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The purpose of this paper is to investigate the factors that enable total quality management (TQM) implementation in the readymade garment (RMG) sector of Bangladesh. More specifically, the present study is a supplement of the previous call from research to investigate the TQM-enabling factors from a broader aspect of organizational change.

This study was conducted through an online survey, followed by phone calls. Data were collected using a questionnaire survey with 256 respondents of the Bangladeshi RMG sector. The TQM-enabling factors were divided into five distinct groups, based on strategic or overall changes required within an organization for TQM implementation. A theoretical research model was created to investigate the contingency of various TQM-enabling factors. Structural equation modeling (SEM) was applied to confirm the factor that enabled TQM implementation in the RMG sector of Bangladesh.

The main finding of this study shows that structural, strategic, contextual and human resource-enabling factors are significant to TQM implementation in the Bangladeshi RMG sector.

This study has been completed in single time frame. Therefore, consideration of the time factor is completely ignored in this research. Furthermore, understanding of TQM-enabling factors in this research relied on quantitative findings only. Also, this study was limited to one industry and one geographic region. However, this study could determine whether data triangulation will provide a good perception on enabling factors and the methodology can be extended to other industries and regions.

This study provides a research methodology for other manufacturing industries that are planning to implement TQM in their organization. This research will contribute to the existing literature by examining the contingency of various TQM-enabling factors in the context of the Bangladeshi RMG sector, and it, therefore, provides direction to increase the success rate of TQM implementation. Furthermore, the research methodology can be used in other studies for variation of contextual variables such as size of the industry, developed or underdeveloped country and manufacturing or service industry.

The methodology used in this study can lead the way for other industries in the RMG sector that implements TQM in their organization. Also, this research further contributes to the existing literature by investigating the contingency of various TQM enabling factors in the context of the Bangladeshi RMG sector and developing associated strategies to raise success rate of TQM implementation.

The purpose of this study is to integrate two well-established frameworks with an aim to reduce the unwanted rejection rate recurring in the drug production process in pharmaceutical industries. The effectiveness of an integrated framework has been demonstrated by a real-time case study in a complex industrial environment, providing a platform for quality tools application in the pharmaceutical industry.

The hazard analysis and critical control points (HACCP) provided a basic framework for hazard analysis and its blending with statistical process control (SPC) aided in data-driven decision-making. The extensive brainstorming and Pareto analysis helped to identify potential critical-to-quality characteristics followed by SPC, x¯ and R charts, histograms and C_p and C_pk analysis to spot the critical control point. The fishbone diagram led to the extraction of the leading cause behind the identified problem. Then, based on recommended corrective actions, control limits were adjusted and the process was brought into control. Finally, a product-based cost analysis is also performed to illustrate the financial impact resulting from the proposed method’s successful implementation.

The integrated framework is applied to a drug production process which has a higher rejection rate (3%) because of the non-conformities. Based on Pareto analysis, potential failure causes were classified and prioritised as inappropriate composition (2.54%), packaging (0.35%), out-of-specification (0.069%), equipment failure (0.022%), input materials (0.018%) and miscellaneous (0.002%). It is found that 84% of the total rejection rate is contributed by inappropriate composition. After taking corrective actions, it is observed that the proposed method has helped to reduce the process rejection rate significantly (2.54-0.82%). In the monetary terms, 2.50% decline per unit costs is noted in this case study work. The proposed integrated framework’s success is further motivating other pharmaceutical industries to implement and expand it to other processes.

The case study is an attempt to contribute to the existing literature of quality management in pharmaceutical industries. In particular, it is a novel example to introduce the simple and user-friendly SPC tool into well-established HACCP framework to enhance its effectiveness in hazard identification. The case study results motivate managers to adopt quality techniques for achieving a higher quality standard and operational excellence.

Increasing scarcity of natural resources and the adverse effects of unsustainable practices call for more and more efficient management strategies in the energy industry. The quality of the coke plays a significant role in the quality and durability of the output steel which is produced using the energy from the coal. This paper aims to investigate the dynamic coal blending problem under overall cost and coke quality constraints in the steel industry within a periodic cycle of operations.

Considering the variability of the natural properties over a periodic cycle, this study proposes a multi-period mixed-integer non-linear programming formulation to optimize the total blending costs while taking various coke quality constraints into account. Besides, this study applies factorial design to investigate about the significant effect of coal proportions as well as improvement into the overall cost of blending.

In this case study, utilizing real data from a coal blending facility in India, through a factorial design, the authors obtain optimal desirable levels of coal proportions and their criticality levels towards the total cost of blending (TCB) or objective function. This analysis reflects the role of the coke quality constraints in the objective function value while characterizing the price of sustainability for the case study among other critical insights.

