crystals, dielectric resonators, surface acoustic wave devices) are of the mechanical vibration type. Dimensional tolerances and constructional rigidity issues, particularly in the resonator element itself, are thus of vital importance. The sharpness of the resonance curve defines the frequency accuracy to a certain extent, and therefore, we need the highest possible quality factor of the resonator, which calls for uncompromised surface quality. Usually, the electrical performance of this type of component is ensured with some computer-assisted tools before manufacturing the first prototype. This research showed that it is useful to simulate also the manufacturing stages beforehand to be able to find solutions for possible bottlenecks in the production. One of the key findings of the computer aided manufacturing (CAM) simulations was the importance of utilizing the optimum combination of the milling tool path, tool diameter, and the stepover to maximize the Q-value of the resonator but keeping the production at a reasonable level.

This paper deals with the optimization of manufacturing and logistics processes with the support of progressive computer simulation approaches. It briefly discusses systems and tools developed at the University of Zilina, from the Laboratory of Intelligent Systems ZIMS, through the use of emulation and software as a service, to own computer applications based on Genetic Algorithms (GAsfoS, GAsfoS2), scheduling of custom production (SSEM) and metamodeling (SAGME). The alignment of developed tools is represented in the system OSMAP.

The realization of a short product-time-to-market is a key-challenge in the design of modern manufacturing equipment. Compression of lead-times for product design and manufacturing require a concurrent way of engineering. This implies that structural decisions about manufacturing-equipment need to be made when products are still under development. This introduces development risks; changes in the layout of production systems, due to late modifications in the product design, are inefficient for lead-time and cost. It is preferable that the production system can be designed in a ‘first-time-right’ fashion. Therefore, the architectural freeze of a manufacturing system is preferably pushed backwards in time to sustain modifications of the product design as long as possible. Reconfigurable Manufacturing Systems (RMS) have been developed for this purpose. With their modular structure, they can be integrated in a short period of time. Though this leaves more time for product development, it does not exclude the industrialization risks. Since configuration of equipment only works reliably if its process technology is well understood, it is needed that poorly functioning manufacturing processes are detected and addressed in an early stage. Only then, sufficient time is available for corrective actions to be taken. This paper presents a scientific framework to model the development of RMS. The method has the capability to uncover manufacturing risks during early development. In combination with RMS, the freeze of system architecture can indeed be pushed backwards in time. The method uses the ‘Structured Analysis Design Technique’ (SADT). The process risks, as outcome of the analysis process, are ranked using a Failure Mode Effect Analysis (FMEA) to determine the severity of their impact. It helps focussing on primary issues to be addressed. The method was applied to a true case; the development of a RMS for cell Phone lenses. The industrialization process may be considered successful. By application of this approach, engineers profit of a complete overview of what actions need to be taken and the effects if these actions are omitted. The method can also be used to inform higher management, to increase understanding of the cause and effect of management decisions related to manufacturing.

The on-going industrial trend toward production of highly complex and accurate part geometries with reduced costs has led to the emergence of hybrid manufacturing processes where varied manufacturing operations are carried out in either parallel or serial manner. One such hybrid process being currently developed is the iAtractive process, which combines additive, subtractive, and inspection processes. The enabler for realizing the hybrid process production is the process planning algorithm. The production time estimation for the additive process, namely build time, is one of the key drivers for the major elements in the algorithm. This paper describes a method for predicting build times for operation sequencing for process planning of the iAtractive process. An analytical model is first proposed, theoretically analyzing the factors that affect build times, which is used to help with the design of four test parts together with 64 sets of variations. The experimental results indicate that part volume, and interactions of volume and porosity, height and intermittent factor have significant effect on build times. Finally, the build time estimation model has been developed, which were subsequently evaluated and validated by applying a wide range of the identified influential factors.

Change in the order requirements usually leads to changes in the production system that tries to meet these requirements. As changes always incur costs and take time, it would be important to be able to estimate the impact of the order requirement changes on the production system. This would facilitate the estimation of the effort and cost needed to accommodate these changes. This paper presents a preliminary method for evaluating the impact of change. The approach utilizes the previously developed capability model and capability matching framework, in order to define, how well the current production system satisfies the new requirements and what needs to be changed. The approach examines the topic from three aspects: the compatibility of the existing production system to the new requirements; the relative effort entailed in making the needed modifications to the system and; the utilization (re-usability) of the existing system for the new requirements. The aim of the approach is to help the decision maker in choosing and prioritizing between different product scenarios, which require changes to the system.

The following paper is to introduce an approach to production process design based on Enterprise Resource Planning (ERP) standard and benefiting from UML (Unified Modeling Language) standard. The goal of the paper is to present methodology and tools for designing, optimization and implementation of manufacturing and service processes with unified language UML and ERP standards. The paper is organized in two main sections. In the first one MRP/ERP standard is briefly described and OMG-UML/RUP (Object Management Group-Unified Modeling Language/Rational Unified Process) is introduced. In the second a case study on company representing food industry is developed to present some examples of object-oriented modeling based on UML standard. The case study object is a company representing food industry, which makes manufacturing processes it performs really sensitive for health, safety and hygiene issues on one hand and cost efficiency on the other, resulting in necessity of holistic and multi criteria approach, provided by ERP standard application, necessary.

Failure Mode and Effect Analysis (FMEA) is a proactive tool used to identify, evaluate and prioritize potential weakness or failure modes in a given system. As with any methodology, familiarity leads to scrutiny. The more a particular method is utilized, the more questions are asked and inevitably the more weaknesses are found. The FMEA is no different. From its early stages of development with NASA, the FMEA has evolved into an industry accepted methodology used across varied fields from pharmaceutical, to militarily to automotive. It is this widespread use which has exposed the FMEA to various questions and critics. This paper will discuss a body of research which aims to dissect the FMEA process with particular focus on the perceived weaknesses documented in the available literature. Following a full and detailed literature review, the next phase of this research work will be to identify an optimum FMEA solution for use in the Electronics Manufacturing industry. All findings, recommendations and modifications will be trialed and proven in a high volume automotive electronic manufacturing environment across a number of global manufacturing sites.

Currently, the development of complex automated production stations will almost be impossible without the use of computer aided simulation. So as to increase the reliability of such simulations, the simulation models must depict the reality as much as possible. Including the physical properties of the elements in the models allows for an increase in realism of the simulation. One of the aspects in this field is the pneumatic behavior of pneumatic drives. Using physics based simulation approaches of the video game industry, a real-time assembly station simulation for the virtual commissioning considering the pneumatic behavior of the pneumatic drive was developed. This paper presents how the underlying model was developed and the extent to which different simulation factors have an influence on the pneumatic behavior.

Simulation in industrial environments has been recognized as a valuable approach for capturing the different characteristics and complexity of the dynamics in industrial processes. However, there is a clear need for spreading the use of simulation tools in manufacturing companies and for simplifying the simulation modeling process. In fact this process is still highly demanding in terms of the specific skills of the modelers and in terms of the time needed to develop models that are effectively useful in actual manufacturing systems. The slow modeling process often precludes the use of simulation for facing the operational problems that rise in the day-to-day operations. This paper presents a brief overview of the use of simulation tools in manufacturing, and focus on the development of an innovative simulation framework based on libraries of components and modules. This framework will contribute for reducing the learning curve in developing simulation models for manufacturing and logistics systems. The requirements and advantages of this novel modular modeling approach are presented and discussed in the context of a case study that uses the SIMIO software for simulating the production and logistics systems of a generic footwear manufacturing system in Portugal.

In recent years, the importance of flexible solutions and new challenging requirements in the field of intralogistics has increased because of changeability in dynamic and uncertain environment. The Cellular Transport System that aims to cope with these new requirements provides an efficient way to increase the flexibility and changeability of intralogistics. In this paper, we propose a multi-agent simulation framework for Cellular Transport Systems that is an application of Swarm Intelligence to control the autonomous vehicles’ behavior. The paper discusses how we apply situated agent-based simulation as a tool for modeling and implementing a decentralized control of vehicle swarm. Furthermore, we aim to optimize the suitable number of vehicles used within a warehouse system. The simulated model provides an environment in order to study problems and performance issues of the vehicle operations.

A laser scanner is a popular sensor widely used in industry and mobile robots applications that measures the distance to the sensor on a slice of the plan. At the same time, simulation has becoming more and more used in industries and academia since it presents several advantages. It takes the building and rebuilding phase out of the loop by using the model already created in the design phase. Further, simulation time on testing is cheaper and faster than performing the multiple tests of the design each time. Besides, it is easier to measure some variables in simulation than in real scenarios. In this paper, a laser scanner sensor is modeled and implemented in a developed simulator that already has several other sensors and actuators models. The presented simulation reflects the laser model properties such as target color dependences, noise, limits, time constraints, and target angle functions. As a case study, the same scenario is assembled with real components on a conveyer belt and in simulation. Results from both approaches are compared and validate the proposed model methodology. As an example, a 3D object recognition task is addressed highlighting the developed realistic model. Further industrial and R&D implementations based on this sensor could be stressed in simulation before implementation.

The current fierce competition within the manufacturing industry throughout the world is a result of globalization and dynamic changes in the market. This new era within the production world requires shorter lead times, integrated logistics, capabilities regarding handling changes in product volumes and variety, as well as conformity to environmental rules and regulations legislated by governments and organizations. Apparently, the multitude of variables needed to solve problems complicates the decision-making process. In order to provide solutions for complex problem solving within production development which include many variables and a certain amount of uncertainty there is a need for robust decision making tools. Discrete-event simulation (DES) is one of the virtual tools that can be used as a support for decision-making for production related problems. The current paper addresses challenges which cause low utilization of DES in industry along with a framework for handling those challenges and performing DES projects in an effective and efficient way.

Machine Tools Assembly has being one of the most important industries in Taiwan for past few decades. Assembling a single modern CNC machine tool may take a few weeks or even months depending on factors such as the complexity of the machine structure, the supply of key components such as spindle, bed, coolant systems, and tool magazine, management of human resources, and the availability for required equipment or tools. The most costly resource for machine tools assembly is the space for assembly. At least an area of 15–20 m

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is necessary for a single machine and essentially the space will be occupied as long as the machine is completed. Besides this spatial problem, Taiwan’s machine tools manufacturers today also face serious unstable supply of the key components offered by outside suppliers. This study focuses on two important decisions faced by every Taiwan machine tools manufacturer: selecting the customers’ orders for assembly launch and determining the priority of the on-going assembly projects for allocating the limited resources like equipment and tools, and human forces. A discrete-event simulation model for a complicated machine tools assembly system considering the spatial problem and the quality issue of key components is developed to evaluate several rule combinations for making these two decisions. Simulation experiments are then properly designed and conducted under various system conditions for detailed investigation.

The aim of this paper is to present results of the project conducted in the manufacturing company in the furniture industry. The main objective was to automate the warehouse operation as much as possible and to minimize the number of staff in the store. The process was modeled using software FlexSim Simulation Software. The proposed solution reduces the number of used forklift trucks and warehouse workers through automatic insertion and retrieval pallet racking with stacker cranes. In addition, the range of the production hall to the storage area are transported by feeder roller (like the storage to the point of completion). All facilities have a chance for long-term use of their stock in the draft. They also allow for maximum cost savings by manufacturing company while maintaining full and accurate customer service and their satisfaction with the delivery of the warehouse. In the future authors want to develop a simulation model with respect to safety stock optimization and optimization of product location.

A real-world factory simultaneously adopting make-to-order (MTO), make-to-stock (MTS), and assembly-to-order (ATO) production strategies for its foreign and local customers is understudied. Foreign orders are more unpredictable and with long lead time where MTO is implemented. On the other hand, local orders are fulfilled by agencies that constantly place orders demanding short lead time. Therefore, for local orders, the factory implements both MTS and ATO strategies depending on the manufacturing lead time of the product. In an attempt not only to minimize inventory cost and work-in-process (WIP) levels, but also to fulfill customer demands by maximizing customer service level, an optimal safety stock policy must be implemented. In this study, a safety stock policy contain safety stock level and reorder point of subassemblies, manufacturing batch size, order review and release (ORR) mechanisms, as well as dispatching rules. This study conducts a two-stage simulation experiment to first evaluating performances of dispatching rules and ORR rules, and then using results from the first stage to further design several safety stock policies that will be evaluated in the second stage for the hybrid manufacturing system.

This paper describes the EMG30 mechanical and electrical modeling and its simulation resorting to SimTwo (Robot@Factory mobile robot competition official simulator). It is described the developed setup applied to obtain the experimental data that was used to estimate the actuator parameters. It was obtained an electro-mechanical dynamical model that describes the motor, its gear box, and the encoder. The motivation to model and simulate the EMG30 is the fact that it is an actuator worldwide popular in the mobile robotics domain, being a low cost 12v motor equipped with encoders and a 30:1 reduction gearbox. The Goal of this work is to provide more realism and new features to the Robot@Factory official simulator, allowing participating teams to produce and validate different robot prototypes and its software, reducing considerably the development time.

