- Department of Industrial and Production Engineering, Bangladesh University of Engineering and Technology. Dhaka 1000. Bangladesh.
- +8801916034096
Due to the increasing popularity of cost-based outsourcing and growing stakeholder concern about environmental, social, and technological issues, supply chain sustainability is vital in both developed and emerging economies. Bangladesh is... more
Due to the increasing popularity of cost-based outsourcing and growing stakeholder concern about environmental, social, and technological issues, supply chain sustainability is vital in both developed and emerging economies. Bangladesh is an emerging economy and wood industry of Bangladesh is suffering from severe sustainability issues besides its growth. Hence, this article aims to examine the critical success factors (CSFs) for sustainability in the Bangladeshi wood industry, which is crucial to help supply chain managers engage in achieving sustainable development goals. This research investigated the CSFs and uncovered their interdependencies through the development of a methodology integrating a literature review, principal component analysis (PCA), interpretive structural modelling (ISM), and Matriced Impacts Croises Multiplication Appliquee aunClassement (MICMAC) techniques. PCA (n = 150) was used to identify and rank the CSFs for sustainability in the Bangladeshi wood indust...
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There is an increasing rate of occurrence of natural or human-made calamities in the present time. So,the issue of humanitarian supply chain needs more attention with strategic and planned approaches. To control the occurrence of... more
There is an increasing rate of occurrence of natural or human-made calamities in the present time. So,the issue of humanitarian supply chain needs more attention with strategic and planned approaches. To control the occurrence of calamities and to strengthen the post calamities relief system, professionals and academics are giving importance to several driving factors of the humanitarian supply chain. Public and private sectors of Bangladesh lack in expertise and planned infrastructure to tackle the adverse effect of disasters. This paper aims to find out the ranking and contextual relationships of the critical success factors (CSFs) of the humanitarian supply chain in the context of Bangladesh. An interpretive structural modeling (ISM) approach along with MICMAC (Matriced' Impacts Croisés Multiplication Appliquée á unClassement) analysis has been undertaken in this study to depict the relative dependence and driving power among the identified critical success factors. ‘Governme...
Warehouses constitute a key component of supply chain networks. An improvement to the operational efficiency and the productivity of warehouses is crucial for supply chain practitioners and industrial managers. Overall warehouse... more
Warehouses constitute a key component of supply chain networks. An improvement to the operational efficiency and the productivity of warehouses is crucial for supply chain practitioners and industrial managers. Overall warehouse efficiency largely depends on synergic performance. The managers preemptively estimate the overall warehouse performance (OWP), which requires an accurate prediction of a warehouse’s key performance indicators (KPIs). This research aims to predict the KPIs of a ready-made garment (RMG) warehouse in Bangladesh with a low forecasting error in order to precisely measure OWP. Incorporating advice from experts, conducting a literature review, and accepting the limitations of data availability, this study identifies 13 KPIs. The traditional grey method (GM)—the GM (1, 1) model—is established to estimate the grey data with limited historical information but not absolute. To reduce the limitations of GM (1, 1), this paper introduces a novel particle swarm optimizati...
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This paper aims to identify, evaluate, and measure the ergonomic factors hampering the production of leather garment-based small and medium-sized enterprises (SMEs). Ergonomic problems faced by the workers largely impact the health of... more
This paper aims to identify, evaluate, and measure the ergonomic factors hampering the production of leather garment-based small and medium-sized enterprises (SMEs). Ergonomic problems faced by the workers largely impact the health of individuals and also the productivity of a firm. Based on experts’ opinions and a literature survey, three emerging categories—namely, occupational disease, personal factors, and the industrial environment—with a total of twenty factors were identified to examine symmetrical impact in five leather garment companies. In this research work, Cronbach’s α was evaluated to check the validity of the ergonomic factors identified through the literature survey. Then, using the fuzzy analytic hierarchy process (FAHP), the identified ergonomic factors were evaluated. A sensitivity analysis was carried out to validate the robustness of the results obtained using the integrated approach. Outdated machinery, vibration, operational setup, fatigue, and poor ventilatio...
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Measuring productivity is the systematic process for both inter- and intra-organizational comparisons. The productivity measurement can be used to control and facilitate decision-making in manufacturing as well as service organizations.... more
Measuring productivity is the systematic process for both inter- and intra-organizational comparisons. The productivity measurement can be used to control and facilitate decision-making in manufacturing as well as service organizations. This study’s objective was to develop a decision support framework by integrating an analytic network process (ANP) and data envelopment analysis (DEA) approach to tackling productivity measurement and benchmarking problems in a manufacturing environment. The ANP was used to capture the interdependency between the criteria taking into consideration the ambiguity and vagueness. The nonparametric DEA approach was utilized to determine the input-oriented constant returns to scale (CRS) efficiency of different value-adding production units and to benchmark them. The proposed framework was implemented to benchmark the productivity of an apparel manufacturing company. By applying the model, industrial managers can gain benefits by identifying the possible ...
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This paper aims to identify the negative impacts of the COVID-19 outbreak on supply chains and propose strategies to deal with the impacts in the context of the readymade garment (RMG) industry supply chain of an emerging economy:... more
This paper aims to identify the negative impacts of the COVID-19 outbreak on supply chains and propose strategies to deal with the impacts in the context of the readymade garment (RMG) industry supply chain of an emerging economy: Bangladesh. To achieve the aims, a methodological framework is proposed through a literature review, expert inputs, and a decision-aid tool, namely the grey-based digraph-matrix method. A total of 10 types of negative impacts and 22 strategic measures to tackle the impacts were identified based on the literature review and expert inputs. Then, the grey-based digraph-matrix was applied for modeling the strategic measures based on their influence to deal with the impacts. Findings reveal that the strategies “manufacturing flexibility”, “diversify the source of supply”, and “develop backup suppliers” have significant positive consequences for managing the impacts of the COVID-19 pandemic in the RMG supply chain. The findings help industrial managers recover f...
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Reverse logistics (RL) is gradually becoming more important to manufacturing companies through environmental awareness, competitiveness, and environmental regulations. In the leather footwear industry of Bangladesh, it is possible to... more
Reverse logistics (RL) is gradually becoming more important to manufacturing companies through environmental awareness, competitiveness, and environmental regulations. In the leather footwear industry of Bangladesh, it is possible to recycle and reuse waste, meaning a reverse logistics system could increase return-on-investment and give a competitive advantage. To date, studies on barriers to RL implementation have been conducted in other countries and in other domains, leaving a research gap in RL barrier analyses in the leather footwear industry. There are many obstacles to implementing RL in a developing country like Bangladesh; examining these barriers is a crucial research issue. This paper identifies RL barriers through (1) an extent literature review, (2) advice from Bangladeshi industry experts under the Delphi study, and (3) ranking RL barriers using the fuzzy analytical hierarchy process. The results indicate that, of the barriers investigated, the 'knowledge and support' category seems to be most critical. A lack of interest and support from top-level management-related to 'knowledge and support' issues-appears to be the major obstacle for RL implementation in the Bangladeshi leather footwear industry. These findings will help the Bangladeshi leather footwear industry, as well as other industries in Bangladesh, to understand the nature of each barrier and overcome the complexity of RL implementation in supply chains. This study will also assist decision-makers in making certain strategic policies. Future studies may contribute to the life cycle assessment and engineering of recycled and reused footwear.
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Reverse logistics (RL) is gradually becoming more important to manufacturing companies through environmental awareness, competitiveness, and environmental regulations. In the leather footwear industry of Bangladesh, it is possible to... more
Reverse logistics (RL) is gradually becoming more important to manufacturing companies through environmental awareness, competitiveness, and environmental regulations. In the leather footwear industry of Bangladesh, it is possible to recycle and reuse waste, meaning a reverse logistics system could increase return-on-investment and give a competitive advantage. To date, studies on barriers to RL implementation have been conducted in other countries and in other domains, leaving a research gap in RL barrier analyses in the leather footwear industry. There are many obstacles to implementing RL in a developing country like Bangladesh; examining these barriers is a crucial research issue. This paper identifies RL barriers through (1) an extent literature review, (2) advice from Bangladeshi industry experts under the Delphi study, and (3) ranking RL barriers using the fuzzy analytical hierarchy process. The results indicate that, of the barriers investigated, the 'knowledge and support' category seems to be most critical. A lack of interest and support from top-level management-related to 'knowledge and support' issues-appears to be the major obstacle for RL implementation in the Bangladeshi leather footwear industry. These findings will help the Bangladeshi leather footwear industry, as well as other industries in Bangladesh, to understand the nature of each barrier and overcome the complexity of RL implementation in supply chains. This study will also assist decision-makers in making certain strategic policies. Future studies may contribute to the life cycle assessment and engineering of recycled and reused footwear.