Objective function (or TCB) includes basic coal cost, movement cost and environmental costs during the coal and coke processing at a coke-oven and blast furnace of steel industry. The price of sustainability provides managerial insights on that sacrifices the industry has to make in order to become more “sustainable”.

The purpose of this paper is to classify different conditions of the rolling element bearing (REB) using vibration signals acquired from a customized bearing test rig.

An effort has been made to develop health index (HI) based on singular values of the statistical features to classify different conditions of the REB. The vibration signals from the normal bearing (N), bearing with defect on ball (B), bearing with defect on inner race (IR) and bearing with defect on outer race (OR) have been acquired from a customized bearing test rig under variable load and speed conditions. These signals were subjected to “modified kurtosis hybrid thresholding rule” (MKHTR)-based denoising. The denoised signals were decomposed using discrete wavelet transform. A total of 17 statistical features have been extracted from the wavelet coefficients of the decomposed signal.

Singular values of the statistical features can be effectively used for REB classification.

REB are critical components of rotary machinery right across the industrial sectors. It is a well-known fact that critical bearing failures causes major breakdowns resulting in untold and most expensive downtimes that should be avoided at all costs. Hence, intelligently based bearing failure diagnosis and prognosis should be an integral part of the asset maintenance and management activity in any industry using rotary machines.

It is found that singular values of the statistical features exhibit a constant value and accordingly can be assigned to each type of bearing fault and can be used for fault characterization in practical applications. The effectiveness of this index has been established by applying this to data from Case Western Reserve University data base which is a standard bench mark data for this application. HIs minimizes the computation time when compared to fault diagnosis using soft computing techniques.

The main purpose of the study was to analyze the relationship between cutting forces and tool wear during turning of steel 30CrNiMo8.

It is very important to find the optimal machining conditions to increase the tool life and to improve product quality. Width of tool wear was measured by universal microscope.

During experimental procedure, one chip shape was obtained for the given machining parameters. Results showed negligible tool wear for the given experimental conditions. In other words, the tool wear is negligible for one chip shape.

To increase tool wear, there are different chip shapes.

The purpose of this paper is to analyze abnormal behavior patterns in a maintenance outsourcing process. Based on the results, the managers can focus on the abnormal behavior and the direction of the investigation can be narrowed. The abnormal behavior can be identified more easily.

Maholanobis Distance (MD) and Decision Tree (DT) are integrated to analyze for abnormal behavior patterns. To prevent abnormal behaviors, a maintenance outsourcing case must be passed by several managers in different departments. In this research, some criteria for pairs of managers are calculated first. Based on the criteria, the MDs of these pairs can be calculated. Pairs are categorized by their MDs. Any pair whose MD is higher than a threshold is labeled “abnormal” while the remaining are labeled “normal”. After oversampling the minority class of abnormal, a DT is built by Classification and Regression Trees (CART) based on the labeled dataset. Finally, the combination of criteria for abnormal categories is extracted from the tree.

Through the results from the DT, the combinations of criteria provide obvious characteristics of cases that are categorized as abnormal, and then provide a direction for investigators. Thus, the range of investigation can be narrowed. The empirical results show that the result of the proposed integrated methodology is helpful for abnormal behavior pattern analysis.

This research is intended to help an organization to enhance their investigation in a large number of maintenance outsourcing cases. About 8,000 cases are collected for analysis.

The integration of MD and DT for analyzing abnormal behavior patterns in a maintenance outsourcing process is not found in the literature. Moreover, the empirical results show that the proposed integrated methodology is helpful in a real application.

With respect to multiple attribute group decision-making (MAGDM) in which the assessment values of alternatives are denoted by normal discrete fuzzy variables (NDFVs) and the weight information of attributes is incompletely known, this paper aims to develop a novel fuzzy stochastic MAGDM method based on credibility theory and fuzzy stochastic dominance, and then applies the proposed method for selecting the most desirable investment alternative under uncertain environment.

First, by aggregating the membership degrees of an alternative to a scale provided by all decision-makers into a triangular fuzzy number, the credibility degree and expect the value of a triangular fuzzy number are calculated to construct the group fuzzy stochastic decision matrix. Second, based on determining the credibility distribution functions of NDFVs, the fuzzy stochastic dominance relations between alternatives on each attribute are obtained and the fuzzy stochastic dominance degree matrices are constructed by calculating the dominance degrees that one alternative dominates another on each attribute. Subsequently, calculating the overall fuzzy stochastic dominance degrees of an alternative on each attribute, a single objective non-linear optimization model is established to determine the weights of attributes by maximizing the relative closeness coefficients of all alternatives to positive ideal solution. If the information about attribute weights is completely unknown, the idea of maximizing deviation is used to determine the weights of attributes. Finally, the ranking order of alternatives is determined according to the descending order of corresponding relative closeness coefficients and the best alternative is determined.