Using Fiber Reinforced Polymers (FRP) have become a fast growing matter in new construction structural components. First transport infrastructures, e.g., road and pedestrian bridges are built out of such components, today already made manually in manufactory workshops. The cooperative EC funded project, TRANS-IND—New Industrialized Construction Process for transport infrastructures based on polymer composite components, shifts from existing manual approaches to industrialization concepts. It targets a cost-effective integrated construction process that will enable the maximum capability of components for transport infrastructures using polymer based materials (carbon fiber, glass fiber, etc.) as well as to industrialize the whole construction process of the FRP components. This paper presents the different planning activities for the conceptual design of the off-site industrialization process and a detailed description of each planning phase and their related planning activities. First the paper surveys important theoretical basic approaches to define the fitting conceptual design of the off-site industrialization process. Further the infrastructure components to be manufactured and the required manufacturing processes are introduced. Subsequently for each infrastructure component, generic production structures are assigned and evaluated. The results are specific models of planned production areas, logistics as well as rough and final layouts for the factory.

Despite the high production rates required in the automotive industry, some small components are being produced manually in peripheral countries where the labor costs are lower than in the middle of the Europe. When the production must be highly flexible, new challenges are placed and, in these cases, some companies adopt intensive labor processes. This work is based on an industrial demand in order to become an intensive labor process in intensive technology process, minimizing human intervention (without removing it), increasing productivity ensuring the quality, and maintaining the high flexibility already achieved in the assembly process of drive systems for automotive windscreen wiper. The equipment developed uses intensive technology through automation systems, needing an operator who is responsible by the initial feeding process. After that, all the process is automatic. The production cycle time is reduced from 11 to 7 s and the quality is ensured. The equipment is very flexible, allowing to assembly 20 different kinds of sets for the same purpose, changing just the gig where the main component is assembled.

In a flexible manufacturing industry the production planner may need to make an updated description of the control strategy every day. The description contains all possible routing paths and is based on actual circumstances. It varies depending on, e.g., rebalancing due to market changes, scheduling of available operators, introduction of new parts, and rerouting due to a machine break down or planned service. A Part oriented Sequence of Operation (P-SOP) description language has been formulated to assist the production planner to be able to handle these flexible manufacturing scenarios. Multi-agents to control the manufacturing are automatically generated from the P-SOP description language. The P-SOP agent generator creates IEC 61131-3 PLC code that can be executed on standard PLC’s. An agent consists of a head, a communicator, and a body. The head and the communicator are the automatically generated part with a predefined interface against the physical body, e.g., the mechanical/electrical structure of a robot. This feature eliminates the need for an external expert in PLC programming. The head contains many small sub-sequences for all operations that are defined for the specific body. The purpose of the communicator is to communicate with surrounding neighbor agents to form a multi-agent system. The formulated language and the P-SOP agent generator has been successfully tested and evaluated in an industrial environment.

In many countries, economy without small and medium-sized enterprises (SMEs) can hardly be imagined—they offer more jobs than large-scale enterprises and significantly contribute to the economic success in many countries. The globalization pressure, social, economic, and political changes as well as technological innovations force SMEs to alter their organization and their market strategy. In order to survive current situations, SMEs need agile structures and speedy decisions. The following article deals with flexibility strategies and their application in industrial SMEs focusing on the measures of the internal flexibility. Measures like working time models, short time work, job rotation, job enlargement, profit/cost/investment center as well as team and group work particularly belong to this. This article offers an insight into the practice of the internal flexibility of SMEs, indicates which goals are pursued with those measures, which constraints and drivers during implementation and realization are experienced and how satisfied the enterprises are with the measures. Finally, it goes into detail about the application pairings.

In a ubiquitous manufacturing environment, different devices such as radio frequency identification (RFID) technology are used to collect real-time data. Additionally, data is used by different enterprise information systems for supporting managerial decision making. Since data sources from applications and devices are characterized by multiple types of heterogeneities such as communication channels, blinding methods, and developing environments, the difficulty in managing heterogeneous data sources is greatly increased. This paper proposes an innovative Application Information Service (AIS) that serves as a middleware for information exchange in between different applications. The AIS possesses several key contributions. Firstly, AIS provides a centralized platform to manage distributed heterogeneous data sources so as to reduce the data duplications, increase consistency, and accuracy. Secondly, it combines software agent technologies with service-oriented architecture (SOA) so that services are capable of accomplishing tasks in an autonomous way without human intervention. Thirdly, agent-based service-oriented architecture paradigm is proposed to cultivate a collaborative environment to integrate different data sources as well as third party application providers.

Enterprises operate in an increasingly turbulent environment. In order to stay competitive, more and more complex decisions have to be taken. Production systems are not relatively closed systems any more, but often part of supply networks with a high number of resulting interfaces. Planning and operation of factories are tightened together. At the same time virtual reality, as the mean of modern factory planning, merges with the real world. The processes of planning and operation are supported by a variety of software tools. With reference to operation of enterprises a lot of effort is put in integrating the different tools, while there is a deficit concerning the integration of factory planning tools. Therefore, the paper will look at the current state of interoperability in factory planning. The requirements and use cases of data exchange between tools for factory planning as well as other enterprise software, are discussed. Thereby, challenges and opportunities resulting from better hardware performance, faster communication networks and a wide range of new types of devices are listed. The consequences of trends like cloud computing and big data are classified. Conclusions are derived for possible architectures of software systems. The role of the Digital Factory in the whole development is investigated.

The use of computer technology for process planning was initiated four decades before. Since then, there has been a large amount of research work carried out in the area of Computer Aided Process Planning (CAPP). One of the reasons for this is the role of CAPP in reducing throughout time and improving quality. Now a day’s due to dynamic market and business globalization, CAPP research faces new challenges. In this article an attempt is made to provide a comprehensive review on CAPP based on features, knowledge, artificial neural networks, Genetic Algorithms (GA), fuzzy set theory and fuzzy logic, Petri Nets (PN), agent, internet, STandard for the Exchange of Product data (STEP) compliant method, and Functional Blocks (FB) technologies for last five years (2008–2012). The design of paper includes a brief introduction of CAPP and its approaches, methods/technologies of CAPP, snap shot survey of previous research work on CAPP, survey of last five years research work on CAPP, then finally a suggestion for future and conclusion.

New generations of collaboration software services supporting Networked Enterprises and Virtual Factories, based on the easily accessible communication facilities, are developed in order to foster the globalization of the business. Still the Interoperability Problem appears to be a bottleneck for their effective functioning. The solution of the problem is of a major importance for their wide adoption. The paper is provides an insight of how the problem was examined and addressed in the project ADVENTURE’s Data Provisioning and Discovery services. This work is part of the FP7 EU project ADVENTURE (ADaptive Virtual ENterprise ManufacTURing Environment).

In the manufacturing industry, customers’ requirements vary all the time, a way that to increase capacity and add capabilities of factories without investing in new infrastructure becomes essential. An advanced information management system to share valuable information and knowledge among collaborative factories is demanded. The concept of “Cloud” can encompasses subscription-based or pay-per-use service that, in real time over the Internet, extends factories existing capabilities. Cloud Storage can be used to share data is a flexible manner. With such perspective, a cloud-based Virtual Factory Information System (CloudVFIS) design is proposed in this research. This new system will provide a concrete tool for SMEs (Small and Medium Enterprises) to realize the integration of factories based on the idea of Virtual Factory. In this paper, the Cloud VFIS architectural framework and the cloud storage in manufacturing management are illustrated.

In our globalized world, small- and medium-sized enterprises in the manufacturing domain face a highly competitive environment. They are subject to various challenges, such as very short product life cycles and a strong price competition with companies from low-cost countries. To remain competitive in such an environment, new forms of collaborations, like Virtual Manufacturing Enterprises, are required. An essential part of virtual organisations is data provisioning. Thereby, data from various sources like factories’ ERP systems or data provided by sensors need to be processed and stored. In this context, data storage is a crucial architectural element that influences both functional aspects and competitive aspects, especially costs, of Virtual Manufacturing Enterprises. For realizing Virtual Manufacturing Enterprises with low up-front investments, the application of new technologies, such as Cloud Computing, is required. For storage of information in databases, Database as a Service offers from the Cloud can be exploited. However, since there is a huge amount of providers acting on a non-transparent market, it is difficult to find appropriate “Database as a Service” offerings. To overcome this problem, we provide a criteria catalog for the selection of providers and their services. Further, we show how different offers, which at the first glance look very similar, could cause very different expenses. With our work, we simplify the selection and evaluation of Cloud storage providers and provide an evaluation of current Cloud storage service offers.

Small and medium manufacturing enterprises (SMMEs) face many difficulties when introducing their manufacturing information systems because of realistic limitations such as the large initial investment needed to buy the system, the burden of maintaining staff to operate it, and continuous payment of maintenance costs, etc. However, most systems are not used properly due to the characteristic difference between SMMEs’ shop-floors and their functions, the lack of understanding concerning their many complex functions, and so on. To overcome the situation, we propose an infrastructure to support the construction of the individualized manufacturing information systems for SMMEs. The infrastructure consists of a Manufacturing Application (MfgApp), Plug-and-Play (PnP) Platform, and a Manufacturing Application Store (MfgAppStore) such as Apple’s business model. The MfgApp is a small-sized application software to treat specific manufacturing tasks and is performed only on a PnP Platform. The PnP Platform includes a PnP Developer which provides developers of MfgApps with a development toolkit containing a common database, user interface, and so on, and a PnP Browser which manages and executes MfgApps. The MfgAppStore is the online marketplace on the Internet to register new MfgApps that have passed the peer review process and are made available to purchase by users of SMMEs. Each SMME is able to construct its own manufacturing information system using a PnP Browser with MfgApps selectively downloaded from the MfgAppStore. We are applying the prototype infrastructure to some SMMEs of the mold industry to validate the proposed concept.

This research provides mechanisms that facilitate to monitor and manage of Virtual Enterprise (VE) collaborative business processes in an efficient and effective way. First, it shows a self-contained process monitoring tool specification that contains the following main functionalities: events capturing from a workflow engine, business activity monitoring, process analytics and monitoring rules definition and evaluation. An interactive user interface layer in the form of dashboard is then highlighted within the scope of this research with the objective to monitor the VE operational processes. The dashboard will be the integration platform for a set of components that allow the establishment and operation of VE successfully. This platform enables a seamless integration of business processes and provides an end-to-end ICT solution among the VE member organizations. The work presented in this paper is developed within the scope of the European Commission NMP priority of the Seventh RTD Framework Programme for the ADVENTURE (ADaptive Virtual ENterprise ManufacTURing Environment) project.

Manufacturing industry is extremely broad and plays a key role in the global economy. However, there are rapid and continued technology changes due to rapid response required by the market challenges and customer demands, therefore the manufacturing industry needs to keep up with market demands at all the times. Reconfigurable manufacturing systems will enable manufacturers to produce a variety of goods within a short time and improve sales. Reconfigurable Machine tools (RMTs) together with Reconfigurable Manufacturing Systems (RMSs) are the new invention introduced in 1999 at the Engineering Research Center for Reconfigurable Manufacturing Systems (ERC/RMS). This paper presents the conceptual development of modular machine tools, by selecting and compiling a list of modules available commercially off the shelf. The machine tool is developed in such a way that it can be configured accumulatively in terms of degrees of freedom, to accommodate different reconfigurations of machine structures. As the modules can be assembled in different ways to create different types of tools capable of performing a variety of functions using the same hardware and software, depending on demand, one should be able to increase or decrease the number of degrees of freedom.

Process industries are highly automated and energy intensive. They produce considerable share of greenhouse gas (GHG) emissions. In these industries, automation and related controls of operations in different layers of production from process level instrumentation to distribution level scheduling and planning have been implemented in separated layers with few respects to sustainability. It is clear that without consideration of sustainable factors in Enterprise Wide Operations holistically; predefined targets of Green Production for industrial operations are unachievable. Substantial requirements for Green Operations rely on the establishment of suitable platforms, tailored to achieve Enterprise Wide Sustainability. This paper tries to model and conceptualize an integrated automation platform for green operations of process industries, including production and scheduling.

Starting-up production machines is a complicated task and takes a substantial part of time and expenses. Especially, in the field of reconfigurable machining systems (RMS), where changes in the machines occur regularly, a short start-up phase is essential. Many activities, which are necessary during the start-up can be automated. Among them are the configuration of control- and field-bus systems, user interfaces, and industrial automation devices, as well as the extensive testing of functions. In reconfigurable manufacturing the concept of mechatronic modularization leads to new system boundaries. As a result, RMS are composed of diverse mechatronic modules (MM) which contain mechanical and electrical components as well information technology. This paper presents an approach to automate the start-up of a RMS by applying a machine-internal service-oriented architecture. Moreover, a reference platform is presented, which can be used for research on the automatic generation of start-up procedures for RMS systems. Modules contain not only a range of mechatronic functions, but also additional software and Web-Services, which support the automatic start-up of a machine. Internal Web-Service communication is handled by a Service-Bus whose communication is tunneled through an automation-bus system. Thus, deterministic real-time communication can be combined with flexible Web-Service communication for the configuration and set-up of MM. Moreover, every MM is equipped with a real-time simulation model for mechanical and electrical parts and a database to store module specific data like CAD models, module descriptions, and software components. The functionality for configuring MMs and the start-up sequence generation for the machining system is provided by an internal configuration system based on Web-Services. Finally, a RMS system can be automatically put into operation by means of the configuration system which derives and executes an automatically generated start-up sequence.

