Operations Management and Systems Engineering

Different parts of a mechanical assembly are usually manufactured at different units so as to be assembled later. The assembled parts must fit together without any interference or unnecessarily large clearance. This paper presents the study of the effect of variation in dimensions of individual parts on the assembly response using Monte Carlo simulation. This technique represents the process distribution of the dimensions of individual parts, which helps in determining the assembly response and yield estimation of successful assembly. A case study on a cylinder-piston assembly has been attempted. The simulation has been carried out using MATLAB 7.0 with different theoretical process distributions (uniform, normal, and beta) and yield has been estimated. The aim of this study is to establish a simple yet powerful technique (Monte Carlo simulation) for tolerance analysis and yield estimation of mechanical assemblies. This approach quantifies and handles both the normal and non-normal process distributions.

Service and service activities are perishable, complex, and multifunctional in nature, because of which the production and delivery of services are inseparable. Services in manufacturing, however need to be treated in a different manner. In a manufacturing organization, while early market leaders focus on innovation, the quality of services rendered along the supply chain would help in developing loyal customers, resulting in enhanced business performance. Research demonstrates that service quality (SQ) has strong linkages with business performance, cost reduction, feeling of delight, trust, and loyalty among partners and consequently leads to profitability. However, the service dominance perspective that establishes the importance of intangible aspects such as service and relationship is still to be widely embraced in the manufacturing sector. The scholarly attention accorded to service quality in manufacturing is still in its nascence. Against this preamble, this chapter aims to bring out a tailor-made framework to evaluate SQ at different interfaces of a manufacturing supply chain. This chapter conceptualizes SQ as a multidimensional construct, which operates at interfaces of supplier–manufacturer, manufacturer–employee, and manufacturer–distributor.

The aim of this research work is to develop a novel integrated framework for improving the availability of Water Circulation System (WCS) of a thermal power industry located in the northern part of India. Qualitative information related to system’s operation has been collected on the basis of feedback from maintenance experts/log book record and using that information, Failure Mode and Effect Analysis (FMEA) sheet was generated. Fuzzy ratings have been assigned by the experts on the basis of designed linguistic scale for three risk factors, namely occurrence probability (O), severity probability (S), and detection probability (D). Fuzzy Risk Priority Number (FRPN) has been computed for each failure cause and ranking was done in descending order. Further, for testing the stability and robustness of ranking results fuzzy Evaluation Based on Distance from Average Solution (EDAS) approach has been applied within fuzzy FMEA approach. Appraisal score values have been computed as EDAS output and ranking of failure causes was done. Ranking results were compared for effective decision-making of critical failure causes. The implork shows its effectiveness in overcoming the limitations of rule base FMEA approach. The ranking results would be supplied to the maintenance manager of the plant for developing an effective maintenance program for WCS. The analysis result will be highly useful in minimizing the total operational cost of the considered unit.

The key concern in competitive market is to maximize the performance as well as growth of the organization. To perform better among their competitors, every industry/company is trying to identify the critical success factors (CSFs) which will enable them to implement the latest technology changes in order to set a long-term sustainable edge. The present research identifies the critical success factors to enactment of Information Technology (IT) structure for better supply-chain performance system in auto industry particularly under Indian context. The aim of present research work is to recognize and examine the CSFs for implementing the IT-enabled supply-chain performance system. To achieve the aim, various success factors (SFs) were recognized on the basis of literature review/expert’s opinions and “Interpretive Structural Modeling” (ISM) with preference rating has been applied as a hybrid approach. Through ISM, interrelationships among the identified SFs have been determined. To know the driving and dependence behavior of considered success factors, this model was developed and to visualize the “driving power” and “dependence power” relations, MICMAC analysis was accomplished. After that based on ISM model leveling (through cluster), a list of “critical success factors” (CSFs) was formulated in order to prioritize them using preference rating approach. The findings of the present research work may be helpful for managers in forming strategies/policies for implementing the IT-enabled supply-chain performance system effectively and efficiently.