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Green supply chain management (GSCM) has emerged as an important issue to lessen the impact of supply chain activities on the natural environment, as well as reduce waste and achieve sustainable growth of a company. To understand the... more
Green supply chain management (GSCM) has emerged as an important issue to lessen the impact of supply chain activities on the natural environment, as well as reduce waste and achieve sustainable growth of a company. To understand the effectiveness of GSCM, performance measurement of GSCM is a must. Monitoring and predicting green supply chain performance can result in improved decision-making capability for managers and decision-makers to achieve sustainable competitive advantage. This paper identifies and analyzes various green supply chain performance measures and indicators. A probabilistic model is proposed based on a Bayesian belief network (BBN) for predicting green supply chain performance. Eleven green supply chain performance indicators and two green supply chain performance measures are identified through an extensive literature review. Using a real-world case study of a manufacturing industry, the methodology of this model is illustrated. Sensitivity analysis is also perf...
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The purpose of this paper is to develop a framework to identify, analyze, and to assess supply chain disruption factors and drivers. Based on an empirical analysis, four disruption factor categories including natural, human-made, system... more
The purpose of this paper is to develop a framework to identify, analyze, and to assess supply chain disruption factors and drivers. Based on an empirical analysis, four disruption factor categories including natural, human-made, system accidents, and financials with a total of sixteen disruption drivers are identified and examined in a real-world industrial setting. This research utilizes an integrated approach comprising both the Delphi method and the fuzzy analytic hierarchy process (FAHP). To test this integrated method, one of the well-known examples in industrial contexts of developing countries, the ready-made garment industry in Bangladesh is considered. To evaluate this industrial example, a sensitivity analysis is conducted to ensure the robustness and viability of the framework in practical settings. This study not only expands the literature scope of supply chain disruption risk assessment but through its application in any context or industry will reduce the impact of such disruptions and enhance the overall supply chain resilience. Consequently, these enhanced capabilities arm managers the ability to formulate relevant mitigation strategies that are robust and computationally efficient. These strategies will allow managers to take calculated decisions proactively. Finally, the results reveal that political and regulatory instability, cyclones, labor strikes, flooding, heavy rain, and factory fires are the top six disruption drivers causing disruptions to the ready-made garment industry in Bangladesh.
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Warehouses constitute a key component of supply chain networks. An improvement to the operational efficiency and the productivity of warehouses is crucial for supply chain practitioners and industrial managers. Overall warehouse... more
Warehouses constitute a key component of supply chain networks. An improvement to the operational efficiency and the productivity of warehouses is crucial for supply chain practitioners and industrial managers. Overall warehouse efficiency largely depends on synergic performance. The managers preemptively estimate the overall warehouse performance (OWP), which requires an accurate prediction of a warehouse's key performance indicators (KPIs). This research aims to predict the KPIs of a ready-made garment (RMG) warehouse in Bangladesh with a low forecasting error in order to precisely measure OWP. Incorporating advice from experts, conducting a literature review, and accepting the limitations of data availability, this study identifies 13 KPIs. The traditional grey method (GM)-the GM (1, 1) model-is established to estimate the grey data with limited historical information but not absolute. To reduce the limitations of GM (1, 1), this paper introduces a novel particle swarm optimization (PSO)-based grey model-PSOGM (1, 1)-to predict the warehouse's KPIs with less forecasting error. This study also uses the genetic algorithm (GA)-based grey model-GAGM (1, 1)-the discrete grey model-DGM (1, 1)-to assess the performance of the proposed model in terms of the mean absolute percentage error and other assessment metrics. The proposed model outperforms the existing grey models in projecting OWP through the forecasting of KPIs over a 5-month period. To find out the optimal parameters of the PSO and GA algorithms before combining them with the grey model, this study adopts the Taguchi design method. Finally, this study aims to help warehouse professionals make quick OWP estimations in advance to take control measures regarding warehouse productivity and efficiency.
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This paper seeks to develop a framework to identify, analyse, and assess the mining industry's key challenges in terms of environmental, operational, and social issues. For each issue, 15 challenges have been identified from experts'... more
This paper seeks to develop a framework to identify, analyse, and assess the mining industry's key challenges in terms of environmental, operational, and social issues. For each issue, 15 challenges have been identified from experts' opinions and from the relevant literature; each is examined in a real-world industrial setting. South India's mining industry is utilized to categorize and to determine crucial challenges based on an identification of their causal relationships. A fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) is used to assess and rank the challenges of each issue. Results reveal that climate change, lack of availability of capital, and unfair wages are the top challenges in the environmental, operational , and social issues, respectively, in India's mining industry. The proposed method is found effective in attaining the causal relationships and ranking amongst the identified challenges. The outcomes help decision-makers and industrial managers to take remedial actions such as adopting new technologies and innovations to protect the environment, improve the operating conditions, and facilitate social benefits to resolve the mining industry's challenges.
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This paper proposes a multi-objective robust-stochastic humanitarian logistics model to assist disaster management officials in making optimal pre-and post-disaster decisions. This model identifies the location of temporary facilities,... more
This paper proposes a multi-objective robust-stochastic humanitarian logistics model to assist disaster management officials in making optimal pre-and post-disaster decisions. This model identifies the location of temporary facilities, determines the amount of commodity to be pre-positioned, and provides a detailed schedule for the distribution of commodities and the dispatch of vehicles. Uncertainties in demand, node reachability by a particular mode of transportation, and condition of pre-positioned supplies after a disaster are considered. Another supposition of this paper is the equity in the distribution of commodities. This paper contributes to the existing literature by adding vehicle flow and multi-periodicity into a robust-stochastic optimisation model. A real-life case study of a flood in Bangladesh shows the applicability of our model. Finally, the findings show that the proposed model can aid decision-makers in allocating resources optimally. ARTICLE HISTORY
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This study develops a mathematical model to mitigate disruptions in a three-stage (i.e., supplier, manufacturer, retailer) supply chain network subject to a natural disaster like COVID-19 pandemic. This optimization model aims to manage... more
This study develops a mathematical model to mitigate disruptions in a three-stage (i.e., supplier, manufacturer, retailer) supply chain network subject to a natural disaster like COVID-19 pandemic. This optimization model aims to manage supply chain disruptions for a pandemic situation where disruptions can occur to both the supplier and the retailer. This study proposes an inventory policy using the renewal reward theory for maximizing profit for the manufacturer under study. Tested using two heuristics algorithms, namely the genetic algorithm (GA) and pattern search (PS), the proposed inventory-based disruption risk mitigation model provides the manufacturer with an optimum decision to maximize profits in a production cycle. A sensitivity analysis was offered to ensure the applicability of the model in practical settings. Results reveal that the PS algorithm performed better for such model than a heuristic method like GA. The ordering quantity and reordering point were also lower in PS than GA. Overall, it was evident that PS is more suited for this problem. Supply chain managers need to employ appropriate inventory policies to deal with several uncertain conditions, for example, uncertainties arising due to the COVID-19 pandemic. This model can help managers establish and redesign an inventory policy to maximize the profit by considering probable disruptions in the supply chain network.
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In recent years, the need for achieving an environmentally sustainable supply chain has become a prominent concern among researchers as well as industry practitioners. However, there exists an insufficiency of comprehensive studies on the... more
In recent years, the need for achieving an environmentally sustainable supply chain has become a prominent concern among researchers as well as industry practitioners. However, there exists an insufficiency of comprehensive studies on the critical factors for environmental sustainability in the context of an emerging economy. To fill this research gap, the present study aims to determine and analyze the critical success factors (CSFs) for implementing Environmentally Sustainable Supply Chain Management (ESSCM) practices considering the readymade garment (RMG) sector of Bangladesh. Initially, fourteen CSFs were sorted-out based on a review of the existing literature. We then held an interactive discussion session with industry experts to screen these candidate CSFs vis-à-vis the RMG industry of Bangladesh. The experts agreed on ten factors that we then processed further intending to understand the contextual relationships and interdependency among them. For this purpose, we applied the Total Interpretive Structural Modeling (TISM) technique. Moreover, we implemented a Cross-impact Matrix Multiplication Applied to Classification (MICMAC) analysis to classify the CSFs according to the influence and dependence level of each factor. Our findings indicate that all the identified CSFs are interrelated and "Effective government policies" is the most dominating CSF that acts independently but influences other CSFs either directly or indirectly. The findings can help motivate managers in the RMG industry to concentrate on the most relevant CSFs, thereby accomplishing ESSCM more effectively in the context of an emerging economy.