This paper aims to explore the literature related to modularity in an enterprise in order to apply the idea of modularity into the business services context. The paper design follows an adductive logic beginning with the construction of a theoretical pre-understanding. Streams of literature that are applied are service marketing and operations and modularity research. Special attention is paid to some of the modularity dimensions such as in services, organizations, and customer interaction to build business competitiveness. To stay competitive, enterprises must apply systems or use principles that not only produce their goods with high productivity, but also allow for rapid response to market changes and consumer needs. A new business capability that allows for quick production launch of new products, with production quantities that might unexpectedly vary, becomes a necessity. Reviewing literature of modularisation of manufacturing products and semi- structured face to face interviews with some of the South African press tool enterprises provided rich data for setting up background for further research. The paper shows how businesses can use modularisation to meet customer demands and product mix, cost efficiently, and flexible.

Due to the rising demand in efficiency and sustainability in commercial aviation, aircraft manufacturers increase the usage of high performance, lightweight materials like carbon fiber reinforced plastics (CFRP). These materials pose new challenges to manufacturing processes concerning cost-effectiveness and quality requirements. To meet these challenges the Institute of Structures and Design within the German Aerospace Center (DLR) designed a flexible robotic manufacturing cell at the Center for Lightweight Production Technology (ZLP) in Augsburg. The multifunctional cell (MFZ) can integrate processes for production and inspection on an industrial scale. Due to large workpieces like fuselage components or wing skins and low production quantities, workshop space, and investment cost are major concerns for effective CFRP production. The large size of the cell (30 × 15 × 7 m) demands a highly reconfigurable space. The platform is composed of five ceiling mounted robots on a gantry like machine frame and may be divided in smaller independent cells. The multifunctional cell will improve the understanding of requirements of future production processes for lightweight components by providing a highly flexible platform on an industrial scale.

Electric discharge machining (EDM) is commonly used to machine precise and tiny parts when conventional cutting methods face difficulty in meeting productivity and tolerance requirements. Die-sinking EDM works well to machine micro-parts and perpendicular walls of die and molds, whereas EDM drilling is excellent for machining deep and narrow holes regardless of material hardness and location. However, EDM electrode wear is rapid compared to conventional cutting and makes it difficult to control the electrode feed and machine precisely. This paper presents an efficient method to estimate electrode wear through a hole pass-through experiment while a stochastic method is adopted to compensate the estimation model. To validate the proposed method, a commercial EDM drilling machine was used. The experimental results show that the electrode wear amount can be predicted acceptably.

Atmospheric pressure plasma polishing (APPP) is an efficient method to produce damage-free ultra-smooth surfaces, due to its chemical nature. APPP works intelligently on distinguishing surface micro-topographies, thereby realizing diverse reaction rates on different surface morphologies. Since the convex surface structures are always removed faster than the concave structures by dry etching process, the whole surface roughness can be reduced further to form ultra-smooth surfaces. Quantum chemistry simulation of two groups of models has been utilized to prove the conclusion in theory. Afterward, practical machining experiments have been conducted, in which the sample is detected every 40 s by atomic force microscopy to testify the decrease of surface roughness. Experimental results accord well with theoretical simulation. The machined sample is also detected by scanning electronic microscopy and nano-mechanical test system. The mechanical properties are demonstrated to be improved by APPP process, especially the residual stress is reduced by about 4.2 GPa after 60 s machining. The micro-topography is also indicated more regular, and finally reaches below Ra 0.5 nm surface roughness.

Conventionally, industrial robots are programmed in special proprietary languages. With the growing integration of industrial robots into PLC controlled machines and manufacturing lines, programming of industrial robots is done in tight relation with PLC controlled devices. In order to reduce engineering complexity as well as training effort for service personal, machine builders, and line integrators request more and more robot programming directly in a PLC language. The PLCopen working group motion control therefore worked out a specification for coordinated motion control, which is also applicable to industrial robots. However, some important details for the implementation are kept free for the manufacturer of controllers and robots. Some other aspects relevant for state-of-the-art industrial robots are not addressed at all. In order to optimally utilize the capabilities of industrial robots, some extensions, and adaptations are necessary. This article discusses the related aspects and describes an experimental implementation.

The IEC 61508 standard recognizes the programming languages defined in IEC 61131-3 as being appropriate for safety-related applications, and suggests the use of static analysis techniques to find errors in the source code. In this context, we have added a semantic verification stage to the MatIEC compiler—an open source ST, IL, and SFC code translator to ANSI C. In so doing, we have identified several issues related to the definition of the semantics of the IL and ST programming languages, as well as with the data type model defined in IEC 61131-3. Most of the issues are related to undefined semantics, which may result in applications generating distinct results, depending on the platform on which they are executed. In this paper we describe some of the issues we uncovered, explain the options we took, and suggest how the IEC 61131-3 standard could be made more explicit.

The paper presents neutral open function blocks to implement programmed data access logic into controllers programs. The paper proposes an approach similar to the successful IEC MotionControl function blocks technology, which has been defined for neutral programming of axis control. In the same way, neutral access blocks could be programmed for data access and recording, and specific brand controllers would implement them and use to build the manufacturing program. A prototype implementation is presented for CAD/CAM/CNC environments to automate manufacturing processes data access and recording in order to support services of production activity supervision, manufacturing data traceability-recording of relevant information of manufacturing processes for future review in case of fault-etc.

The success of the textile industry largely depends on the products offered and on the speed of response to variations in demand that are induced by changes in consumer lifestyles. The study of behavioral habits and buying trends can provide models to be integrated into the decision support systems of companies. Data mining techniques can be used to develop models based on data. This approach has been used in the past to develop models to improve sales in the textile industry. However, the discovery of scientific models based on subgroup discovery algorithms, that characterize subgroups of observations with rare distributions, has not been made in this area. The goal of this work is to investigate whether these algorithms can extract knowledge that is useful for a particular kind of textile industry, which produces highly customized garments. We apply the CN2-SD subgroup discovery method to find rare and interesting subgroups products on a database provided by a manufacturer of custom-made shirts. The results show that it is possible to obtain knowledge that is useful to understand customer preferences in highly customized textile industries using subgroup discovery techniques.

The paper deals with modeling and improvement of diagnostic processes. The aim is to develop a new methodology which could be used as a tool for modeling and improvement of diagnostic processes. This paper is firstly focused on evaluation of SPC methods and their possible usage for modeling, measurement, controlling, and following improvement of diagnostic processes. Seven basic methods were evaluated according to few basic criteria which are important in the field of diagnostics. The Ishikawa diagram was chosen as one of the suitable tool and was used for setting of Key Performance Indicators. Then, the results were applied on specific diagnostic process and their behavior was analyzed and evaluated. The research was mainly focused on time and quality measurement because they play very important role in the final product evaluation and tell us which parts has to be optimized.

In recent times, impeller machining has posed a new challenge to engineers due to demand from aerospace, automobiles, and ship building industries. Various methods are introduced by researchers in machining impellers by using 5

-

axis milling machine; this is because the 5

-

axis method has the flexibility of tool orientation to machine the extremely twisted surfaces between the blades of impellers. When impellers are machined by a 5

-

axis machine, the time consumed is very long and the process creates a bottleneck in the manufacturing line. The problem causes increase in the manufacturing lead time and manufacturing cost. To overcome the problem, this paper introduces a new method of machining impellers by integrating 3

-

axis and 5

-

axis machine. This paper opens up a new field in impeller machining with the aim to reduce rough

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cut time. The results show that by applying this strategy, total machining time of an impeller can be reduced significantly up to 17 %.

Electrical discharge machining (EDM) drill is a kind of EDM processes to machine deep, micro sized holes of hard machining material. Since it works regardless of materials strength or stiffness, it is known that EDM drilling is effective than conventional drilling for the micro-drilling. The accuracy of a machined surface is determined by electric discharge parameters. Thus, in this study a EDM-drilling plan with the experiment of design (DOE) is set up to analyze the characteristics of Pass-Through Holes in EDM-drill and then the relationship between the four major discharge parameters and machined hole accuracy is addressed in terms of hole diameter and surface roughness. Finally, the tendency in each parameters of EDM-drilling is studied with average response value (ARV).

In this work, the interdependencies of different metal cutting parameters are examined. In order to ensure competitiveness in the field of manufacturing, the quality, productivity and costs of the work must be in optimal balance. The parameters affecting the end result of a metal cutting process form a complex web of interdependencies. In this work, graph-based modularity analysis is applied in order to impose a structure on the network of parameters. This allows the identification of the parameters that are to be used in more thorough examination of the individual cases. Combined with an understanding of the graph topology such as parameterized relationships between different factors, this enables powerful heuristic tools such as expert systems to be created.

Engineered components must satisfy the surface texture requirements and traditionally surface roughness (arithmetic average, Ra) has been used as one of the principles methods to assess quality. Surface roughness is a result of the cutting parameters such as: cutting speed, feed per tooth and the axial depth of cut, also the tool’s geometry, tool wear vibrations, etc. Moreover, the surface finish influences the mechanical properties such as fatigue behavior, wear, corrosion, lubrication, and electrical conductivity. The research reported herein is focused mainly on surface roughness and power consumption analysis of an austenitic stainless steel milled in a dry cutting environment. The experiments were conducted on a Siemens 840D Bridgeport Vertical Machining center 610XP2. The selection of this workpiece material was based on it’s widely applications in cutlery, hardware, surgical instruments, industrial equipment and in the automotive and aerospace industry due to its high corrosion resistance and high strength characteristics. The results show that selection of a careful combination of cutting parameters can achieve low values of surface roughness and power consumption instead of changing the cutting parameters individually.

During the rotor blade bearing assembly of wind turbines three bearings, which have a diameter of several meters, are bolted to the rotor hub with hundreds of bolts. Although the introduced preload force on these bolts should be subjected to only minor deviations, the tightening process is performed manually despite of its high labor intensity. To ensure a reproducible quality of the bolt connection and to increase the efficiency of the assembly process, an adaptive automation solution with viable and flexible automation strategy has been developed. This automation allows for an adaptation to different types of wind turbines and a compensation of even larger tolerances of the components. Due to the integration of sensors and actuators in a newly developed robot-guided bolt tensioning tool, process variables are recorded and a response to errors by adjusting process parameters is possible. As a result, the tightening process is carried out automatically and the unreliable sensitivity of employees is replaced by an intelligent tensioning system.

Today, the dynamic market requires manufacturing firms to possess high degree of adaptability and flexibility to deal with shop-floor uncertainties. Specifically, targeting SMEs active in the machining and metal cutting sector who normally deal with complex and intensive process planning problems, researchers have tried to address the subject. Among proposed solutions, Web-DPP elaborates a two-layer distributed adaptive process planning system based on function-block technology. Function-block enabled machine controllers are one of the elements of this system. In addition, intensive reasoning based on the features data of the products models, machining knowledge, and resource data is needed to be performed inside the function blocks in machine controller side. This paper reports the current state of design and implementation of a knowledge-based operation planning module using a rule-engine embedded in machining feature function blocks, and also the design and implementation of a common interface (for CNC milling machine controller and its specific implementation for a specific commercial controller) embedded in the machining feature function blocks for controlling the machine. The developed prototype is validated through a case-study.

To face globalization challenges, today manufacturing companies require new and more integrated monitoring and control solutions in order to optimize more and more their production processes to enable a faster fault detection, reducing down-times during production, and improving system performances and throughput. Today industrial monitoring and control solutions give only a partial view of the production systems status, what compromises the accurate assessment of the system. In this scenario, integrating monitoring and control solutions for secondary processes into shop floor core systems guarantees a comprehensive overview on the entire system and its related processes since it provides access to a greater amount of information than before. The research currently done under the scope of Self-Learning Production Systems (SLPS) tries to fill this gap by providing a new and integrated way for developing monitoring and control solutions. This paper introduces the research background and describes the generic SLPS architecture and focus on the Adapter component responsible for adapting the system according to current context information. The proposed Adapter architecture and its core components are introduced as well as the generic Adaptation Process, i.e., its “modus operandi” to face context changes. Finally, one of three distinct business-case scenarios is presented to demonstrate the applicability of the envisioned reference architecture and Adapter solution into an industrial context as well as its behavior and adaptive ability along system lifecycle.

For an enterprise, the forecast of order quantity for a company affects the cost and the balance of production capacity. Many traditional time series forecasting technologies, such as Moving Average and Exponential Smoothing methods, are popular used to forecast order quantity in the field of Industrial Engineering and Management. Recently, machine learning methods in the field of Artificial Intelligence (AI) have also been used for prediction, among them including Artificial Neural Network (ANN) and Fuzzy Neural Networks (FNN) approaches. In this study, real treadmill part order quantity data are used to compare the forecasting efficiency of the above-mentioned four methods with methods which are combined time series and AI methods.

In five-axis milling of 3D free form surface, determination of instantaneously changing cutter workpiece engagement for supporting force and surface quality prediction is still a challenge. In order to predict cutting force accurately, precise geometric information on cutter workpiece engagement is very important. Solid model and discrete model are the most common method used to predict the engagement region. Both methods give the result with the accuracy as the tolerance set in the beginning. However, the methods are suffering with the long computational time. This paper presents a new simple method to define Cutter Workpiece Engagement between flat-end cutter and free form workpiece surface. The engagement is calculated by using a combination of discretization and analytical method. Despite workpiece is discretized by normal vectors, but there is no calculation to check the intersection between cutter and normal vector. They are only used as the reference to define the shape of the surface at every Cl-point, mathematically. The engagement point is obtained based on predicted surface shape and tool orientation at instantaneous location. The formula were derived and implemented in a computer simulation. The program simulation can generate instantaneous cut shape and its size. To ensure the accuracy of the developed method, it was tested by compared the depth of cut generated by the program simulation with the depth of cut measured in Unigraphic. A test on sculptured part surface and workpiece surface was performed. The result indicates that the proposed method is very accurate.