Managers are using metrics such as productivity, quality and low costs, to reach their objectives and keep companies success; however, customer expectations in the twenty-first century are not only including deliveries on time, good quality, and low costs; but they are also looking for values such as long term commitment, strategic integration and innovation as competitive values. For the mentioned conditions, today’s managers need to learn how to adapt to such challenges by using flexible methodologies that help them to integrate more qualitative requirements to the conventional metrics. For this challenge recently, Lean-Sigma has proven to be a flexible and adaptable methodology that can incorporate such requirements. For proving this concept, this chapter describes a case study in which the initial valuation of the metrics shows that a product has been delivered as expected with the quality and productivity values in the best levels. However, the customer perception is different and product competitiveness is at risk, signals that the operations management presented as a priority requiring actions and a later solution. Using the Voice of the Customer (VoC) and Lean-Sigma, this study focuses in an operation framed in the automotive industry. The assembly process is the target in specific in the cutting step of rubber hoses, which have to measure different lengths depending on the product models. At first sight, with a production rate of 1000 pieces per hour, the 7 complains in a year looks as expected for the variability in the process. However, the quality perception and confidence of the customer are at risk. Actions were taken and in two weeks the team incorporated the qualitative requirements to the operations’ quantitative targets and responded to the customer concerns and kept the product competitiveness. The adjustments and implementations results are reflected in the measured values at the cutting process, achieving an 80% reduction in the process’ variation, and an increment in the capability index (Ppk) from 0.97 to 1.97.

Manufacturing industries consume different types of resources while manufacturing their products as well as offering services. This consumption of resources, particularly diminishing natural resources, has been hazardous and causing serious losses to the environment and hence to the earth as well as animal and plant life. Most of the manufacturing organizations have realized the need of corrective actions towards this destruction. They have also realized the importance of adopting sustainable practices for their manufacturing activities to survive in the intense competition at local as well as global level. Thus, the Sustainable Manufacturing (SM) has been gaining increasing importance. Research so far in SM does not offer an easy to adopt, integrated and holistic approach towards implementing SM. Most of the researchers have mentioned the need of a comprehensive framework or a model for the adoption of SM practices with due importance to ‘manufacturing and technology’ domain over to three conventional domains of sustainability, i.e. economic, social and environmental. The main aim of this paper is to address this need by proposing a basic framework of four domains and hence to develop a Partial Least Square—Structural Equation Modelling (PLS-SEM) model validated using SmartPLS software for the analysis of empirical data of Indian Engineering Manufacturing industries. The results of model fit analysis revealed quite satisfactory performance of the ‘manufacturing and technology’ domain with acceptable level of control over the adverse impact on environment and a need for enhanced attention towards social domain. Authors of this paper expect that this study will provide a systematic approach for the implementation of SM in manufacturing industries so as to enhance the decision-making towards controlling adverse impact of manufacturing-related activities.

In the customer-centric marketplace, it is getting increasingly important to add value in services being delivered to customers. The service quality rendered to consumers results in developing loyal customers, which helps to yield enhanced business performance. The present study tries to study the service quality being imparted to stakeholders by a well-established group of technical institutions located in North India established since 2001. This study is carried out through a specific case study tool named as SAP-LAP (Situation-Actor-Process–Learning-Action-Performance) methodology from the stakeholders’ point of view. The analysis brings out six service quality factors, namely, leadership, process management, people management, resource management customer satisfaction, and customization to influence the outcome in terms of placements, reputation, growth, and sustainability of such institutions.

In the current competitive structure of the manufacturing industries, the qualitative decision-making has become an issue of paramount prominence to solve the real-life industrial environment based problems. It becomes further more complex when the decision maker has to be in concern with the multiple constraints at one time. The present article has targeted to select the optimum hole quality conditions for performing ultrasonic machining of a selected composite material through multiple criteria decision-making (MCDM) approaches. The experimentation has been designed according to the Taguchi’s methodology. The hole quality based attributes (out of roundness, hole over size and conicity) have been studied under the influential situations of several selected input variables namely; thickness of workpiece, cobalt content, tool profile, power rating, material of tool and grit size. In addition, two different MCDM approaches called as the additive ratio assessment (ARAS) technique, and the TOPSIS method have been attempted for the selection of the best optimum condition that can offer fruitful hole quality based outcomes for the considered manufacturing environment problem. The optimality function and the specific alternative to the perfect solution to observe the best available alternative have been computed as per the ARAS, and the TOPSIS techniques, respectively. Results revealed that, for both the explored MCDM methods, the 9th experimental run offers the highest value of the calculated hole quality attribute index. This particular conducted test is entailing of the parametric blend as; cobalt content—24%, workpiece thickness—3 mm, tool profile—hollow, material of tool—stainless steel, abrasive grit size—500 (mesh size) and power rating—80%.

CNG is considered a low maintenance cost and environment friendly fuel. Its use as an alternative fuel has surged in cities having CNG stations. Due to limited number of CNG stations, there is a substantial gap between demand and supply of CNG fuel. CNG dispensing unit is an important system of CNG station. Extended operation of dispensing unit is required for delineating this gap. For this, availability and reliability of CNG dispensing unit should be high. The present study reviews and exemplifies the fuzzy reliability analysis approach for behavioural analysis of CNG dispensing unit. The reliability block diagram and fuzzy Lambda-Tau approach have been used for evaluating reliability parameters. Fuzzy methodology has been used for representing failure rate and repair time. In present research work a comparative study of conventional fuzzy theory and vague theory has been expounded. The crisp reliability input and output data have been fuzzified using extension principle and alpha-cut approach. The fuzzy output has been defuzzified for assessing the system behaviour. The results of the study were communicated to system analyst and maintenance engineer.