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This paper develops an integrated economic model for the joint optimization of quality control parameters and a preventive maintenance policy using the cumulative sum (CUSUM) control chart and variable sampling interval fixed time... more
This paper develops an integrated economic model for the joint optimization of quality control parameters and a preventive maintenance policy using the cumulative sum (CUSUM) control chart and variable sampling interval fixed time sampling policy. To determine the in-control and out-of-control cost for both mean and variance, a Taguchi quadratic loss function and modified linear loss function are used, respectively. Imperfect preventive maintenance and minimal corrective maintenance policies were considered in developing the model, which determines the optimal values for significant process parameters to minimize the total expected cost per unit of time. A numerical example is used to test the model, which is followed by a sensitivity analysis. The integration of CUSUM mean and variance charts with the maintenance actions are proven successful to detect the slightest shift of the process. The findings reveal that among all the cost components, process failure due to external causes and equipment breakdown has a noteworthy attribute to the total costs of the optimized model. It is expected that top managers can utilize the suggested combined model to minimize the costs related to quality loss and maintenance policy and achieve economical advantages as well.
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The global pandemic of COVID-19 has affected most countries and has impacted every household's operations. Mandatory stay-at-home lockdowns have forced building residents to use more energy for their daily routine activities, giving rise... more
The global pandemic of COVID-19 has affected most countries and has impacted every household's operations. Mandatory stay-at-home lockdowns have forced building residents to use more energy for their daily routine activities, giving rise to higher energy usage. The increased energy use by building residents results in high energy bills and leads to a scarcity in the energy supply. Identifying factors that can control the high energy consumption in buildings can be used to optimize energy consumption and act as energy conservation factors. This proposed research is conducted to identify and explore the most influential energy consumption factors amid COVID-19 pandemic in residential buildings using a case study in India. To analyze the energy consumption factors, a Multiple Criteria Decision Making (MCDM) methodology based Best Worst Method (BWM) and a Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodology have been integrated. The results show that among 34 comprehensive energy consumption factors, the high priority topmost 50% of the factors were analyzed. The main research outcome indicates that 53% of the factors were in the cause group and the remaining 47% were in the effect group factors. Research results conclude that in response to COVID-19, social distancing, home quarantine, and home transformation were the primary factors for energy consumption in homes. Among the sub-factors, the lockdown of streets, shutdown of public markets, and psychological factors were the top three factors adding to increased energy consumption. Further, Industrial and economic importance of the research is also discussed. ARTICLE HISTORY
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The occurrence of occupational accidents and injuries has always been a major concern for industrial management. Such undesirable incidences are higher in developing countries, especially in India, than in developed countries. This... more
The occurrence of occupational accidents and injuries has always been a major concern for industrial management. Such undesirable incidences are higher in developing countries, especially in India, than in developed countries. This research aims to identify, analyze and evaluate the faulty behavior risks (FBRs) that trigger occupational accidents and injuries. Using a data triangulation strategy, this study identified 19 FBR factors under five categories. An integrated approach comprising the fuzzy analytic network process (ANP) and the decision-making trial and evaluation laboratory (DEMATEL) method is proposed for assessing these FBRs. The five most prominent critical risk factors are the absence of continuous monitoring, defective equipment and maintenance, cognitive bias, proper signage and adverse ambient working conditions. The study postulates some implications for industrial management to mitigate occupational accidents and injuries based on the outcomes.
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This paper aims to identify the negative impacts of the COVID-19 outbreak on supply chains and propose strategies to deal with the impacts in the context of the readymade garment (RMG) industry supply chain of an emerging economy:... more
This paper aims to identify the negative impacts of the COVID-19 outbreak on supply chains and propose strategies to deal with the impacts in the context of the readymade garment (RMG) industry supply chain of an emerging economy: Bangladesh. To achieve the aims, a methodological framework is proposed through a literature review, expert inputs, and a decision-aid tool, namely the grey-based digraph-matrix method. A total of 10 types of negative impacts and 22 strategic measures to tackle the impacts were identified based on the literature review and expert inputs. Then, the grey-based digraph-matrix was applied for modeling the strategic measures based on their influence to deal with the impacts. Findings reveal that the strategies "manufacturing flexibility", "diversify the source of supply", and "develop backup suppliers" have significant positive consequences for managing the impacts of the COVID-19 pandemic in the RMG supply chain. The findings help industrial managers recover from supply chain disruptions by identifying and classifying the impacts and strategies required to manage the major supply chain disturbances caused by the COVID-19 pandemic. As a theoretical contribution, this study is one of few initial attempts to evaluate the impacts of the COVID-19 outbreak and the strategies to deal with the impacts in the supply chain context.
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Motivated by the COVID-19 pandemic and the challenges it poses to supply chain sustainability (SCS), this research aims to investigate the drivers of sustainable supply chain (SSC) to tackle supply chain disruptions in such a pandemic in... more
Motivated by the COVID-19 pandemic and the challenges it poses to supply chain sustainability (SCS), this research aims to investigate the drivers of sustainable supply chain (SSC) to tackle supply chain disruptions in such a pandemic in the context of a particular emerging economy: Bangladesh. To achieve this aim, a methodology is proposed based on the Pareto analysis, fuzzy theory, total interpretive structural modelling (TISM), and Matriced Impacts Cruoses Multiplication Applique a un Classement techniques (MICMAC). The proposed methodology is tested using experienced supply chain practitioners as well as academic experts' inputs from the emerging economy. This study reveals the influential relationships and indispensable links between the drivers using fuzzy TISM to improve the SCS in the context of COVID-19. Findings also reveal that financial support from the government as well as from the supply chain partners is required to tackle the immediate shock on SCS due to COVID-19. Also, policy development considering health protocols and automation is essential for long-term sustainability in supply chains (SCs). Additionally, MICMAC analysis has clustered the associated drivers to capture the insights on the SCS. These findings are expected to aid industrial managers, supply chain partners, and government policymakers to take initiatives on SSC issues in the context of the COVID-19 pandemic.
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This study examines critical success factors (CSFs) for the implementation of green supply chain management (GSCM) for the electronics industry of an emerging economy. Based on a literature review, a total of 22 CSFs for GSCM... more
This study examines critical success factors (CSFs) for the implementation of green supply chain management (GSCM) for the electronics industry of an emerging economy. Based on a literature review, a total of 22 CSFs for GSCM implementation were selected. Sixteen of the 22 CSFs were finalised using Pareto analysis, based on the feedback of 30 experts from three renowned consumer electronics manufacturing firms in Bangladesh. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was then utilised to capture the interactive relationships among the CSFs. Findings reveal that the CSFs for GSCM implementation are top management commitment, government regulations and standards, pollution prevention and hazardous waste management, and environment management certification (ISO 14000). Findings also show that top management commitment is paramount to GSCM implementation, followed by pollution prevention and hazardous waste management. This study helps industrial managers make strategic and tactical decisions to implement GSCM practices in the electronics industry. ARTICLE HISTORY
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Lean six sigma (LSS), a process improvement tool to achieve operational excellence in any industry, has become popular among practitioners over the last few decades. In this study, a framework for identifying barriers to LSS... more
Lean six sigma (LSS), a process improvement tool to achieve operational excellence in any industry, has become popular among practitioners over the last few decades. In this study, a framework for identifying barriers to LSS implementation in supply chains has been developed using the interpretive structural modeling (ISM) method. The ISM technique was used to identify the contextual relationships among the barriers. Barriers were classified based on their dependence power and driving power using MICMAC (Matriced Impacts Croiseś Multiplication Appliqueé á un Classement). This framework will provide a comprehensive understanding of how the barriers of LSS affect each other. The proposed framework has been tested using data from a real-world apparel manufacturing company in Bangladesh.