This work proposes the application of Case-Based Reasoning (CBR) to build a knowledge base system for seeking and providing solutions for non-conformances that take place in the aluminum extrusion process. CBR is an important area of Artificial Intelligence (AI) that is used to solve problems based on the knowledge accumulated previously from known scenarios, providing a solution to both recurrent and new problems. The CBR cycle is characterized by having four stages known as: retrieval, reuse, revision, and retention. These stages interact with the knowledge base in order to seek one or more solutions to the problem. The steps for the development of the relational model of the knowledge base according to CBR are as follows: (a) identification and classification of the non-conformances, (b) information gathering of situations that result in non-conformances, which include: records of non-conformances, experience of operators with non-conformances, literature on non-conformances in the aluminum extrusion process, and (c) the structure definition for the diagnosis of cases of non-conformance and support in decision-making. The final step consists in storing the cases in a relational database, which will correspond to a knowledge base. New cases may be added in the knowledge base, as they occur. The structure of the cases in the knowledge base will be important for its provision for decision-making in the aluminum extrusion process. In a further work it is intended to implement a web-based distributed system to support the inclusion of new cases (that may occur in different geographic locations and company conditions) as well as a fast search for solutions to non-conformances that occur in the aluminum extrusion process.

Many definitions of logistic management exist, but some of them are connected with the transport-warehouse chain, that includes obtaining raw materials, their processing, and selling. The environment, in which the company exists is also important. This is the reason why the optimization in a company should be made having in mind those aspects. The modification and optimization process in a company should include changes in its environment. The question is how long it takes for the company to adapt. Changes can be not significant in certain moment, but with the time they can have large influence on the company. It is not easy to recognize the size of the impact while consequences can be serious for the company. If the changes are recognized quickly, the company can conquer the difficulties by adaptation or can make changes in their processes. Sometimes the situation is not so simple, for example when the changes are detected too late or they require changes in management system. Improvement of the system can take a lot of time, i.e., year or more. This time would be shorter, if the system would change from itself, then the improvement of the system could be not so tedious and so consumptive of time. This is possible by implementation of elements of artificial intelligence in the system. Therefore the authors suggest a new concept of transport management, with use of an intelligent hybrid system, which adjusts to the current economic situation without updating or changing the management system and thanks to it the company can quickly replay with no outlay. The hybrid system consists of a neural network and three expert systems. It will influence the transport time by optimization of loading processes. In this manner the time and money will be spared. The loading surface and the number of trucks needed to transport the goods will be also optimized by continuous adaptation to the current economic situation.

In this work, a recommender system is proposed for a manufacturing appstore which is designed and built to revitalize online application trades among application developers and small size manufacturing companies. The aim of the recommender system is to create and provide each website user an effective application recommendation list. The list for a user might include items which are not bought by the user but useful. To build the recommendation list the proposed system makes a list of users having similar purchasing pattern to the given user. To construct the user list every user is represented by a

k

-dimensional vector of categories which are predetermined according to industry and business area. Based on the vectors user similarities are calculated for every pair of users. With the user list the system figures out recommendation candidate items which are purchased by users in the list but by the target user. To rank items in the candidate list an item similarity metric is utilized. The metric for a given item implies how close the item is to the applications which the target user purchased. Finally, candidate items are ranked by this metric and first

r

items are recommended to the target user. To demonstrate the effectiveness of the proposed algorithm the proposed system is applied the manufacturing appstore (

www.mfg-app.co.kr

) and a numerical analysis has conducted with real data from the appstore.

This paper presents a tracking system developed to study the behavior of an oil tanker moored at the Berth “A” of the Leixões Oil Terminal, Porto, Portugal. A brief description of the local environmental conditions and the existing operational conditions at that oil terminal are presented. Due to extreme outdoor working conditions a Kalman filter was implemented to ensure the robustness and reliability of the obtained measurements. Tests were performed in laboratory on a physical model of a moored oil tanker at a scale 1/100. The results were compared with a commercial motion capture system installed in laboratory. The presented measurement system was developed as part of the DOLPHIN project that aims to study the behavior of moored ships in harbors.

The use of automation can increase competitiveness but does not guarantee advantageous results. The right choice of technology and correct implementation and use is the key to a successful outcome. This in turn puts great demands on how automation development projects are managed. The aim of this paper is to make a comparison between industrial needs and existing theoretical support associated with managing automation development projects. Through a multiple case study, challenges and success factors related to managing automation projects have been identified. The empirical findings are compared with automation development support found in literature. The results from the empirical study indicate the need for improved process models and clear strategy connected to automation development. The importance of an overall view and planning during automation projects is highlighted as a success factor while difficulties in collaborating with third parties is identified as existing challenges. It is concluded that the support in literature deals with many of the identified challenges and success factors and offers some support for specific parts of the automation development project. There is however still need for an overall framework connecting existing theoretical support, and suggesting how strategy can be connected to the process of developing automation.

Manufacturing industry in economically developed countries is undergoing a major change. Vast demands on quality, price cutting and increased throughput together with deepening globalization, put a lot of pressure on manufacturing companies and their management. Efficient utilization of advanced manufacturing technology (AMT) seems to be a convenient tool to address the challenges we have to face. However, it is not easy to select the most appropriate technology, purchase it, implement it successfully, and to reach the stage of its routine operation. Especially small and middle-sized companies lack relevant experience and an unsuccessful attempt to adopt AMT can easily lead to serious problems. This paper brings out selected results of several surveys that were carried out in the Czech Republic. We will focus especially on the problems related to AMT benefits expectations, management attitudes toward AMT, and methods used during the appropriate decision making processes.

The market and technology environment of manufacturing companies in Europe is rapidly changing. Past crises have shown that variability in demand is far greater in magnitude in a highly networked global economy. With growing customer requirements, companies expand their variety of products, a trend that is intensified by the order-specific product customization typical for build-to-order and small batch production. Companies will only be able to address these challenges if a high level of technological and process flexibility and adaptability on the shop floor is provided for and made use of. Within a socio-technical production system (where men and technology interact), organizational and process-related response mechanisms are also necessary to dynamically align the complex order fulfilment process to be found in build-to-order and diversified mass production. The presented approach describes a reference model with a takt-based production system enabling the dynamic alignment of the entire order fulfillment process, spanning all stages from sales via material planning to manufacturing and assembly. The takt times are modularized and designed in a way to enable integration across functional boundaries for a dynamic alignment.

This paper studies an integrated forward and reverse (closed-loop) supply chain network design problem with sustainable concerns under the uncertain environment. We are interested in the logistics flow, capacity expansion, and technology investments of existing and potential facilities in the multi-stage closed-loop supply chain. First, a deterministic 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. Then, due to the uncertainty in supply side, customer demand and return quantities, the robust counterpart of the proposed multi-objective supply chain design model is presented using the robust optimization theory. Both deterministic and robust multi-objective supply chain design models are transformed into single-objective models to obtain non-dominated compromise solutions using LP-metrics-based compromise programming method. In the numerical evaluation and results, we analyzed the relationship between the total cost and carbon emission in integrated supply chain network and verified robustness of the proposed robust multi-objective supply chain design model by the generated non-dominated compromise supply chain design solutions.

In an international competitive environment, where companies can sell their products all over the world, coordination with other companies is of utmost importance, as a means to obtain an optimal utilization of their own resources and a competitive advantage over other supply chains. Nevertheless, in real world, most businesses are reluctant to share demand information or future plans with others, even if they belong to the same supply chain, the reason being that most of them see any other company as a potential competitor. This paper describes the architecture of an integrated approach for dynamic production and distribution scheduling in a supply chain with three levels; i.e., a company, its suppliers, and customers. This architecture tries to provide solutions to improve the performance of the supply chain by identifying the information that must be exchanged between nodes and developing methodologies for dynamic production and distribution scheduling in a coordinated manner. Moreover, a number of exceptions have been considered, both in production and distribution, to make the model as realistic as possible. Finally, the paper focuses on the distribution stage, where the problem is presented as a Dynamic Vehicle Routing Problem with Time Windows and Backhauls. This research is part of the PRODIS project (Grant PI2011-58, funded by the Basque Government in Spain).

Currently, performance analysis on complex manufacturing systems is performed in an ad hoc way since the main objective is to verify if the strategy designed has been helping companies achieve their targets following a reactive approach. However, more and more companies are performing in competitive markets, forcing them to become more proactive than reactive. This way, a simple approach is no longer suitable for this type of companies, and a stronger and effective interaction between the strategic and operational layers is key. Therefore, this research proposes a framework composed of both qualitative and quantitative methods that allow decision-makers to better understand their production system. Moreover, using key leading indicators as reference, the idea is to provide companies with the ability to anticipate future performance behaviors based not only on the knowledge acquired, but also on a mathematical tool that will synthesize this knowledge and infer future performance behaviors. This paper explores a critical issue for contemporary industrial organizations and sustainability issues concerning energy consumption. In this scope, an important research was performed aiming at modeling and understanding the normal behavior of electricity consumption, as well as the factors affecting energy consumption in the painting line of an automotive plant.

Assuring the highest quality at a realistic cost is a permanent challenge for commodities manufacturing. Complex processes, demanding customer specifications and high production rates make the traceability of Non-Conformities (NCs) a defiant task, requiring a holistic approach and methods to complement the traditional quality control tools. This paper presents a new tool, that addresses the different NCs generated along a production line in a matrix way and apply the Design Structure Matrix (DSM) principles for a more comprehensive analysis. This tool was applied in an industrial setting with the purpose of improving the quality of three-piece tin plate aerosol cans. Due to the complexity of the problem, where many NCs can be generated along the production process eventually causing defective aerosol cans, the application of this Non-Conformity Matrix (NCM) tool showed promising results, by a clearer identification of interactions among NCs. Subsequently, DSM algorithms of clustering and sequencing were applied on this matrix, pointing out which are the most important clusters of NCs throughout the overall manufacturing process, thus targeting the efforts of quality control engineers at the critical activities of the production process. Linking this tool with other process improvement tools, such as design of experiments and failure mode and effects analysis will significantly improve the final product quality, thus reducing the overall costs.

Controlling, maintaining, and improving quality is a central topic in manufacturing. Total Quality Management (TQM) provides several tools and techniques to deal with quality related topics, which are not always applicable. With the increased use of Information Technology (IT) in manufacturing there is a higher availability of data with great potential of further improvements. At the same time this results in higher requirements for data storage and processing with demanding, time consuming sessions for interpretation. Without suitable tools and techniques knowledge remains hidden in databases. This paper presents a methodology to help analyzing root causes of nonconformities (NCs) through a pattern identification approach. Hereby a methodology of Knowledge Discovery in Databases (KDD) is adapted and used as a quality tool. As the core element of the KDD methodology, the data mining, a well-known statistical measure from the field of economics—the Herfindahl–Hirschman Index (HHI)—is integrated. After presenting the theoretical background a new methodology is proposed and validated through an application case of the automotive industry. Results are obtained and presented in the form of patterns in matrices. They suggest that concentration indices may indicate possible root causes of NCs and invite for further investigations.

Improved efficiency can be achieved through the effective management of efforts to improve productivity. Effective troubleshooting requires an ability to observe changes in workover performance over time. The investigation of the cause of the downtime has been made and takes steps to prevent the problem from re-occurring in the workover procedures. The fact of the matter is that there are three types of problems mostly encountered with workover procedures: workover design errors; poor operation; poor workover practices. The objective of this work is to minimize production losses by identifying downtime factors and eliminating the causes by generating Key Performance Indicators (KPIs) to evaluate and enhance the procedures of the workover. To achieve this objective, this paper presents a downtime model framework to address this issue. Using this model, the generic factors and processes related to downtime are identified, and the impact of downtime is quantified. The work findings highlight how various factors and processes interact with each other to create downtime, and mitigate or exacerbate its impact on workover performance. It is suggested that production engineering departments at Arabian Gulf Oil Company (AGOCO) need to adopt proactive equipment management and workover programs to minimize the impact of downtime.

The aim of this paper is to develop OEE as a metric and a measure to monitor the actual performance of workover activities. Improved efficiency can be achieved through the effective management of effort to improve productivity. The main purpose of the OEE results is to evaluate essential data against where decisions may be made. The OEE monitors the actual performance of workover relative to its performance capabilities under optimal workover conditions. An attempt could be made to enhance the efficiencies of the workover activities rigs in the Sarir Oilfield. A case study approach was adopted for the data collection, which was undertaken over an eight-month period, and utilized a number of collection techniques including, participant observation, daily report analysis, and work experience. The concept discussed in this paper is providing the basis for developing a more uniform method of evaluating rig performance. It should result in more efficient rig operations. This method of calculating rig efficiency provides the practical measure of the workover performance which can aid in rig procedures negotiation and rig selection. The improvement opportunities in workover procedures have been identified based on OEE results for improvement and new variations of these measures can be implemented for other workover at Oilfields that use the same artificial lift method.