Exposure of human operator to whole-body vibration generated from tractors has been associated with low back pain (LBP) and degeneration of intervertebral disc. Researchers related the ischial tuberosities with the theory of evenly distributed pressure and found that pressure at the ischials decreased when the seat is more comfortable. This paper concentrates on the assessment of prevalence of MSDs and related ill effects among tractor operators and non-tractor operators during driving. The study was carried out on 80 active operators, out of which 40 (50%) were tractor operators and 40 (50%) were nontractor operators. All the participants were aged between 20 and 50 years old and taken from the region of Punjab, India. The results revealed that tractor operators reported more health-related problems (LBP, neck pain and shoulder pain, etc.) in comparison to non-tractor operators. Work-related musculoskeletal symptoms,i.e. LBP in 70% of operator, neck pain in 60% of operator and shoulder pain in 43% of operator were greatest among tractor operators. It can be concluded that tractor operators are more prone to MSDs occurred due to WBV. Thus, providing a cushion on the seat during operation may cause operation more comfortable and the operator may experience less prevalence of LBP, neck pain and shoulder pain. Further, this paper concentrates on the assessment of ride comfort and related ill effect among tractor operators, those who use cushion and not use cushion on the seat. The second phase of study was done on 40 tractor operators, out of which 25 (62.5%) tractor operators use cushion on tractor seat and 15 tractor operators (37.5%) did not use cushion on the seat. Most of the tractor operators stated that cushion on the seat is more supportive and also give them more comfort. The result also indicated that the tractor operators, who used cushion on the seat, reported less health-related problems (LBP, neck pain and shoulder pain, etc.). Work-related musculoskeletal symptoms were greatest, i.e. LBP (87%), neck pain (87%) and upper back pain (33%) among those tractor operators who did not use cushion on the seat during driving. It was found that cushions made of any fabric material are better than cushionless driving seat. Thus, it can be concluded that tractor operators who used cushion on the seat during driving were more comfortable and experience less prevalence of LBP, neck pain and upper back pain.

Simulation is a vital tool for validation of methods and architectures in the complex manufacturing environment before there application on shop floor for the production process. Manufacturing simulation, digital engineering tools and procedures have a positive impact on the manufacturing industry. Simulation models have been extensively used in manufacturing to enhance the design, planning and productivity of the processes. In manufacturing environment, crucial material movement, is controlled by various dynamic factors. Situations becomes cumbersome for assembling plants which deal with multi-product, owing to the dominance and interconnectedness of dynamic factors. Analysing of these factors in real-life business environment is very complex in nature and required the use of modelling and simulation tools. This chapter glimpses modelling and simulation application, in a multi-product automobile gear manufacturing plant, aimed for development of an efficient production system that expresses ability for assurance of timely product deliveries at minimal cost. For three distinct type of gear production lines, simulation-based models were developed using Arena^® Simulation Software. The proposed simulation model is capable enough to increase the resource’s utilization rate and production rate of gear manufacturing process by identifying the bottlenecks in the manufacturing system. The models developed are capable enough to be synchronized with the company’s other products and hence aids in highly precise production planning and scheduling exercises within the company.

Manufacturing companies are under the stress to give best quality products at minimum cost within the minimum delivery time, in spite of unpredictable economic conditions. Due to global competition like improved customer satisfaction and minimum cost, the organizations are thinking for innovative methods for creating competitive advantage. One such way is the collaboration among all the members of supply chain. To understand supply chain collaboration, we have to know the driving forces of collaboration within the supply chain. In this study, from the relevant literature and the advices of an expert team composed of technical and managerial of the manufacturing firms and academicians, 20 collaborative drivers have been diagnosed. An ISM-based model has been formed to study the understanding of the collaborative drivers in adopting supply chain collaboration within a manufacturing organization. We propose the ISM model, and an MICMAC investigation is done. Its practical significance is to make use of the decision-makers’ knowledge to give a fundamental understanding of a complicated situation, followed by a course of action for problem-solving.

We review the type of toxic substances that exist in e-waste, their impact on environment, health of human beings, and management approaches that are being used to manage e-waste in some developed countries. Several tools like Material Life Cycle Assessment (LCA), Extended Producer Responsibility (EPR), Multi-Criteria Analysis (MCA), and Flow Analysis (MFA) are being used for the management of e-waste in developed countries. Multiple tools working together coherently are required to resolve the e-waste problem.