This paper proposes a novel fuzzy stochastic MAGDM method based on credibility theory and fuzzy stochastic dominance, and a case study of investment alternative selection problem is provided to illustrate the applicability and sensitivity of the proposed method and its effectiveness is demonstrated by comparison analysis with the proposed method with the existing fuzzy stochastic MAGDM method. The result shows that the proposed method is useful to solve the MAGDM problems in which the assessment values of alternatives are denoted by NDFVs and the weight information of attributes is incompletely known.

The contributions of this paper are that to describe the dominance relations between fuzzy variables reasonably and quantitatively, the fuzzy stochastic dominance relations between any two fuzzy variables are redefined and the concept of fuzzy stochastic dominance degree is proposed to measure the dominance degree that one fuzzy variable dominate another; Based on credibility theory and fuzzy stochastic dominance, a novel fuzzy stochastic MAGDM method is proposed to solve MAGDM problems in which the assessment values of alternatives are denoted by NDFVs and the weight information of attributes is incompletely known. The proposed method has a clear logic, which not only can enrich and develop the theories and methods of MAGDM but also provides decision-makers a novel method for solving fuzzy stochastic MAGDM problems.

The purpose of this study is to propose an innovative methodology in solving the lean production design from semiconductor crystal-ingot pulling manufacturing which is an important industry. Due to the complexity of the system, it is computationally prohibited by an analytical approach; thus, simulation optimization is adopted for this study.

Four control factors that affect the system’s performance, including the pulling strategy, machine limitations, dispatching rules and batch-size control, are identified to generate the future-state value stream mapping. Taguchi two-step procedure and simulation optimization are used to determine the optimal parameter values for a robust system.

The proposed methodology improved the system performances by 6.42 and 12.02 per cent for service level and throughput, respectively.

This study does not investigate operations management issues such as setup reduction, demand forecasting and layout design.

A real-world crystal-ingot pulling manufacturing factory was used for the case study. The results are promising and are readily applied to other industrial applications.

The improved performances, service level and throughout rate, can result in an improved customer satisfaction level and a reduced resources consumption, respectively.

The proposed methodology innovatively solved a practical application and the results are promising.

The purpose of this paper is to propose a modified Importance-Performance Analysis (IPA) model and calculates the performance of quality characteristic for the purpose of defining quality improvement strategy.

This study developed modified IPA by introducing the Mahalanobis Distance and multiple regression analysis to evaluate the performance gap and implicit importance of quality characteristics. This paper used a large air-conditioning manufacturer in Taiwan as the case analysis and study targets. It discussed and validated the modified IPA analytical results by studying case history and market analysis.

Through the case study, the quality characteristics of air-conditioning product and service needed to be improved immediately are Green product (Q3) and Repair service (Q10), and the Price (Q11) and Serviceability (Q2) could be kept or enhanced to win the market competitive advantages.

This study developed a modified IPA to help organization identifying key quality characteristics of product and service, and choosing its improvement strategies to win the market competitive advantages effectively.

The purpose of this paper is to investigate and minimize the printing-related defects in the surface mount assembly (SMA) process.

This paper uses an experimental approach to explore process parameter and printing defects during the SMA process. Increasing printing performance, various practices of solder paste (Ag3.0/Cu0.5/Sn) storage and handling are suggested. Lopsided paste problem is studied by varying squeegee pressure and the results are presented. Unfilled pads problems are observed for ball grid array (BGA) and quad flat package (QFP) which is mitigated by proper force tuning. In this paper, a comparative study is conducted which evaluates the manifestation of printing offset due to low-grade stencil. The input/output (I/O) boards were oxidized when the relative humidity was maintained beyond 70 per cent for more than 8 h. This pad oxidation problem is overcome by proper printed circuit board (PCB) handling procedures. When the unoptimized line is used, the paste wedged in the stencil and influences the performance of the screen printer, for this reason, an optimized line is proposed that minimize the printing defects.

The key findings are as follows: in the SMA process, printing quality is directly associated with solder paste quality. Experimentally, it is observed that a considerable variance in solder deposition occurred when the front and rear squeegee have different configurations. High-grade and unsoiled stencil results in superior paste deposition and less distinction. Insufficient solder paste and bridge problems also occur in printing when PCB pads are oxidized. Optimized line resolves solder paste clog issues, associated with stencil’s aperture. The cooling arrangement on the conveyor, after reflow, explicates hot jig problem. Control environmental conditions minimized static charges and printing defects.

The preceding studies emphasis mostly on the squeegee pressure, while other important parameters are not completely investigated. Moreover, it is very imperative to concurrently measure all parameters while varying the environmental conditions. This study highlights and provides an experimental approach to various PCB printing defects, and a comparative study has been conducted that concurrently measure all process parameters.