To assess the performance of a manufacturing system is not as easy as it seems at first. Besides common key performance indicators (KPI) mainly so called operating curves are used to this end. The advantage of the operating curves is that one can study the system behavior under varying conditions. However, the systems cannot be compared with each other so easily. To ensure the comparability of the system behavior the operating curves must therefore be normalized. In this paper a method will be developed for defining normalized operating curves, which is also suitable for complex manufacturing system structures. These methods are based on Little’s law as well as a special kind of flow graphs, with which it is possible to find the limiting bottlenecks in the system under special conditions. An example will explain that the method works.

Due to the imposition of austerity measures, enterprises are facing increased costs and overheads due to this policy at a time when the market price is decreasing because of emerging countries and globalization. This has a knock-on effect on the quality of products and enterprises look for solutions to reduce cost such as laying off staff and relocation of production to low cost countries etc. In this paper, the bases of elaboration of new models are given. For enterprise typology, reference models are defined per sector of activity and two types of solutions will be put forward. The first solution is in accordance with existing models with the progressive improvement of the system. The second solution would imply a complete transformation and the creation of new reference models adapted to the actual constraints of enterprises. This category of reference model, complete transformation, is constructed not only for enterprises but also local authorities. Present models integrating optimization around criteria such as quality, cost, and lead time by projecting themselves toward a target to be defined will undoubtedly lead us toward new models which take into account social, societal, and environmental parameters.

Due to the increasing globalization process and the current economic situation, the power has shifted from the producer to the costumer, forcing companies to become more aware of the market needs. In order to become more customer-oriented, companies have been enhancing their management capabilities by shifting from a functional oriented approach to a process centered strategy, where core inter-firms processes can be seamlessly monitored and controlled. Since it is not possible to manage a system if its performance cannot be measured continuously during its entire life cycle, it is necessary to explore flexible and agile performance measurement and management systems as they are important tools capable of supporting the achievement of the strategic goals on the operational side. In the recent years several research projects have developed techniques and tools that support the collaboration. However they are restricted to the business level. In order to achieve the goals with the best performance, innovative and appropriate process monitoring and control mechanisms are needed. Consequently, this research provides an innovative solution that facilitates not only the gathering of operational and strategic information but also the assessment of collaborative manufacturing processes behavior following a fuzzy approach.

Companies are supposed to be aware of the parameters of job satisfaction to retain a greater motivation and reduce the staff turnover. Shift workers have non-routine work hours which lead to some social disadvantages, higher levels of various disorders, and lower concentration level. From this point of view, it is inferred that measuring job satisfaction of shift workers plays an important role for companies on the way to reduce the work-related stress. Hence, a questionnaire consists of sleepiness and fatigue, health and well-being, social and domestic situation is submitted to 60 shift workers. The results are analyzed and it is seen that there are both linguistic and numerical data which cause some complexity. In order to overcome the uncertainty, fuzzy multiple criteria decision-making method is adopted which addresses approximate reasoning. The main aim of the study is to emphasize the importance of adverse effects of shift work and propose a model to measure the job satisfaction. In the context of shift working, the findings of the study provide managers prominent results on how to enhance the job satisfaction of their employees. In the light of the obtained results, companies should focus more on “sleep and fatigue” to increase productivity.

Due to a change in the manufacturing paradigm, manual work is often preferred to automation while assembling products. Nonetheless, the human performance is variable by nature and from worker to worker there can be considerable differences in performance, which are commonly disregarded for the sake of simplification when analysing system performance. Heterogeneity of performance has been pointed out in earlier studies. However, there is a gap in the literature regarding the heterogeneity of performance quantification and systematization, which both researchers and industry can refer to for a more accurate assembly system performance prediction. With the objective of contributing to the knowledge on heterogeneity of performances within a group, a laboratorial experiment was set up. Several subjects were evaluated assembling LEGO parts simulating a product for the automotive interiors, based on an actual product produced by a supplier of the Automotive Industry. The results of this experiment show that the performance varies significantly from subject to subject in terms of speed and variability. A mapping approach is proposed to systematize the quantification of those differences, as well as the identification of the most typical types of performances, contributing to the knowledge on the human factor.

The constant social, political, and economic changes require business organizations to continuously readjust. Sensitivity regarding gender equality has been determined by factors such as the entry of women into the work market, changes in business management proposals, which have started to appraise human capital as the companies’ main assets or the implementation of measures to reconcile working, family, and personal life. This effort not only guarantees compliance with the applicable regulations but also an increase in productivity and satisfaction both of the workforce of the organization and of its customers/suppliers. The aim of this study is to shed light on gender equality and the degree of satisfaction of employees of technology-based companies of Science and Technology Parks (STPs), members or partners of the APTE (Association of Science and Technology Parks of Spain), trying to identify good practices carried out in these entities, extracting success factors that show how to guarantee the specific procedures to achieve the aforementioned gender equality, and indicating those aspects that can be improved in order to reach effective equity. To this end, an empiric, quantitative analysis is performed using the survey technique, with the participation, via an online questionnaire, of mid- and top-level managers of all the companies set up in the 49 partner STPs of the APTE. An analysis of the results of this phase provides a clear vision of the success elements in favor of gender quality in STPs, which can also be generalisable to other companies.

Adding values on products, services, or systems by responding to customers’ needs quickly is a relevant issue for companies and requires them to be located competitively in their environment. In line with this issue, the demand chain approach enables companies to create user-centered designs. A demand chain is defined as a special customer-oriented supply chain network structure in the decision making process, that analyses customer demand and market conditions in order to reach an efficient distribution. The aim of this study is to examine the customer portfolio in white goods industry and find the preferences of current and potential customers in order to build and retain customer loyalty. The decision rules which help to increase the market share are obtained by using the Classification and Regression Trees (CART). After conducting a comprehensive literature survey on the demand chain approach and its applications, the required components for a network structure are determined by utilizing the bi-directional relationships between the customers and the manufacturers. Hence, eighty-five customer and twenty dealer surveys are carried out. The research methodology is then presented and the data collected from the surveys is analyzed statistically. The results of the study have prominent importance to overcome the uncertainty in demand chain and to determine which strategies should be adopted by the companies to have a loyal customer base.

Manufacture using advanced composite materials is a predominantly manual process. Despite recent advances in automation; the manufacture of complex panels such as those found in secondary aircraft structures, is usually carried out by highly skilled human operators. A requirement for increasing build rates of aircraft structures means that a formerly low production cycle technique must now be applied to much faster and larger production runs. This is further complicated by a desire to achieve higher quality at lower cost. Increased automation and laminator aids are being employed to achieve this goal. This paper presents an initial study into the current state of composite laminators’ motivation using Maslow’s Hierarchy of Needs. A series of semi-structured interviews were conducted with a variety of laminators from a range of industries. The principle aim is to generate a preliminary set of recommendations based on trends gained from this initial study, with a view to later widening the study to improve motivation and thus productivity and quality.

This study makes a proposal and then presents the information required to describe operations and human resources management factors in a manual assembly line environment. This information is needed since the purpose of this study is to increase the understanding of the effects of the factors and their interrelationship on system performance. Because of the complex nature of the socio-technical assembly environment the present study focuses on task- and worker-related matters as a basis for conceptual-level analysis and factor connections flow. The study uses the Gephi software for analyzing factor clusters, occurrences, and connections by means of a relationship network. As a result, the software produced four different factor clusters, each characterized by strong mutual relationships between the factors comprising them. Further, the results of this study help to identify the factors that are to be used in more thorough analysis, from assembly environment development up to semi-intelligent decision-making systems.

The scope of this work is the segmentation of the orders of Bivolino, a Belgian company that sells custom tailored shirts. The segmentation is done based on clustering, following a Data Mining approach. We use the K-Medoids clustering method because it is less sensitive to outliers than other methods and it can handle nominal variables, which are the most common in the data used in this work. We interpret the results from both the design and marketing perspectives. The results of this analysis contain useful knowledge for the company regarding its business. This knowledge, as well as the continued usage of clustering to support both the design and marketing processes, is expected to allow Bivolino to make important business decisions and, thus, obtain competitive advantage over its competitors.

Planning of manufacturing process chains requires simultaneously the consideration of the necessary human and technological resources for producing parts. Thereby, today’s planning methodologies often only focus on the technical resources of production systems like machinery, tools, or material. A systematic integration of the worker′s competencies in terms of process chain planning is often neglected. This is a major drawback which is especially critical for production systems characterized by a high vertical range of manufacturing resources like multiple types of processes and machines or knowledge intensive manual work steps. Besides assembly processes in specialized industries, forging process chains are an example for production systems of high complexity in terms of coupled processes which will be discussed in this paper. Therefore, a new method for competence-based planning of coupled process chains has been developed, merging a competence analysis with analytical technological process models and a Genetic Algorithm for optimization. Based on a set of pareto-preferable solutions, parameters for forging process chain dimensioning can be found and selected based on the planner′s experience. The developed method and software-prototype are depicted and optimization results are discussed based on a case study.

This paper aims to provide novel ideas for capturing tacit knowledge in order to enrich the product life-time information used in product design, process planning, and manufacturing. In this paper, a case from the factory floor is presented. For capturing the tacit knowledge, different social media applications and mobile tablets can be used effectively. The captured tacit knowledge, that hold both feedback and context in its creation time, can be connected to a semantically rich, formal, and machine-readable knowledge representation that combines product, process, and resource descriptions. The paper presents novel and innovative concept that can enhance design collaboration and co-creation by lowering the barriers between different design domains. One of the possible solutions is presented here and it is expected to lower costs of design in manufacturing industry as consumer needs, manufacturing realities, and rapidly developing media technology are holistically put together.

Although Radio Frequency Identification (RFID) is one of the most promising technologies in recent years with the potential to radically improve the performance of supply chains, its adoption has been slower than anticipated in supply chain applications. This fact, led researchers to investigate the impediments and challenges of RFID implementations, as well as its critical success factors. Consequently, there is a need to understand how these challenges are being addressed during the implementation of RFID systems by organizations along the supply chain. This paper aims to fill this gap by investigating, by means of action research, and the solutions implemented in a footwear supply chain. The results of the study present the approaches developed to address six RFID implementation challenges, namely: forming the implementation team, selecting the RFID technology, and defining the RFID system infrastructure, overcoming technical problems, redesigning supply chain processes, integrating the RFID system with existent information systems, and measuring the RFID implementation performance.

Global competition forces companies to constantly increase the efficiency in their production systems. One important factor affecting the production performance is the inbound materials handling system. When designing or relocating a manufacturing system, the cost of the material handling system is one of many things to take into consideration. In connection with on-going research a comprehensive decision support for production location, both work procedures and model and tools for strategic and economic analyses are developed. A case study was conducted, at a supplier to the heavy vehicle industry, in order to develop cost models for inbound logistics. The results were two cost models of different accuracy giving the cost per part, where the comprehensive model is taking the process and equipment into consideration. In addition, the study also revealed the proportion between inbound logistics costs and assembly costs at the company studied. The result in this article is part of the development of making models for calculating the total production part cost.

This paper investigates solving a group-scheduling problem in the assembly of printed circuit boards (PCBs). The type of setup operation to assemble a group of boards exactly matches with the real application. The kitting operation in the assembly of PCBs which have always been ignored in previous research is paid attention to by introducing the term “integration of external (kitting) and internal (machine) setups,” which eventually results in the development of a dynamic PCB assembly system incorporating the concepts of just-in-time manufacturing. The problem investigated is NP-hard implying the requirement of heuristic approaches for solving industry-size problems. A meta-heuristic algorithm called Tabu Search, which is known to be efficient in solving combinatorial optimization problems, is employed. However, apart from finding the best sequence of jobs, evaluation of the objective function associated with each sequence is still an issue and it cannot be guaranteed to be optimal without the help of a mathematical model. Thus, a decision tree-based approach enabling the search to evaluate each of the sequences is developed including several properties and a lower bound, all of which are demonstrated in this paper.

Over the last few decades, a rapid advancement in the arena of technology has escalated the competitive scenario across the globe. Several companies are now using intelligent systems to assist their supply chain management activities. This research, therefore, attempts to explore the advantage of using intelligent systems in managing supply chain activities. A review of the literature shows that with growing demand of food products, improved supply and storage facilities, and strong emphasis on cross boundary trade and policies have generated a lot of interest among researchers to look at the issues faced in the food supply chain. Researchers have attempted to study various types of food supply chains; however, little emphasis has been given to study the wine supply chain industry. One of the key challenges that exist in wine supply chain is the integration among the key members of the supply chain to accomplish a collective set of tasks. This paper, therefore, aims to address the supply chain coordination issue. To achieve better coordination among the wine supply chain members, this paper put forward the use of an intelligent agent based architecture framework. The paper suggests that the proposed intelligent multi-agent framework can reduce the complexity of decision making process, improve the supply chain coordination, and assist the SCM managers in smooth running of the wine supply chain.

Hong Kong is a strategic procurement center and logistics center in Asia. Majority of Hong Kong’s trading companies’ involvement in the supply chain is to bid orders from global distributors and retailers, and then search for appropriate contract manufacturers to produce the goods. In recent years, there has been an increasing concern for sustainability of products, processes, and services. To increase its competitiveness, it is an important issue for trading companies to take green supply chain management (GSCM) initiatives to improve its long-term development capabilities. This paper is on the establishment of a green procurement model for trading companies. The model integrates environmental and sustainability concerns into the procurement process. In trading firms, purchasing is the main SCM activity. It is therefore the focus of this paper to take environmental and corporate social responsibility (CSR) requirements into account for product and supplier evaluation and selection. The procurement model developed by Analytical Hierarchy Process (AHP) comprises an approach to rank and select products and suppliers with the incorporation of sustainability requirements. The proposed system aims to support long-term supplier continuous assessment for further performance monitoring and evaluation, and also help on reviewing supplier management strategies and green supply management.