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Eco-efficiency and resource optimization for business strategy and the environment can be achieved by the circular economy (CE) practices in supply chains (SCs). The leather industry is a significant industrial contributor to the economic... more
Eco-efficiency and resource optimization for business strategy and the environment can be achieved by the circular economy (CE) practices in supply chains (SCs). The leather industry is a significant industrial contributor to the economic growth of some countries, but at the same time, it leads to tremendous environmental pollution. This research focuses on the identification and evaluation of critical success factors (CSFs) needed in the business strategy development of CE practices as well as to minimize environmental pollution in leather industry SCs. The CSFs are identified via a comprehensive literature review and are validated by experts' opinions. The validated CSFs are further analyzed using the best-worst method (BWM) and the decision-making trial and evaluation laboratory (DEMATEL). The BWM is used to identify the weights of the CSFs, and DEMATEL is used to determine the cause-effect relationship between the CSFs. The findings show that "leadership and top management commitment" is the most important CSF. Six CSFs are classified as causal towards CE practices: "leadership and top management commitment," "strong legislation towards CE practices," "ecological scarcity of resources," "knowledge of CE practices," "funding support for R&D from the government," and "competitor pressure on CE practices." The findings of this study can help managers in the leather industry implement CE practices in their existing SCs to minimize waste. K E Y W O R D S business strategy, BWM, circular economy, critical success factors, DEMATEL, environmental protection, leather industry, resource optimization
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The recent emergence of data-driven business markets and the ineligibility of traditional data management systems to trace them have fostered the application of Big Data Analytics (BDA) in supply chains of the present decade. Literature... more
The recent emergence of data-driven business markets and the ineligibility of traditional data management systems to trace them have fostered the application of Big Data Analytics (BDA) in supply chains of the present decade. Literature reviews reveal that the successful implication of BDA in a supply chain mainly depends on some key drivers considering the size and operations of an organization. However, collective analysis of all these drivers is still neglected in the existing research field. Therefore, the purpose of this research is to identify and prioritize the most significant drivers of BDA in the supply chains. To this aim, a novel Best-worst method (BWM) based framework has been proposed, which has successfully identified and sequenced the twelve most significant drivers with the help of previous literature and experts' opinions. Theoretically, this study contributes to the BDA literature by offering some unique drivers to BDA in supply chains. The findings show that 'sophisticated structure of information technology' and 'group collaboration among business partners' are the top most significant drivers. 'Digitization of society' is identified as the least significant driver of BDA in this study. The outcome of this study is expected to assist the industry managers to find out the most and least preferable drivers in their supply chains and then take initiatives to improve the overall efficiency of their organizations accordingly.
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The airlines' industry is one of the fastest-growing transportation sectors, playing a significant role in the global economy. The objective of this study is to develop a systematic approach for regional aircraft selection considering... more
The airlines' industry is one of the fastest-growing transportation sectors, playing a significant role in the global economy. The objective of this study is to develop a systematic approach for regional aircraft selection considering environmental, design, and cost impact. To eliminate the human vagueness and uncertainty, a newly integrated general framework is developed by using the Fuzzy AHP (FAHP) and Efficacy method for selecting the regional aircraft. The proposed framework considering purchase cost, design, environmental criteria based on future standards gives new insight for the airliner procurement team. All the criteria are selected after an in-depth analysis of various research works, current and future market requirements, and in consideration of environmental standards. Those are reviewed by aviation industrial and academic expert. Our framework is inspired by Canadian airliners and the whole context is developed in the focus of the Canadian perspective, which can be modified for any other decision-making process. A sensitivity analysis is carried out to check the consistency of our newly proposed model results. The developed model will help the managers or higher-level procurement team to make appropriate decisions for the selection of an aircraft focusing on environmental, cost, and design impact.
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This paper aims to identify, evaluate, and measure the ergonomic factors hampering the production of leather garment-based small and medium-sized enterprises (SMEs). Ergonomic problems faced by the workers largely impact the health of... more
This paper aims to identify, evaluate, and measure the ergonomic factors hampering the production of leather garment-based small and medium-sized enterprises (SMEs). Ergonomic problems faced by the workers largely impact the health of individuals and also the productivity of a firm. Based on experts' opinions and a literature survey, three emerging categories-namely, occupational disease, personal factors, and the industrial environment-with a total of twenty factors were identified to examine symmetrical impact in five leather garment companies. In this research work, Cronbach's α was evaluated to check the validity of the ergonomic factors identified through the literature survey. Then, using the fuzzy analytic hierarchy process (FAHP), the identified ergonomic factors were evaluated. A sensitivity analysis was carried out to validate the robustness of the results obtained using the integrated approach. Outdated machinery, vibration, operational setup, fatigue, and poor ventilation and lighting are the top five factors inducing ergonomic-related problems and hampering the production of the leather garment companies in India. These top ergonomic factors are the result of a failure in the provision of an ambient working environment. Providing ergonomically designed working environments may lower the occurrence of ergonomic problems. The findings of this study will assist industrial managers to enhance production rate and to progress towards social sustainability in Indian SMEs. The proposed symmetrical assessment in this study could also be considered as a benchmark for other companies in which human-machine interaction is significant.
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Owing to the sudden changes in climatic conditions, monsoon failure, and scarce availability of resources because of population hike, yielding a minimum profit has become a challenge for Indian farmers. This is a severe problem for India,... more
Owing to the sudden changes in climatic conditions, monsoon failure, and scarce availability of resources because of population hike, yielding a minimum profit has become a challenge for Indian farmers. This is a severe problem for India, as a major part of the Nation's Gross Domestic Product (GDP) depends on agriculture. To change this dreadful situation, Indian farmers must employ sustainable agricultural practices in farming, as it will help them to meet their agricultural needs and economic stability. Here, we have built a framework for selecting the ideal crop pattern for Winter Cropping Season (Rabi Season), as crop pattern plays a vital role in the effective function of sustainable agricultural practices. We have used the rough AHP-TOPSIS (Analytical Hierarchy Process-Technique for Order Preference by Similarity to Ideal Solution) method for finding the best crop pattern for the Rabi season, by considering all the influential criteria in terms of agriculture sustainability. Our study demonstrates an overall idea to the farmers and stakeholders about attaining maximum crop productivity with optimum use of available resources, without compromising the economic, social, and ecological aspects of agriculture.
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Transportation is one of the logistical drivers in supply chains. Transportation disruption is costly in supply chains. This paper aims to assess transportation disruption risks using a Bayesian Belief Network (BBN). First, the disruption... more
Transportation is one of the logistical drivers in supply chains. Transportation disruption is costly in supply chains. This paper aims to assess transportation disruption risks using a Bayesian Belief Network (BBN). First, the disruption risk factors and their sub-factors were identified from the relevant articles and experts' opinions. The BBN-based model is developed to calculate the marginal probabilities of the risk factors and their sub-factors to determine the most sensitive factors/sub-factors. The framework was demonstrated using an example case of the pharmaceutical industry in Bangladesh. The findings reveal the usefulness of BBN in examining transportation disruptions in supply chains. BBN captured the interdependencies between the disruption risk factors/sub-factors effectively. The proposed model will be useful to managers for predicting transportation disruptions and to build resilient strategies to tackle them.
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Rapid environmental depletion and ever-increasing CO 2 emission have necessitated an environment-friendly manufacturing practice for industries across the globe. In this perspective, green manufacturing (GM) practices were conceptualized... more
Rapid environmental depletion and ever-increasing CO 2 emission have necessitated an environment-friendly manufacturing practice for industries across the globe. In this perspective, green manufacturing (GM) practices were conceptualized and practiced by large scale enterprises of developed countries. However, small and medium-sized enterprises (SMEs) in developing countries are struggling to adopt GM practices. There are many reasons for this struggle in a developing country like India. To shed light on this issue, this research work intends to identify, analyze and rank the predominant barriers , which restrict implementing of GM practices in Indian manufacturing small and medium-sized enterprises (SMEs). Based on a comprehensive literature review and experts' opinion by employing the Delphi method (DM), the study revealed 25 barriers, in three broad categories, of GM implementation in Indian SMEs. The identified barriers are ranked, and their interrelationships are explored using a novel integrated multi-criteria decision making (MCDM) framework, with a combination of Decision-Making Trial and Evaluation Laboratory Model (DEMATEL), Analytical Network Process (ANP), and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) in a fuzzy context. A sensitivity analysis is performed to check the consistency of the results. The results reveal that core category, which include several barriers related to lack of internal abilities and strategies, is the most critical category of barriers for manufacturing SMEs in India. In particular, the three most critical barriers are lack of research and development (R&D), failure in eco-design and lack of accreditation respectively. The study findings, which provide valuable insight for SME practitioners of Indian manufacturing SMEs, can be used to formulate appropriate strategies to overcome the barriers.