The production of large-dimensioned, customer specific goods like machinery, investment goods, and special vehicles is a demanding challenge because of the integration of numerous customer specific features and the need for short delivery times. In addition, complex assembly operations require highly skilled workers to ensure the flexibility of production, which is needed to cope with varying workloads and assembly procedures. The presented paper introduces a concept for planning and controlling the production of those products, with a focus on personal allocation and assembly order development. After giving a brief problem statement, which highlights the major aspects to be considered, an overview of the literature, which copes with comparable problems, is given. The following sections introduce three means of control used in the concept and present a computational investigation of these under varying settings concerning hindering effects in assembly operations. The paper is closed by a discussion of the achieved results and a brief summary.

Injection mold maintenance scheduling is a challenging problem in plastics production systems. On one hand, it harmonizes the production activities on machines and molds. On the other hand, it decides when maintenance activities should be performed in order to improve the reliability of production systems. In the previous studies [

1

,

2

], a Joint Scheduling (JS) approach was proposed to deal with some mold maintenance scheduling problems. It was shown that the JS approach outperforms the traditional Maximum Age (MA) approach. However, the models had not considered the capacity of mold

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lifting crane which is likely to be the bottleneck of mold maintenance activities. Therefore, in this paper, a new problem is modeled with the consideration of the capacity of mold

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lifting crane. A genetic algorithm approach is applied to deal with this new problem. The numerical examples show that considering the mold

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lifting crane, the JS approach can still outperform the MA approach and obtain the shortest makespan.

This paper focuses on the machine arrangement problem on common loop network. The machines are arranged in a cycle and materials transported in only one direction around the cycle using a conveyor belt. The goal of this problem is to minimize the maximum number of loops required for the manufacture of any of the products. The problem is known to be NP-hard. Thus, the right way to proceed is through the use of heuristics techniques. However, the industrial managers complain about an issue which is the mishandling of large variables and constraints that led to a lack of realism. In this work, we introduce a new formulation for the machine layout problem by adding new constraints which are the machine dimensions and the proximity constraints between the machines. This new formulation led us to propose two-stage approach to solve this problem. The first step consists on positioning the machines on a grid while respecting the proximity constraints and machines dimensions. The second step aim to optimize the path between these machines already positioned in order to minimize number of the loops traveled by parts. In this paper, we are interested in the first step by using multi-agent system. This choice can be explained by the well-known cooperation of the multi-agent system. The effectiveness of our approaches is demonstrated through numerical examples.

This paper presents two different models for the organizational procedure of Integrated Process Planning and Scheduling from scientific literature. These approaches try to connect both components of the Product Development Process to realize better results in planning. Objectives of these approaches are the reduction or even the elimination of capacity conflicts, the reduction of makespan, and the compliance of due dates as well as the adaption to disturbances at job floor. An introduction and a description of problems of the classical procedure as well as advantages of an integrated view will be followed by a presentation of both models of integration called Non-linear Process Planning (NLPP) and Closed-loop Process Planning (CLPP). Another main component of this paper is a further developed model based on NLPP, which is able to overcome the significant deficits of the models presented in scientific literature.

The aim of this paper is the presentation of a scheduling method, its implementation to a software system, and its application to a commercial refrigerator factory. The method employs the modeling of the factory’s resources and the assignment of the workload of the resources in a hierarchical fashion. The developed software system simulates the operations of the factory and provides a schedule for the manufacturing system’s resources. The system is integrated with a holistic virtual platform, namely Virtual Factory Framework that allows it to exchange data related to product, process, resources, and key performance indicators along with other software components also integrated with the Virtual Factory Framework. A set of digital scheduling experiments with data, coming from a real manufacturing system are conducted in order to validate the proposed method and the implemented system under different operational conditions.

Facility layout is the arrangement of machines, equipments, or other resources in a manufacturing environment to designate an ideal configuration for minimizing the total cost by affecting the production flow. Layout design has a significant impact on the performance of manufacturing systems, and the layout problems are generally regarded as NP-Hard problems. In the literature, a considerable amount of attention is granted to biology-inspired metaheuristic algorithms in order to find efficient solutions to deal with many optimization problems. In this study, the general features and the mechanism of the Firefly Algorithm are presented initially. In order to illustrate how to adapt the proposed algorithm to a real manufacturing problem, a numerical application is shown for the solution of single row facility layout problem. A candidate solution array for 15 departments is obtained through the presumptions of the proposed algorithm. For a sample size of 500 iterations, 95 % confidence interval is constructed between the values of 8,306.53 and 8,378.22 with a standard error value of 18.288.

Micro-mixer has been widely used in mixing processes for chemical and pharmaceutical industries. Conventional design of micro-mixer T-junction has poor mixing performance; while improved micro-mixer design typically requires expensive manufacturing processes due to complex geometrical structure. In previous work, we introduced improved yet easy to manufacture micro-mixer design utilizing wavy structure micro-channel T-junction which can be easily manufactured using simple stamping method. To extend our work, we optimize the geometrical parameters, i.e., wavy frequency, wavy amplitude, width and height of the micro channel. A robust Taguchi statistical method is employed for this purpose with regard to the mixing performance (mixing index), pumping power, and Figure of Merit (FoM). The results indicate that high mixing performance does not always associates with high FoM due to higher pumping power. The advantages and limitations of the designs and objective functions are discussed in the light of present numerical results.

In present day’s economy of recession and frequent market fluctuations, it is difficult to satisfy the customer with the products and services at reasonable price. The prices of resources are increasing consistently and the manufacturing industries have to optimize the use of resources so as to make a trade-off between the cost incurred and the services provided to the customer. Realizing this scenario, this article proposes an automated system equipped with artificial intelligence to deal with these complexities and difficulties. This automated system has the capability of self-decision-making and is further complemented by the feature of reconfiguring its operation according to the various uncertainties in the Supply Chain. It utilizes multi agent architecture for its operations. It focuses on adding some additional features to the conventional multi agent architecture for improving the efficiency of the Supply chain and optimizing the make span. It exploits the “Outsourcing of operations” feature by its agents to conclude the manufacturing processes faster and reduce the idle time of certain machines. This article also presents the concept of outsourcing of the manufacturing plant. This multi agent architecture will facilitate small scale manufacturing industries to execute their manufacturing process and complex logistics issues efficiently.

In this paper, Multi-Item Capacitated Lot-Sizing Problem (MICLSP) has been taken into consideration. Demand for each item in each period is uncertain and it is known at the starting off first time period. This paper also addresses the backlogging and a high penalty cost occurred for backlogging. Simultaneously, the penalty cost for exceeding the resource capacity is also occurred. These both penalty costs are included in the main objective function. In this connection, the main objective is to achieve such a solution so that the total cost should be minimized. The ingredients of total cost are the setup cost, production cost, inventory holding cost, and aforementioned both the penalty cost. To solve this computationally complex problem, a less explored algorithm Biased Random Key Genetic Algorithm (BRKGA) has been applied. According to the authors’ knowledge, this paper presents the first study for the application of BRKGA in lot-sizing problem. The encouraging results proved that the proposed algorithm is an efficient algorithm to tackle such complex problems. A comparative study with other existing heuristics shows the supremacy of proposed algorithm on the basis of quality of the solution, number of generation and computational time.

Sustainable manufacturing is regarded as a new manufacturing paradigm that provides an abstract representation of a manufacturing system. Although many manufacturing paradigms have been proposed, most of them are based on the assumption that the boundary of a manufacturing system can be defined based on customers’ requirements. However, sustainable manufacturing is different. It has evolved from the past manufacturing paradigms and brings new challenges to today’s practice. Within the context, the objective of this work is to examine the manufacturing requirements in a wider scope, to revisit existing paradigms so as to clarify the limitations and bottlenecks, and eventually to identify future challenges for better sustainable manufacturing. This paper reports our findings on what the requirements and challenges are, and reveals a Cloud-based approach toward better sustainability.

Companies are facing challenging circumstances: markets are evolving; clients are becoming more and more demanding and unpredictable; product variety is rising; time windows are shrinking; and error tolerance is decreasing. Therefore, companies must adapt and improve their supply chains, develop a differentiated supply chain strategy to solve the supply–demand mismatch. So far, the main differentiation approach has been focused on: (a) product; (b) customer; and (c) market characteristics. This paper uses a case based research approach in the context of a business-to-business food company to analyse the use of analytical tools commonly applied in other fields of research to support the identification of product and customer characteristics relevant for supply chain strategy differentiation. Using daily recorded sales data over two operational years we apply the following methods: Principal Component Analysis (PCA) followed by Cluster Analysis (CA). A new differentiator (order corrections) is introduced, in between characteristic correlation is spotted and used to generate a more meaningful attributes (case specific), creating four product segments based on proximate characteristics. Therefore, by reducing a large product portfolio into manageable groups of homogeneous SKU’s it is possible to assign a proper set of supply chain tailored practices.

Small and medium enterprises (SMEs) represent over 90 % of the companies in the world. As well, the vast majority of persons employed work in SMEs. Most laws, regulations, and standards are targeted toward and implemented by larger firms. In order to promote global sustainability, policies need to be adapted for smaller entities. This work summarizes an assessment on environmental sustainability in SMEs in a rural region of the United States, which identified barriers to and promoters of environmental sustainability, including how sustainability and green initiatives are interpreted by small business owners. This work also summarizes a model for effectively adapting technology policy and practices to promote (or impede) particular technical practices and policies. A discussion of how this assessment and model can be integrated in the context of promoting sustainability among SMEs in a developing country of Morocco is presented. Finally, the implications for promoting the effective management and perception of sustainability in the world’s SMEs are presented and discussed.

Many manufacturing organizations in developed countries need to be proficient in not only incremental improvements but also radical innovations. Radical innovations largely depend on exploration capabilities, in other words capabilities of searching, discovering, and developing radically new systems, processes, and operational practices. Since many manufacturing organizations are proficient in incremental improvements, an important challenge for them is to develop the exploration capabilities across the organizations. However, little knowledge has been accumulated as to how to develop such capabilities in practice. The main purpose of this paper is to propose an approach to building organization’s exploration capabilities. In the approach, the capabilities are built through leaders iteratively and deliberately creating situations where groups in an organization have to or can be more explorative. The approach is made by analogy from how organizational changes toward lean manufacturing were driven by an experienced lean consultant. In addition, this paper presents a model of how to practically apply the approach at companies. The model is developed firstly based on existing theories then modified through employing the model at a manufacturing company.

Manufacturers are nowadays highly affected by the ever-increasing number of product variants, under the product personalization trend. The large number of cooperating manufacturing network partners leads to enormous search spaces of alternative manufacturing network configurations. This obstructs effective decision-making towards configuring efficient network structures, a nonetheless crucial decision for a company. Exact methods guarantee that the identified solution is the optimum, with regards to the objectives set in the specified problem. However, in real life cases the magnitude of the solution space is such that these methods cannot be utilized due to computational constraints. For tackling such NP-hard problems, meta-heuristics can be utilized that provide a trade-off between the quality of solution and the computation time. This research work describes the modeling and solving of a manufacturing network design problem using the meta-heuristic methods of simulated annealing and tabu search. The quality of the results identified by these methods is compared with the results obtained from an intelligent search algorithm and an exhaustive enumerative method, which are implemented into a web-based platform for the design and planning of manufacturing networks. The approach is validated through its application to a real life case study with data acquired from the automotive industry.

Nowadays, business models play a key role in competitiveness. Each industry has specific needs regarding the customization of their business models. Through a personalized business model, organizations can enjoy a customized mapping of all the business activities. In the machinery industry domain and specifically producers of integrated Products and Services, the need for a customized business model has been growing due to the specifications of the industry. The existing business models do not satisfy the capital goods companies’ needs, therefore a study was conducted to analyze and understand companies’ specifications, the existing supporting business frameworks to further proceed with the creation of a new methodology and framework that supports the businesses of this specific industry.

In fashion business, consumer needs and expectations of specific target groups—such as elderly, obese, disabled, or diabetic persons—are arising as challenging opportunities for European companies that are asked to supply small series of innovative and fashionable goods of high quality, affordable price and eco-compatible. This paper aims at proposing a reference model to support collaborative supply networks in addressing the need for Fashionable and Healthy Clothing and Footwear products. In particular this work describes the implementation of the model in a real case highlighting the developments and changes implied at network level.

Purpose

The purpose of this paper is to present a case study to assess the customer service concept within the internal supply chain management (SCM) approach. In particular, the paper emphasizes an interest in an integrated approach to considering customer service performance in an efficient way. Indeed, information systems as technical support play an essential role in the SCM of small and medium-sized enterprises (SMEs). The customers are the first concern of any firm that seeks to be competitive.

Design

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methodology

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approach

A qualitative research methodology is used based on semi-directed interviews with SME telecommunications professionals and direct observation as part of a telecommunications network SME in France.

Findings

In total, the objective of this empirical case study is to delineate the concept dimensions (background). These dimensions allow the drawing up of a framework of actions to improve SME customer service performance evaluations in the supply chain management.