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Purpose-Supply chain management plays an important role in sustaining businesses in today's competitive environment. Therefore, industrial managers are focusing on exploring the key performance improvement attributes of supply chain... more
Purpose-Supply chain management plays an important role in sustaining businesses in today's competitive environment. Therefore, industrial managers are focusing on exploring the key performance improvement attributes of supply chain management to achieve a better position in the global market. Aimed at ensuring best supply chain management practices, this study presents the key performance improvement attributes, known as critical success factors (CSFs), within the context of the apparel supply chain of Bangladesh. Design/methodology/approach-In this paper, the interpretive structural modeling method (ISM) has been applied to develop a structural framework to analyze the contextual relationship among the factors under consideration. MICMAC (Matriced' Impacts Croises Multiplication Appliquee aunClassement) analysis has also been performed to define the classification of the CSFs in terms of their driving and dependence power. Findings-The research findings reveal that supply chain collaboration/partnership and customer satisfaction are of crucial importance to success in the context of supply chain management of the readymade (RMG) garments industry of Bangladesh. Further evidence suggests that these, along with other success factors, can assist in achieving a competitive advantage and better market position. A number of theoretical and managerial implications have been provided for managers and practitioners, and for further evaluation of the study. Originality/value-This paper considers a new supply chain problem which identifies and evaluates critical success factors. This paper also develops a new structural model for evaluating critical success factors.
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Due to an increased pressure to be environmentally sustainable, many manufacturing organizations, especially from developing countries like Bangladesh, are attempting to make necessary changes in practices and supply chains. However,... more
Due to an increased pressure to be environmentally sustainable, many manufacturing organizations, especially from developing countries like Bangladesh, are attempting to make necessary changes in practices and supply chains. However, those attempts need to be applied strategically with the objective to be both environmentally sustainable and economically viable. This paper offers a decision-making methodology by integrating a fuzzy cognitive map (FCM) and data envelopment analysis (DEA) for evaluating strategies for environmental sustainability based on their impact on the overall supply chain network of an organization. This paper first identifies 18 generic strategies for environmental sustainability and three supply chain performance measurement (PM) factors. Afterwards, the cause-effect relationships among these strategies and PM factors are utilized to capture the complicated relationships by FCM. The extended delta rule (EDR) learning algorithm was used in association with FCM to quantify the impact of those strategies on supply chain PM factors. Finally, DEA is used to prioritize strategies using these impact values. A real-life case using a fast-moving consumer goods (FMCG) manufacturer from Bangladesh is presented to justify the applicability of the proposed methodology. The results reflect the usefulness of this methodology for evaluating strategies for environmental sustainability in a supply chain (SC), specifically in the FMCG sector of an emerging economy. Thus, other manufacturing organizations from any industry can use this methodology to evaluate strategies for environmental sustainability.
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Appropriate suppliers are essential for optimizing cost in contemporary supply chain decisions. Supplier selection is a challenging issue that requires the evaluation of both quantitative and qualitative criteria based on imprecise and... more
Appropriate suppliers are essential for optimizing cost in contemporary supply chain decisions. Supplier selection is a challenging issue that requires the evaluation of both quantitative and qualitative criteria based on imprecise and limited information. This study proposes a framework to assess sustainable supplier selection methods using a fuzzy analytical hierarchy process (FAHP) and the preference ranking organization method for enrichment evaluation (PROMETHEE). Based on a literature review and expert opinions, 20 sustainable supplier selection criteria were grouped into economic, environmental, social, and transportation dimensions. FAHP was then used to determine the weights of the criteria and PROMETHEE was used to rank the suppliers. The proposed framework was implemented in a ready-made garment company in Bangladesh. The findings showed that 'price of product,' 'profit on product,' 'quality of product,' 'environmental management system,' and 'green packaging and labeling' were the top five sustainable supplier selection criteria. Business professionals and managers will benefit from this study when identifying suppliers to ensure sustainability in the supply chain. ARTICLE HISTORY
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Purpose-In Bangladesh, the chemical industry is one of the expanding industries based on current statistical data analysis. Green supply chain management (GSCM) is pivotal in order to compete with the global competition. This paper main... more
Purpose-In Bangladesh, the chemical industry is one of the expanding industries based on current statistical data analysis. Green supply chain management (GSCM) is pivotal in order to compete with the global competition. This paper main aim is to discuss a systematic approach to build a structural outline. The purpose of the proposed structural outline is to predict the constructive implementation of GSCM especially on chemical industry in Bangladesh. Design/methodology/approach-This proposed structural framework evaluates the suitable interrelationship next to the barriers of GSCM in the Bangladesh's chemical industry. Here, on the basis of literature review and survey from expert opinions by the use of the Delphi methodology in total eight barriers were concluded. Here additionally, MICMAC analyses were applied to determine the driving and dependence power. Furthermore, the frameworks outline for the barriers were included by means of total interpretive structural modeling (TISM) method. Findings-Based on the analysis, the most significant barriers were found lack of supporting laws and guidance from the government and cost of disposal of hazardous products. Research limitations/implications-The TISM technique only has implemented to develop the framework, whereas other tools or structural equation modeling (SEM) technique can be used to develop and validate the frameworks for barriers. Originality/value-In this research, Delphi method questionnaire generated based on the GSCM in the Bangladesh chemical sector. This study will assist the industrial managers to assess and evaluate the crucial sectors, whereas they should give priority to apply the GSCM in the Bangladesh chemical industry.
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Green supply chain management (GSCM) has emerged as an important issue to lessen the impact of supply chain activities on the natural environment, as well as reduce waste and achieve sustainable growth of a company. To understand the... more
Green supply chain management (GSCM) has emerged as an important issue to lessen the impact of supply chain activities on the natural environment, as well as reduce waste and achieve sustainable growth of a company. To understand the effectiveness of GSCM, performance measurement of GSCM is a must. Monitoring and predicting green supply chain performance can result in improved decision-making capability for managers and decision-makers to achieve sustainable competitive advantage. This paper identifies and analyzes various green supply chain performance measures and indicators. A probabilistic model is proposed based on a Bayesian belief network (BBN) for predicting green supply chain performance. Eleven green supply chain performance indicators and two green supply chain performance measures are identified through an extensive literature review. Using a real-world case study of a manufacturing industry, the methodology of this model is illustrated. Sensitivity analysis is also performed to examine the relative sensitivity of green supply chain performance to each of the performance indicators. The outcome of this research is expected to help managers and practitioners of GSCM improve their decision-making capability, which ultimately results in improved overall organizational performance.
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The transportation network plays a vital role in the strategic imperative of automotive parts manufacturing companies. There is a lack of academic and practical studies, which focus solely on transportation disruption analysis in the... more
The transportation network plays a vital role in the strategic imperative of automotive parts manufacturing companies. There is a lack of academic and practical studies, which focus solely on transportation disruption analysis in the supply chain of automotive parts manufacturing company. Moreover, very few studies have taken into account the cause and effect relationship between transportation disruption factors. The objective of this study is to analyze the critical transportation disruption factors of the supply chain of automotive parts manufacturing company and to represent the interrelationships using the best-worst (BWM) and rough strength-relation (RSR) analysis methods. The newly integrated BWM-RSR framework considers the vagueness and ambiguity in disruption factor analysis. The applicability and effectiveness of the newly developed BWM-RSR framework are demonstrated at an automotive parts manufacturing company in Oldcastle, Ontario, Canada. The results show that infrastructural bottlenecks/congestion and inadequate skilled labor are the most critical factors to the disruption of the transportation network in the automotive industry. The developed new framework can be used as an effective tool to analyze critical transportation disruption factors and examine the associated interrelationships.
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Reverse logistics (RL) is gradually becoming more important to manufacturing companies through environmental awareness, competitiveness, and environmental regulations. In the leather footwear industry of Bangladesh, it is possible to... more
Reverse logistics (RL) is gradually becoming more important to manufacturing companies through environmental awareness, competitiveness, and environmental regulations. In the leather footwear industry of Bangladesh, it is possible to recycle and reuse waste, meaning a reverse logistics system could increase return-on-investment and give a competitive advantage. To date, studies on barriers to RL implementation have been conducted in other countries and in other domains, leaving a research gap in RL barrier analyses in the leather footwear industry. There are many obstacles to implementing RL in a developing country like Bangladesh; examining these barriers is a crucial research issue. This paper identifies RL barriers through (1) an extent literature review, (2) advice from Bangladeshi industry experts under the Delphi study, and (3) ranking RL barriers using the fuzzy analytical hierarchy process. The results indicate that, of the barriers investigated, the 'knowledge and support' category seems to be most critical. A lack of interest and support from top-level management-related to 'knowledge and support' issues-appears to be the major obstacle for RL implementation in the Bangladeshi leather footwear industry. These findings will help the Bangladeshi leather footwear industry, as well as other industries in Bangladesh, to understand the nature of each barrier and overcome the complexity of RL implementation in supply chains. This study will also assist decision-makers in making certain strategic policies. Future studies may contribute to the life cycle assessment and engineering of recycled and reused footwear.