Practical implications

This proposal will help to the picture regarding services for improving the relationship with the customers (by commercial and Project Manager reporting on customer follow-ups); improve operational reporting (internal indicators, quality reports); improve invoice control and indicator follow-ups with the Project Manager; and improve cost management.

Originality

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value

The paper adds a new case study—that of Alpha—which is focused on the engineering and telecommunications network. As such, it offers a new perspective that customers are among the major actors in the telecommunications market, along with the corporate customers and administrations involved in implementation or service quality follow-up and telecommunications use.

Disruptive innovation, such as electric vehicles, go along with new requirement in aspects of cost, quality, and scalability while the market environment is considered as risky and dynamic. Many companies form strategic alliances, acquire competencies or participate in new developing value-added networks to cope with the new requirements and to spread the risk. This leads to new opportunities for value-added networks, as they can be designed to perform best in terms of cost and quality, to handle scalability as well as to define a cooperative strategy to align the specific goals of network participants. For companies it remains unsure which value-added network to join, which role to play and whether the cooperative strategy fits the corporate strategy of the company. So far there is no methodology that allows network participants to assess the strategic fit of a value-added network. This paper address the need for action in theory and practice and presents a methodology to assess the strategic fit of value-added networks. Part of the strategic fit assessment are: fit in motives, fit in resources and products, structural fit, and cultural fit. The electric engine production for electric vehicles is chosen as an example for disruptive innovation and serves as the application case for the methodology of the network fit assessment.

The main purpose of this research work is to conduct an in-depth analysis of the existing relations between organizations located in Science and Technology Parks (STPs). The aim is to analyze the extent to which the entities located at Walqa Technology Park (Spanish acronym PTW), situated in Huesca, interrelate, and which factors have an influence in these relations. To this end, a total of 56 organizations located at PTW were encouraged to participate, via personal interview or e-mail. Later on, the network of relations formed by the different agents of the park were analyzed, verifying the hypothesis that states that the relations between them depend on the characteristics of the entities; in this case, on the type of entity, size and activity sector. A study of different properties of the network and of the nodes were studied, such as the density of the network and of the agents per se, the degree of centrality of an entity, the centralization rate as well as the degree of intermediation. With a response rate of 96 %, the main results show that, as a result of the relations established, the companies set up at PTW obtain: opening up of new markets and business credibility. Based on an overall perspective, the appearance of marked centrality patterns that group together entities such as technology centres and universities in the centre of the network, can clearly be observed, the reason being that they combine the largest number of technology collaborations and staff collaboration. From the viewpoint of size, small companies appear in the central network with a very high number of collaborations. Finally, depending on the sector, it can be seen that the most interrelated are those that belong to the ICT sector followed by those from the engineering and energy sector.

Multi-agent systems have been successfully used to represent distributed manufacturing systems. Each part or characteristic of the system can be represented by an agent which acts independently and in a cooperative way. Information exchange between agents and combined individual rules for each agent can lead to the emergence of a better integrated operation. Better decisions from a holistic viewpoint can be achieved when manufacturing asset management is supported by a multi-agent approach. A model to manage distributed manufacturing is proposed and applied to onshore oil fields. The distributed characteristics of oil field units, such as wells, collecting stations, compressing stations, supplies, and mean that they have to cooperate to reach production targets. The integrated management model carries out a cost analysis and helps to identify unprofitable assets and to support decision making processes as well. Agents help to reduce the load of information for the operator, giving him/her more time to focus on situations that require greater attention. Successful applications in which the proposed multi-agent model could help oil field surveillance and support decision-making process are presented.

The purpose of this paper is to investigate Augmented Reality applied into a real industrial context (Industrial AR) from a new perspective: AR is not anymore seen as a standalone technology for assisting specific manufacturing tasks, but rather as a totally integrated framework within future factory workplaces. In the last 15 years, both academic and industrial research communities have seen the huge potentiality of AR in improving industrial performances in several scenarios, but it is undeniable that no killer-apps or de-facto standard as well as scalable solutions have been developed yet. The paper addresses the issue from a new and different point of view showing how AR can potentially be exploited in order to boost lean-based manufacturing and management processes, thus guaranteeing more efficient production and higher competitiveness. The paper is organized with the aim to underline the new and feasible opportunities offered by the proposed approach, as well as the main technological and conceptual challenges connected to it. Finally, a potential framework capable of enabling AR features for visual management in real factories is proposed.

Lean Management is a very broad management method. Many companies try to implement the lean management concept nowadays. It represents a multifaceted concept based on integration of the methods JIT, total quality management, total preventative maintenance, human resource management, Six sigma, KAIZEN, KANBAN, productive maintenance and involved employees etc. The problem in practice is how to monitor the efficiency of the lean management system. The performance measurement is an important diagnostic tool for management and its implementation may be one solution of the afore mentioned problem. Design of the performance measurement system should be based on lean metrics and a process controlling system. Process performance measurement tools and techniques applied to enterprise environments are essential for the enterprise continuous improvement. Therefore, the aim of this paper is to present research study for implementation of the performance measurement based on the Balanced Scorecard method and the process controlling for the lean management.

The current reality of intense competition has forced many companies to increase their performance and competitive advantages by pursuing innovation and improving and streamlining internal methods of designing products and processes. With shortening of product life cycle, in order for companies to survive, the need for a continuous stream of multiple innovations over time has arisen. However, the resources consumed by companies, whilst developing a product or process, are increasingly high, even in integrated approaches, and often the finished product or process arrives too late to provide the company with an edge over its competitors. Due to the large impact Lean philosophy has had in recent decades, within the manufacturing area, through the increase of efficiency and generation of continuous improvement, more companies have progressively applied Lean methods in their units of product and process development. This paper seeks to present a reference model for Lean implementation in the areas of product and process development in order to support companies in their path to streamline and make their innovative processes more efficient. The proposed reference model includes a concrete case study example that helps to explain the main concepts behind the proposed approach.

The aim of the work presented in this paper is to determine the most important critical success factors (CSFs) which have the strongest impact on the implementation of lean tools and ERP systems within small-medium enterprises (SMEs). In order for SMEs to be competitive and responsive to the market, they need to assess their practices. This can only occur by adopting the appropriate practices related to the business and manufacturing strategy of the company. The various competitive practice methods being used by organizations are Total Quality Management (TQM), Supply Chain Management, Six Sigma, Lean tools, Material Requirements Planning (MRP), Manufacturing Resource Planning (MRP II), Enterprise Resource Planning (ERP) systems. These methods are considered as tools and practices, which can lead to improve the performance of SMEs. The approach, which has been adopted in this work, consists of two phases; the first phase is a literature review, in order to identify the set of CSFs that have an impact on lean tools and ERP systems implementation. The second involved the design of a questionnaire and the gathering data from SMEs regarding the factors, which they consider influences the successful implementation of lean tools and ERP systems. Ten SMEs were involved in completing the questionnaire and the first analysis was based upon six the received responses. This study has indicated that there is a positive correlation between the CSFs of lean tools and the CSFs of ERP systems.

An increasing number of companies implement lean principles into their production processes due to changing market conditions, a higher market competition, and the high success of the Toyota Production System in the 1970s. Since lean manufacturing focus primarily on changes in the process organization, most of these changes do not require complex technologies. Additionally, many companies establish IT systems, e.g., a Manufacturing Execution System (MES) or an Enterprise Resource Planning System (ERP), as well as RFID and sensor technologies, for the improvement, and monitoring of their processes. They may enable autonomous production that shifts the decision making from central to decentral.The question is how human factors, IT systems, and smart communication technologies can support the objectives of lean manufacturing. This paper provides an approach for the analysis of the correlation of lean manufacturing and decentrally controlled production by modern technologies, modern software systems as well as human, and organizational factors. Thus, the effects of the usage of autonomy for a decentralized production control and benefits for various objectives can be classified. Therefore, the paper introduces a three-layer cluster for the classification of the level of autonomy.

The academic and industrial worlds seem to agree in the convenience of implementing Lean Manufacturing. Arguments to highlight the benefits of implementing Lean usually include testimonials from successful companies, published case studies, even conference presentations, plant tours, and television programs. It is not easy to foresee the impact of a Lean implementation in strictly monetary terms. Lean is an operational philosophy that does more than saving money; it prepares companies for sustained improvement and creates disciplines and operational capabilities, yet it could be argued that these capabilities are hard to value and quantify. In this paper, we propose a flowchart-type methodology to decide if a change in a procedure, in the use of tangible resources or in the use of time brought about by the implementation of a Lean Manufacturing technique will have a measurable economic impact. The decision maker will need to know the specific circumstances of the production system, but we believe he will be able to predict the economic impact of a Lean implementation (or to evaluate the results of an ongoing Lean project) with more precision, to build a stronger and more comprehensible business case and convince upper management of the real benefits of Lean.

Manufacturing industry is currently under a strong competitive pressure, not only from the developed countries, but also from countries with significantly lower labour costs. New products and processes are and will be fostered by the emergence of new manufacturing technologies, stimulated by intense competition. As complement, new management and labor practices, organizational structures, and decision-making methods will emerge. It is necessary to develop strategies that are capable of building a strong competitive position in the global market and the journey starts on the shop floor—on the capability to supply the client needs. One of the most critical point of production process in manufacturing industry is the Setup process. When companies give low attention to the Setup process or don’t know that it’s possible to improve it, the overall time spent on it can be really significant. Consequently, a significant percentage of production time is consumed in non-added value activities, time that could be used in actual production or to increase production flexibility. This paper is about the creation of a tool capable to diagnose the Setup process. This tool is based on a methodology that allows identification and monitor Setup’s key process indicators (KPI)—i.e., total time, longer operations, waiting times, transports, handling and cleaning times. It also allows the Setup process control by assessing the KPI of consecutive Setups.

This paper deals with introduction of Kanban principles in the form of social group game. The game was prepared for the course of operational management at the University of West Bohemia. The goal of the game is to show participants how Kanban works at the simulation of bar. In the first round participants can see problems connected with wasting due to unfinished production. In the second round Kanban is implemented. Participants then can see the results and benefits of Kanban. The whole game is introduced in paper and benefits of the game based on students evaluation after course are discussed.

Six Sigma is a data-driven approach using specific tools and methodologies that lead to fact-based decisions. It employs a well-structured methodology to reduce process variability and eliminate waste within the business processes by applying statistical tools and techniques. This paper presents a case study highlighting how a manufacturer of domestic water heating equipment has used the Six Sigma Define-Measure-Analyze-Improve-Control (DMAIC) methodology to improve one of its internal logistical processes; the replenishment of supermarket in production lines. The paper describes how a company can use a systematic methodology to improve an internal logistical process, moving it toward a world class quality level. The application of the Six Sigma methodology resulted in a reduction of those routes taking more than 30 min to be completed from 25 to 3 %; a reduction in the coefficient of route time variability from 40 to 14 % and a reduction of the mean route time from 31 to 24 min. These results had a significant financial impact, allowing the elimination of one of the three existing routes—without any negative impact in the supermarket replenishment process—leading to a drop in man hours and costs through the elimination of two milk runs.

Distribution is an important activity in the integrated supply-chain management for pharmaceutical products, especially when these goods have to travel long distances from manufacturing facilities to the consumer markets. This paper presents the case of a pharmaceutical company in which the quality assurance and the management teams set an objective of reducing their distribution costs to less than 0.16 Euros per unit. The quality assurance (QA) team has decided to optimize sample shipments as a high priority in order to reduce costs. The methodology used in this study was supported through a series of experiments using a Lean Six Sigma approach that implemented the Define Measure Analyze Improve Control (DMAIC) phases. The QA team analyzed the previous state of sample shipments and then suggested improvements based on an optimized process. The results showed a set of non-value added activities specifically in transportation, motion, waiting, defects, and the sub-utilization of people. Based on Lean tools, the improvements achieved a 26 % reduction in the cycle time spent and no complaints from customers have been reported since implementation of the new process. In addition, a control plan was also developed to track shipments and maintain open and close communication with the customer. Finally, the resulting processes that have been implementation have a significant impact on reducing distribution costs.

Fierce competition and more complex customer needs and demands have forced organizations to continuously improve their operations and the quality of their products and services. Over the last decades, two of the most popular and effective strategies used by organizations to achieve such improvements have been lean manufacturing and Six Sigma. However, as competition and costumer needs and demands evolved and increased, the quest for even more efficient operations and higher quality products and services resulted in the integration of these two strategies to form an improved approach known as Lean Six Sigma. This paper investigates and compares the implementation status of Lean Six Sigma in South Korea and the UK. To do this, an empirical and exploratory study was conducted based on the design, validation, and random distribution of a survey questionnaire in various South Korean and UK industries. The data was analyzed using descriptive statistics. The study results revealed that Lean Six Sigma has been more widely adopted in the UK than in South Korea and that some other operations and quality improvement strategies are also a popular choice among organizations of these two countries. The results also provide evidence about different aspects of the implementation of Lean Six Sigma in South Korea and the UK. This study offers academics, researchers and practitioners interested in Lean Six Sigma with some preliminary evidence of the adoption of this approach in two industrialized nations such as South Korean and the UK.