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The main purpose of Green Supply Chain Management (GSCM) is to improve the quality of supply chain management strategies and environmental performance. As per current statistics , the chemical industry is growing fast in Bangladesh. In... more
The main purpose of Green Supply Chain Management (GSCM) is to improve the quality of supply chain management strategies and environmental performance. As per current statistics , the chemical industry is growing fast in Bangladesh. In order to compete for global competition, GSCM is essential in this sector. This paper proposes a systematic approach of structural framework whose aim is to enhance the probability of constructive implementation of GSCM in the field chemical industry in Bangladesh. Therefore, this framework evaluates the appropriate interrelationship along with the drivers of GSCM in the chemical industry. In total, eight drivers were finalized from an associated literature review with the help of survey and by taking expert opinions via the Delphi methodology. In addition to MICMAC analysis, the driving and the dependence powers for all the drivers were determined. Moreover, the structural frameworks for the drivers were developed by means of total interpretive structural modeling (TISM) technique. As a result, the findings indicate that the most significant driver was supplier pressure and willingness and the most important barrier was high cost. Finally, the main objective of this research is expected to help industrial managers to evaluate and understand the critical areas where they should emphasize to implement GSCM in the chemical industry. ARTICLE HISTORY
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This research presents critical success factors (CSFs) for developing energy-efficient supply chains (EESCs) in the leather industry in an emerging economy, which implications for energy policy. A novel decision-making support approach... more
This research presents critical success factors (CSFs) for developing energy-efficient supply chains (EESCs) in the leather industry in an emerging economy, which implications for energy policy. A novel decision-making support approach named the 'best-worst method' (BWM) is employed to rank the most important CSFs. Furthermore, an interpretive structural modeling (ISM) approach and a MICMAC analysis (Matriced Impacts Crois es Multiplication Appliqu ee a un Classement) are undertaken in this study to depict the relative dependences and influences among the selected CSFs. The CSF 'International pressure and scarcity of natural resources' is identified as the most significant factor via a hybrid BWM-ISM method that may drive the leather industry to implement EESC practices and thus maintain a sustainable environmental approach. This research will be beneficial to decision makers in carrying out effective operations and improving implementation of EESC practices in the leather industry.
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Purpose-The purpose of this paper is to explore organizational and human factor-related challenges to information technology (IT) service management standard ISO 20000 in an emerging economy context. Then, this research has proposed some... more
Purpose-The purpose of this paper is to explore organizational and human factor-related challenges to information technology (IT) service management standard ISO 20000 in an emerging economy context. Then, this research has proposed some implications of the challenges to implementing environmental sustainability and circular economy. Design/methodology/approach-To fulfill the research purpose, an empirical study was undertaken. The data required for the current study, based on a Likert scale and using questionnaires, were collected through surveys, interviews, telephonic conversations and meetings with IT firm managers and staff. The ranking of challenges was obtained based on the mean and standard deviation calculated from the survey responses. Findings-The results indicated that senior management support was the most significant challenge for the successful implementation of IT Service Management systems. Other significant challenges were the justification of significant investment, premium customer support, cooperation and coordination among IT support teams, proper documentation and effective process design. Practical implications-The current research is expected to help IT managers implement ISO 20000 and to manage environmental sustainability and circular economy across their organizational networks. Originality/value-To the best of the authors' knowledge, the current study is the first attempt to explore the organizational and human factor-related challenges to ISO 2000 in an emerging economy context. Furthermore, the current study proposes implications to the challenges to environmental sustainability and circular economy.
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Purpose-Green human resource management (GHRM) is an arising issue for the tannery industry in the context of developing economies. As the tannery industry can be seen as one of the highest polluting industries on earth, it becomes... more
Purpose-Green human resource management (GHRM) is an arising issue for the tannery industry in the context of developing economies. As the tannery industry can be seen as one of the highest polluting industries on earth, it becomes imperative for the industry to implement GHRM practices for greening the workforce. In this context, the purpose of this paper is to focus on antecedents that will support the implementation of GHRM practices in the tannery industry supply chain. Design/methodology/approach-In this study, an expanded literature review was organized to establish antecedents for implementing GHRM practices. The total interpretive structural modeling (TISM) technique is employed to explore interactions among the identified antecedents. Furthermore, Matriced Impact Croises Multiplication Applique analysis was conducted for determining the driving-dependence power of each antecedent. Findings-The results revealed that "green selection facility," "green recruiting facility," "green organizational culture," "green purchasing," "green strategy towards ES," "regulatory forces towards ES" and "top management commitment towards greening the workforce" are the key antecedents for the exercise of GHRM practices in the tannery industry. Practical implications-The proposed model might support decision makers to understand the interactions among the antecedents of GHRM practices. This model will help managers to understand the impact of one antecedent on another prior to the implementation of GHRM practices in the tannery industry. Originality/value-In this study, the author(s) propose a new version of the interpretive structural modeling approach (ISM), named the TISM technique, for determining the contextual interactions between GHRM initiative antecedents that are very new in the existing literature.
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This study proposes a fuzzy-based VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje) framework for evaluating barriers to implementing green supply chain management (GSCM) in the context of an emerging economy. The methodology... more
This study proposes a fuzzy-based VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje) framework for evaluating barriers to implementing green supply chain management (GSCM) in the context of an emerging economy. The methodology uses a mix method approach combining literature review and opinions of some selected managers from the plastic industry of Bangladesh to identify four main-barriers and twenty-five sub-barriers relevant to GSCM implementation. Fuzzy-VIKOR approach was applied to aid in the analysis of the barriers in the plastic industry of Bangladesh. The findings of the study show the order/rank of intensity and severity of the main-barriers to implementing GSCM practices in the plastic industry of Bangladesh as follows: 'inadequate knowledge and sup-port', 'insufficient technology and infrastructure', 'financial constraints and unsupportive organizational' and 'operational policies'. The results also show the rankings of the sub-barriers under each main barriers. This research contributes to the literature in a number of ways. First, it identifies multi-levels of barriers to GSCM implementation. Secondly, it identifies and proposes alternative action plans (strat-egies) to help mitigate and implement GSCM practices. Though this study has significant contributions , a number of limitations do exist. The barriers in this study were identified using the extant literature review and industrial managers' opinions. A more scientific approach and empirical validation is required, especially in the plastic manufacturing industry of Bangladesh to identify more new challenging barriers. However, this study can provide managers with a better understanding of the barriers to implementing GSCM practices and motivate the researchers to further extend the investigation on the insights for developing strategic plans for implementing GSCM practices in the plastic industry of Bangladesh. ARTICLE HISTORY
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Assessing sustainability in supply chains is an important task for any organization in the competitive business environment. The process of assessing the sustainability of a supply chain involves incorporating different sources of... more
Assessing sustainability in supply chains is an important task for any organization in the competitive business environment. The process of assessing the sustainability of a supply chain involves incorporating different sources of information, which are normally uncertain, incomplete, and subjective in nature. However, previous studies have failed to incorporate such uncertain, incomplete and subjective information. Therefore, this research proposes a methodology that uses an integrated approach combining the Analytical Hierarchy Process (AHP) and Hierarchical Evidential Reasoning (HER) based on Dempster-Shafer (D-S) theory to develop a supply chain sustainability assessment model. After identifying the sustainability assessment criteria, Analytical Hierarchy Process is used to structure and rate the criteria based on experts' opinion. In this research, subjective judgmental belief data are used to test the model. The information is combined using Dempster-Shafer theory and results are depicted according to the supply chain sustainability index. In the proposed mode, the results from the Dempster-Shafer theory are compared using Yager's recursive rule of combination. The model generates satisfactory results which denotes the condition state of sustainability along with unassigned degree of belief or uncertainty. To assess the sustainability condition in supply chain this methodology can be adopted by the management of the organizations.
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Environmental sustainability is not being practiced in the supply chains of many industries. Previous studies on environmental sustainability have not outlined clear strategies to achieve sustainability across supply chains, particularly... more
Environmental sustainability is not being practiced in the supply chains of many industries. Previous studies on environmental sustainability have not outlined clear strategies to achieve sustainability across supply chains, particularly in the context of emerging economies, and have been of limited relevance in settings beyond the geographical region of their focus. To address these gaps, we have proposed a best worst method (BWM) as a framework to assess the environmental criteria for sustainability in select industries in Bangladesh. Different industrial activities or criteria affecting the environment in various ways were assessed and weighted using the BWM. To ensure the efficiency and accuracy of this framework, we sought the opinions of 34 experts to specify the most suitable indicators from our initial literature review. Findings from this study revealed that “waste management” was the most important indicator for establishing environmental sustainability in industries in Bangladesh, which was substantiated by a sensitivity analysis. This research will assist industry managers and entrepreneurs to work toward environmental sustainability across supply chains.
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The leather-processing industry (LPI) is constantly polluting the environment in Bangladesh. As a result, stakeholders are continuously pressurizing managers working in LPI to embrace green leather-processing activities. Thus, the green... more
The leather-processing industry (LPI) is constantly polluting the environment in Bangladesh. As a result, stakeholders are continuously pressurizing managers working in LPI to embrace green leather-processing activities. Thus, the green concept is attracting significant attention from managers in the Bangladeshi LPI. However, the industry is struggling with many barriers to implementing green supply chain management (GSCM). There are many studies regarding barriers to GSCM. However, those studies failed to show the possible pathways to implement GSCM. This study addresses the gap by evaluating barriers to GSCM considering effective pathways to GSCM. In this study, the Analytical Hierarchy Process (AHP) is integrated with Elimination Et Choix Traduisant La Realite (ELECTRE-I) method to identify and prioritize the barriers and to rank the possible pathways to implementing GSCM in the leather industry. To accredit the proposed framework, it is implemented on a leather-processing factory in Bangladesh. A sensitivity analysis is performed to inspect the strength of the outcome of this method. The outcome of this study indicates that the high cost of advanced technology is the most important barrier to implement GSCM while green technology and techniques are the most effective pathways to GSCM. The findings of this research will support researchers and practitioners by giving insights on barriers and possible pathways to implementing GSCM. ARTICLE HISTORY
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Purpose-Risk management has emerged as a critical issue in operating a supply chain effectively in the presence of uncertainties that result from unexpected variations. Assessing and managing supply chain risks are receiving significant... more
Purpose-Risk management has emerged as a critical issue in operating a supply chain effectively in the presence of uncertainties that result from unexpected variations. Assessing and managing supply chain risks are receiving significant attention from practitioners and academics. At present, the ceramic industry in Bangladesh is growing. Thus, managers in the industry need to properly assess supply chain risks for mitigation purposes. This study aims to identify and analyze various supply chain risks occurring in a ceramic factory in Bangladesh. Design/methodology/approach-A model is proposed based on a fuzzy technique for order preference using similarity to an ideal solution (fuzzy-TOPSIS) for evaluating supply chain risks. For this, 20 supply chain risk factors were identified through an extensive literature review and while consulting with experts from the ceramic factories. Fuzzy-TOPSIS contributed to the analysis and assessment of those risks. Findings-The results of this research indicate that among the identified 20 supply chain risks, lack of operational quality, lack of material quality and damage to inventory were the major risks for the ceramic sector in Bangladesh. Research limitations/implications-The impact of supply chain risks was not shown in this study and the risks were considered independent. Therefore, research can be continued to address these two factors. Practical implications-The outcome of this research is expected to assist industrial managers and practitioners in the ceramic sector in taking proactive action to minimize supply chain risks. A sensitivity analysis was performed to determine the relative stability of the risks. Originality/value-This study uses survey data to analyze and evaluate the major supply chain risks related to the ceramic sector. An original methodology is provided for identifying and evaluating the major supply chain risks in the ceramic sector of Bangladesh.
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In today's business world, supply chain networks are becoming increasingly prone to uncertainties and complexities. The supply chain network of the ready-made garment (RMG) industry in Bangladesh is global in nature and is therefore... more
In today's business world, supply chain networks are becoming increasingly prone to uncertainties and complexities. The supply chain network of the ready-made garment (RMG) industry in Bangladesh is global in nature and is therefore vulnerable to increased risks and disruptions. This paper identifies potential supply chain risks and analyzes the interactions. To achieve this, a hierarchical structural model was developed through the application of an interpretive structural modeling (ISM) approach. Moreover, MICMAC (Matriced’ Impacts Cruoses Multiplication Applique a un Classement) analysis was conducted to classify the risks based on driving and dependence power. Findings revealed that disruption risk was the most influential risk in the RMG industry. The results of this study will guide industrial managers to take remedial measures to mitigate the supply chain risks in the apparel industry.
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Handling editor: Xin Tong Keywords: Green supply chain management process (GSCMP) Hierarchical cluster analysis Textile industry Emerging economy a b s t r a c t Green supply chain management is attracting increasing attention as a way to... more
Handling editor: Xin Tong Keywords: Green supply chain management process (GSCMP) Hierarchical cluster analysis Textile industry Emerging economy a b s t r a c t Green supply chain management is attracting increasing attention as a way to decrease the adverse environmental effects of industries worldwide. However, considering the context of an emerging economy like Bangladesh, green supply chain management is still in its inception and has not been widely embraced in the textile industry, and therefore barriers hindering its adoption in emerging economy context demand a comprehensive investigation. This research reviews the viewpoints and hurdles in adopting green supply chain management practices in the context of the Bangladeshi textile industry. A questionnaire survey of Bangladeshi textile practitioners of operations and supply chain management division, having a sample size of thirty, was undertaken to identify the barriers, and a hierarchical cluster analysis technique was used in the detailed analysis of this data. Opinions were sought from experts on the significance of the resulting clusters, considering the relative importance of the barriers. Fifteen barriers to the adoption of green supply chain management were identified in the review of the literature, with these barriers then analyzed by using the data collected from Bangladeshi textile industry practitioners. The research indicates that the most important barrier is that there is low demand from customers and financial constraint resulting from short term little financial benefit to businesses, with lack of government regulations also a commonly faced barrier in adopting green supply chain initiatives. This study will provide valuables insights to practitioners and relevant policy makers about the barriers prevailing in the emerging economies towards the adoption of green supply chain management practices, which, in turn, can guide to undertake appropriate steps for alleviating those barriers.
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Supply chain sustainability includes environmental, economic, and social dimensions. However, social sustainability in supply chains has received less attention than environmental and economic dimensions. Sustainability issues in emerging... more
Supply chain sustainability includes environmental, economic, and social dimensions. However, social sustainability in supply chains has received less attention than environmental and economic dimensions. Sustainability issues in emerging economies have also been neglected. Literature reviews reveal that assessing social sustainability in the context of the footwear supply chain in an emerging economy is still an under-researched area. Therefore, this study investigates enablers of social sustainability in the footwear supply chains in Bangladesh using the Best-Worst method. The framework was applied to a footwear manufacturing company with an aim to incorporate social sustainability practices into operations and supply chains. Nineteen enablers were identified by reviewing the extant literature. Among them, ten enablers were selected with the help of expert inputs. The enablers were ranked according to average weight evaluated by the Best-Worst method. The results indicated that workplace health and safety practices was the most important enabler to the social sustainability of a footwear manufacturing company's supply chain, followed by the wages and benefits offered to the employees of the company. The findings of this study are expected to guide industrial managers and experts on where to focus attention on achieving social sustainability in supply chains.
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Over the years, food supply chains (FSCs) have faced various challenges, including supply chain interruptions. Previous studies focused only on household food waste. In this study, the FSCs risks is connected with food wastage to develop... more
Over the years, food supply chains (FSCs) have faced various challenges, including supply chain interruptions. Previous studies focused only on household food waste. In this study, the FSCs risks is connected with food wastage to develop sustainable framework to reduce food waste. A Pareto analysis is developed for risk identification based on feedback from 130 experts from food companies. Finally, a blended grey-based Decision-Making Trial and Evaluation Laboratory (DEMATEL) model has been proposed to assess the relationships among the identified major risks in FSCs. The five risks of greatest priority include: lack of skilled personnel, poor leadership, failure within the IT system, capacity, and poor customer relationship. The risk mitigation strategies for these risks are also presented. The proposed model is applied to food processing companies in Bangladesh to establish a sustainable business policy to minimize food wastage. These results can guide managers and practitioners to formulate resilient strategies to mitigate the identified risks, thereby minimizing food wastage and lead to food safety, security and sustainability across the food supply chain. The proposed model can be extended to address sustainability risk and be integrated to the internet of things for planning, monitoring, controlling , and optimizing supply chains in real time.