The manufacture of primary structural wing components from high-performance composite materials is a relatively new technique. GKN Aerospace faces the challenge of manufacturing complex large-scale aero-structures by the ‘Automated Fibre Placement’ (AFP) process whilst transitioning from the ‘new product introduction environment’ to meet contractual production rates. This paper reports on the adoption of the Lean philosophy within a ‘value stream’ by capturing staff perceptions to gain an understanding of the success levels and areas of concern. The research is of particular importance since the ‘barriers of resistance’ in manufacturing environments can be high if Lean is not introduced in a fashion production staff can relate to. Therefore, the research conducted offers GKN the opportunity to focus on the specific areas to realise continuous improvement through the adoption of Lean. The research investigation consisted of a questionnaire employed to gauge staff perceptions from the end of operations at Year 1. At the end of Year 2, the questionnaire was repeated to broaden the cross-sectional study over a longitudinal time horizon. The results were subject to statistical significance testing which showed the differences in staff perceptions were evident. These differences were attributed to the overall level of Lean understanding and appreciation within the facility. The novelty of this research is manifested in how well Lean practice has been adopted in a large-scale aerospace manufacturing facility transitioning from the NPI environment to serial production. Other Lean practitioners and academics will be able to apply the approach in their work, especially those looking to incorporate a Lean philosophy in a NPI environment.

Small and medium-sized companies today need to maintain or increase their competitiveness, and this is necessary for effective production with the least amount of waste. This paper seeks to use Value Stream Mapping (VSM) to identify waste within a company in the red ceramic sector. It should be mentioned that there are few studies in the literature describing the application of lean production tools in companies in the red ceramic sector. Through the knowledge of the production process of the company, followed by a subsequent data collection, we built the current state value stream map of the company. With the analysis of this map, several improvements aimed at reducing waste in the production process were proposed, which are depicted in the future state value stream map. With the proposed improvements, we expect a 69 % lead time reduction, as well as reduction in raw material, in-process and final inventory levels.

Due to globalization, enterprises face an increasing competition that influences their strategy. To achieve a sustainable market position, enterprises have to differ from their competitors through cost or performance advantages. Both competitive advantages are linked to decisions in product development. Therefore enterprises start to initiate optimization efforts in product development. In production, enterprises achieve positive results by implementing lean production systems (LPS) to optimize their production processes. The aim of LPS is the reduction of waste and the implementation of a continuous improvement process to assure sustainable success. Due to the positive results, enterprises intend to apply the lean approach also in product development (lean development). Enterprises that want to implement lean development (LD) are faced with many different concepts and strategies for the implementation. To analyze the different concepts, criteria for an implementation process need to be identified. For that reason, the article analyzes LD-concepts regarding these implementation criteria and describes the agreements between the different concepts. Thereby, enterprises can develop a strategy for LD implementation. Based on the implementation criteria, a study was carried out among enterprises that want to establish a lean development system. The study identified which specific strategies for implementation was preferred by the enterprises.

The U.S. wood products (NAICS 321) and furniture manufacturing (NAICS 337) industries have been greatly affected by economic cycles, rising production, and transportation costs, changing buyer habits, and, arguably, most powerfully, increasing global competition. Tens of thousands of jobs were lost and a large number of companies in the industry experienced bankruptcy, closed operations, or relocated to other countries. However, theories exist stating that the use of management systems, such as Lean management, allows companies to become more competitive and enhance the likelihood of survival. To investigate Lean management practices in the wood products and furniture manufacturing industry, a census survey with all known members of these two industry sectors in the Commonwealth of Virginia was conducted. Findings indicate that a majority of Virginia’s wood products and furniture manufacturing industries have heard about Lean, but few enterprises have implemented or have started to implement Lean principles in their operations.

Pull system is an important component of lean manufacturing that can effectively reduce typical wastes associated with push production systems, such as overproduction. Using Toyota’s Kanban system, a production line can be configured as a pull system to avoid unnecessary accumulation of Work in Process (WIP). Another common method to carry out a pull concept is the CONWIP line, which maintains a constant WIP level within a segment of production line. Both methods have proven effective, but they may have different characteristics. The objective of this paper is to explore the potential to combine Kanban and CONWIP methods into a robust hybrid pull system that preserves the advantages of both methods while minimizing the disadvantages of each individual method. A simulation study has been carried out based on a real-world assembly line. Various pull system configurations of the assembly line have been evaluated and compared in terms of WIP level, number of Kanban cards in system, and throughput. The study shows that the productivity of CONWIP configuration outperforms Kanban configuration in majority of scenarios; and the performance of a well designed hybrid system can be more robust to various scenarios, compared to Kanban and CONWIP system.

This paper presents the results of a project aiming to understand the viability of value stream mapping techniques on the “one of a kind production” context typical of mould making industry. More than having a representation of a standard process, the idea is to use the mapping techniques to support the analysis and the discussion of the time-oriented performance of the whole manufacturing process. The project involved the creation of a VSM application tool which improves the analysis of the mould making critical processes, the automatic calculation of the main process indicators, and the generation of the value stream map of each process under analysis. Several mould makers were involved to support the design of the tool and to evaluate its potential in guiding purposeful improvement actions. The results presented are quite satisfactory. Even if the process is not a repetitive one, its time-oriented performance analysis reproduces repetitive time waste patterns in each company. Moreover, the visual nature of VSM techniques facilitates the process understanding and leads the improvement teams in focusing towards the global improvement.

Lean is a powerful tool, which can bring significant benefit to manufacturing industries by creating value through reduction of waste. Although the lean concept has become very popular in mass production industries such as the automotive industry, more recently the concept has been adopted in different batch processing industries and service sectors. The application of lean tools into the food processing industry has not received the same level of attention compared to the traditional manufacturing industries. The paper focuses on implementation of lean tools in a food manufacturing company in UK. The company produces diverse ranges of meat-free and dairy-free food products such as vegetable burgers, sausages, cutlets etc., and supply to the major supermarket chains in UK. In general, the typical manufacturing cycle includes raw material preparation, cooking, mixing, forming into a desired shape, coating with a crumb mixture, and frying. Finally, the products are frozen and then packaged. First, lean tools and lean practices in food manufacturing industries have been briefly presented. The implementation of lean into the company started with reviewing the products, manufacturing processes, technical facilities, and process flow charts. Key areas have been identified to achieve tangible benefits by implementing lean tools such as waste elimination, 5S, single minute exchanges of dies (SMED), Andon system, visual management, work standardisation etc. The results have been presented in the form of a case study. The paper concludes that lean tools can be successfully implemented in a food manufacturing company to improve production efficiency, to improve product quality, and to reduce production cost by reducing waste and adding value. The information presented will be of interest to general food manufacturers and in particular to frozen food manufacturers.

The results of laboratory test play an essential role for physicians to diagnose medical conditions and lead time is the major indicator of the performance. Due to the critical role of medical laboratory, increasing number of hospitals adopt total laboratory automation (TLA) to improve the performance. Although the average lead time has a significant improvement, lots of work in process (WIP) cause by specimens piled up with 40-count at the centrifuge module and batch mode at the DXC module in some peak hours. Therefore, the use of lean value stream mapping (VSM), constant work-in-process (CONWIP), and simulation were adopted. The decision variables of the upper limit WIP level, two break points for scheduling rules, and the batching time will be decided by simulation optimization. The methodology is compared with the original system in a real practical case. The results show that 74.36 % improvement in the service level was achieved.

Minimizing waste is one of the essences of modern Lean Production Systems. The activities for waste reduction are usually focused on lead time and inventory. Therefore the method of Value-Stream Mapping (VSM) has proven itself as a very powerful tool. Nowadays the unnecessary consumption of energy is more and more regarded as a kind of waste, too. There is a need to extend the proven method of Value-Stream Mapping to an Energy Value-Stream Mapping (EVSM). Therefore criteria must be defined that allow us to divide the energy consumption into value-adding and non value-adding. This is shown by using the example of a chip removal process, where the energy requirement for an air-cutting process is compared to that for an operation with a workpiece. The dual view of value-adding and non value-adding energy consumption provides the opportunity of extending the Value-Stream Mapping systematic to an Energy Value-Stream Mapping.

The experiences of 31 collaborative research projects, financed by the Federal Ministry of Education and Research, were connected through the “Efficiency Factory”. The focal point of support was “resource efficiency in production”. One of the selected projects “reBOP”(efficient production by resource-based evaluation and optimization of process chains) was investigated at the Chair of Production Systems, Ruhr-University Bochum from 2009 to 2012. A concept to identify weak points in terms of energy efficiency was developed within the project. The concept was adopted to analyze the process chain and machinery of an associate partner. Therefore the energy efficiency of the organizational and technical level was improved. Companies, involved in this project, achieved specific results to strengthen their competitive ability: enabling them—as a system provider—to create energy efficient process chains and to assist customers in efficient use of their machinery and equipment. Objective of mentioned cluster-project was to develop and implement a holistic concept to evaluate and optimize process chains and assets energetically. Energy efficiency in this context means a reduction of electric energy input at a constant output quantity. Inevitable need to evaluate and compare specific processes is their uniform, normed character. For this purpose a set of unique key performance indicators was created. This set enabled the companies to transform even dissimilar processes and, in the consequence, to benchmark and enhance them. Additionally, employing the novel simulation software, present processes were configured, under organizational and technical aspects, up to 30 % more energy efficient. The successor project “rebas” (resource efficient development and optimized operations of filling-facilities within the food industry through development of a novel simulation software) will be set up on “reBOP”-generated insights, focusing brewery-facilities. Systematic consideration of all kinds of process related resources and a steadily evolving plant layout planning tool, supported by novel simulations will extend previous generated solutions.

Energy efficiency has become an important objective for industrial companies and its importance is constantly rising. Factory planning plays an important role to reach the challenging goals for energy efficiency, because energy consumption can be influenced at early planning stages more effectively. Existing methods with the goal to increase energy efficiency can only be used during factory operation, because they need detailed quantitative insights into a process. Furthermore, they mainly provide scientific support for the analysis rather than for the identification of improvement measures. Therefore, a concept has been developed to systematically identify energy efficiency measures on the basis of qualitative information about a process. The basic idea is to define fundamental energy efficiency approaches and to make them available for factory planning participants in a systematic and structured manner. The overall concept and the steps that are necessary for the development of this concept are presented in this paper. The approach is explained by means of a case example dealing with internal transport planning, which represents an important part of factory planning. Based on this, potentials and limits of use as well as further research needs are deduced.

Improving energy efficiency in manufacturing has to be considered from a holistic perspective. Investigating and optimizing manufacturing processes in an isolated manner may neglect possible energy intensive pre- and post-processes, and thus may miss an overall optimum. Instead, the whole process chain has to be accounted for being able to find an optimum for the production of a certain product. The presented method for the evaluation of process chains therefore integrates a detailed analysis of the core as well as necessary pre- and post-processes, and enlarges this approach for a factory wide optimization. Single steps of a process chain are energetically modeled using a detailed mapping of each step’s energy profile, generalized by investigating the product variant related energy profiles for each machine. The result provides the base for improving the energy efficiency of a factory as well as for calculating the embodied energy of a product, fostering the energetically optimization of its manufacturing processes. Furthermore, factories in most cases produce multiple variants of similar products, requiring an optimization not for one product but for the overall product mix of the considered manufacturing site. The introduced method is therefore extended following a sustainability technology roadmap approach.

Advancing climate change and rising prices for fossil resources and therefore industry supplies call for answers that go beyond optimizing our current use of resources and energy in production. The green cycle vision presented looks at carbon (C) for green production and green raw materials. This opens up new production models and new product markets to provide an answer for the world’s hunger for materials. One driver for this development is the merging of the different energy grids. Our future vision is that CO

2

is the main source for green production businesses. The prerequisites will be CO

2

-neutral forms of renewable energy and chemistry production technologies.

In the context of sustainability and for strengthening the competitiveness of manufacturing systems, energy efficiency becomes a more and more important objective for industrial processes. For designing energy-efficient systems and processes, new or improved tools and methods focusing energy efficiency are needed. Furthermore, detailed energy data, information, and knowledge are required for energy efficiency improvements. However, in practice, these are often not available in the appropriate form. This leads to the need to illustrate the issue “energy” in a tangible and visible form. Energy Management as an organizational instrument helps to consider energy efficiency in planning and operation tasks. Energy Labels are useful tools for benchmarking similar goods. Though, they are not available for different systems of a factory. The presented tool “Energy Cards” bundles energy data of a system and enables the transfer of energy information and knowledge in a structured and clear manner. In this article, the basic concept and the structure of the Energy Cards are described. In addition, some prototypes of digital cards are presented. An example on process modeling illustrates some possibilities of application.

The importance of performance measurement and indicators in realizing energy-efficient and, in broader perspective, sustainable manufacturing has been noticed and realized by the industry and academia. Although several frameworks for sustainability performance measurement and reporting exist, those focus mainly on corporate level and hence fail to provide adequate support for factory planning and management. This paper and the related research projects are motivated by this need to provide manufacturing companies with sustainability performance indicators that better support the realization of sustainable and energy-efficient manufacturing. The proposed paper aims to set the stage and to present the initial steps for identifying or developing sustainability key performance indicators that cover the three aspects of sustainability, economic, social, and environmental, and are linked to the improvement possibilities and measures at shop-floor level. The proposed paper contributes to the conference and the workshop by discussing performance indicators for planning and management of sustainable and energy-efficient factories. The paper presents guidelines and research needs for academia, while the related research projects intend to provide the industry with useful sustainability performance indicators for factory planning and management.