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Recently, big data (BD) has attracted researchers and practitioners due to its potential usefulness in decision-making processes. Big data analytics (BDA) is becoming increasingly popular among manufacturing companies as it helps gain... more
Recently, big data (BD) has attracted researchers and practitioners due to its potential usefulness in decision-making processes. Big data analytics (BDA) is becoming increasingly popular among manufacturing companies as it helps gain insights and make decisions based on BD. However, there many barriers to the adoption of BDA in manufacturing supply chains. It is therefore necessary for manufacturing companies to identify and examine the nature of each barrier. Previous studies have mostly built conceptual frameworks for BDA in a given situation and have ignored examining the nature of the barriers to BDA. Due to the significance of both BD and BDA, this research aims to identify and examine the critical barriers to the adoption of BDA in manufacturing supply chains in the context of Bangladesh. This research explores the existing body of knowledge by examining these barriers using a Delphi-based analytic hierarchy process (AHP). Data were obtained from five Bangladeshi manufacturing companies. The findings of this research are as follows: (i) data-related barriers are most important , (ii) technology-related barriers are second, and (iii) the five most important components of these barriers are (a) lack of infrastructure, (b) complexity of data integration, (c) data privacy, (d) lack of availability of BDA tools and (e) high cost of investment. The findings can assist industrial managers to understand the actual nature of the barriers and potential benefits of using BDA and to make policy regarding BDA adoption in manufacturing supply chains. A sensitivity analysis was carried out to justify the robustness of the barrier rankings.
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The success of an organization or a particular activity is evaluated through the measurement of key performance indicators (KPIs). The aim of this paper is to analyze and predict the indicators of healthcare performance using grey systems... more
The success of an organization or a particular activity is evaluated through the measurement of key performance indicators (KPIs). The aim of this paper is to analyze and predict the indicators of healthcare performance using grey systems theory. Recent advancements in science and technology have made the healthcare industry extremely efficient at collecting data using electronic claims systems such as electronic health records. Therefore, collecting field level primary data becomes easier and accumulate them to generate secondary data for research purpose and to get an insight of the organization performance is absolutely necessary. Our research analyzes the KPIs of a hospital based on a secondary data source. Since, secondary data contains uncertainty and sometimes poor information, grey prediction model suits best to make a prediction model in this regard. Conventional grey model has considerable drawbacks while making a rigorous prediction model. For this, we apply an improved grey prediction model to predict the KPIs of the healthcare performance indicators. Several error measures in our model give a best fit of the data and allow prediction of the KPIs. The prediction model gives good estimates of the quantitative indicators and produced error rate within an acceptable range. We observe that the KPIs of bed turnover rate (BTR) and bed occupancy rate (BOR) have an increasing trend, whereas the KPIs of average length of stay (ALOS), hospital death rate (HDR) and hospital infection rate (HIR) show a decreasing trend over time. The main contribution of this research is a grey-based prediction model that can provide managers with the information they need to evaluate and predict the performance of a hospital. The research indicates that managers should give greater priority to the indicators which will result in better patients' satisfaction and improved profit margin. Healthcare managers striving towards better performance will now have an empirical basis upon which to formulate and adjust their strategies, after analyzing the predicted value.
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Corporate social responsibility (CSR) is gaining popularity among researchers and practitioners due to its strong influence on the global market. Recently, the decision-makers of footwear companies have given special attention on CSR... more
Corporate social responsibility (CSR) is gaining popularity among researchers and practitioners due to its strong influence on the global market. Recently, the decision-makers of footwear companies have given special attention on CSR issues due to increased stakeholders' awareness on social and environmental issues. In this study, the fuzzy analytical hierarchy process (FAHP) has been used to identify and evaluate drivers to CSR-based sourcing in the context of the footwear industry of Bangladesh. A total of 20 drivers are identified through a literature review and experts' opinions. The results indicate that financial drivers are paramount toward CSR-based sourcing into existing supply chains followed by environmental drivers. This study offers some managerial implications that may assist companies to incorporate CSR-based sourcing into existing supply chains. The identified drivers may guide footwear companies in strategic planning to create a sustainable business structure in the competitive market.
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Measuring productivity is the systematic process for both inter-and intra-organizational comparisons. The productivity measurement can be used to control and facilitate decision-making in manufacturing as well as service organizations.... more
Measuring productivity is the systematic process for both inter-and intra-organizational comparisons. The productivity measurement can be used to control and facilitate decision-making in manufacturing as well as service organizations. This study's objective was to develop a decision support framework by integrating an analytic network process (ANP) and data envelopment analysis (DEA) approach to tackling productivity measurement and benchmarking problems in a manufacturing environment. The ANP was used to capture the interdependency between the criteria taking into consideration the ambiguity and vagueness. The nonparametric DEA approach was utilized to determine the input-oriented constant returns to scale (CRS) efficiency of different value-adding production units and to benchmark them. The proposed framework was implemented to benchmark the productivity of an apparel manufacturing company. By applying the model, industrial managers can gain benefits by identifying the possible contributing factors that play an important role in increasing the productivity of manufacturing organizations.
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Researchers and practitioners are giving significant attention to Industry 4.0 due to its numerous benefits to manufacturing organizations. Several aspects of Industry 4.0 have been studied in the literature. However, studies on the... more
Researchers and practitioners are giving significant attention to Industry 4.0 due to its numerous benefits to manufacturing organizations. Several aspects of Industry 4.0 have been studied in the literature. However, studies on the challenges for implementing Industry 4.0 in manufacturing operations have received less attention. To address this gap, this study identifies a set of challenges (framework) for implementing Industry 4.0 in manufacturing industries. This framework is evaluated in the leather industry of Bangladesh aided by a novel multi-criteria decision-making method named Best-Worst method (BWM). The findings of the study showed that ‘lack of technological infrastructure’ is the most pressing challenge that may hurdle the implementation of Industry 4.0 whereas ‘environmental side-effects’ is the less among the challenges that may hinder implementation of Industry 4.0 in the Bangladeshi leather industry. This result may help decision makers, industrial managers and practitioners in the Bangladeshi leather industry to realize the actual challenges confronting them when attempting to implement Industry 4.0 and focus their attention on how to address these challenges to pave ways for a successful implementation of Industry 4.0.
Research Interests:
Purpose-Managing risks is becoming a highly focused activity in the health service sector. In particular, due to the complex nature of processes in the pharmaceutical industry, several risks have been associated to its supply chains. The... more
Purpose-Managing risks is becoming a highly focused activity in the health service sector. In particular, due to the complex nature of processes in the pharmaceutical industry, several risks have been associated to its supply chains. The purpose of this paper is to identify and analyze the risks occurring in the supply chains of the pharmaceutical industry and propose a decision model, based on the Analytical Hierarchy Process (AHP) method, for evaluating risks in pharmaceutical supply chains (PSCs). Design/methodology/approach-The proposed model was developed based on the Delphi method and AHP techniques. The Delphi method helped to select the relevant risks associated to PSCs. A total of 16 sub risks within four main risks were identified through an extensive review of the literature and by conducting a further investigation with experts from five pharmaceutical companies in Bangladesh. AHP contributed to the analysis of the risks and determination of their priorities. Findings-The results of the study indicated that supply-related risks such as fluctuation in imports arrival, lack of information sharing, key supplier failure and non-availability of materials should be prioritized over operational, financial and demand-related risks. Originality/value-This work is one of the initial contributions in the literature that focused on identifying and evaluating PSC risks in the context of Bangladesh. This research work can assist practitioners and industrial managers in the pharmaceutical industry in taking proactive action to minimize its supply chain risks. To the end, the authors performed a sensitivity analysis test, which gives an understanding of the stability of ranking of risks.
Research Interests:
Effective response and recovery from disruptions are vital to achieving the supply chain objectives. This study aims to formulate a quantitative model for mitigating disruptions in a supply chain. An inventory model has been developed... more
Effective response and recovery from disruptions are vital to achieving the supply chain objectives. This study aims to formulate a quantitative model for mitigating disruptions in a supply chain. An inventory model has been developed for a manufacturer with one supplier and one retailer by considering random capacity of the supplier and random availability of both the supplier and the retailer assuming zero delivery lead time. Backorders are allowed and it has two parts – unit dependent and both unit and time-dependent. This study suggests an optimal order quantity and a reordering point so that the average cost per cycle gets minimized. A genetic algorithm is used to solve the proposed inventory model. The applicability of the proposed model has been tested using a numerical example. Finally, sensitivity analysis is performed to examine the robustness of the model.
Researchers and practitioners are paying attention to reverse logistics (RL) issues due to growing environmental concerns, competitive advantage, promising financial potential, legislative reasons and social responsibility. This study... more
Researchers and practitioners are paying attention to reverse logistics (RL) issues due to growing environmental concerns, competitive advantage, promising financial potential, legislative reasons and social responsibility. This study aims to examine the contextual relationship and interactions among barriers to implement RL practices in the computer supply chain of Bangladesh. We applied Interpretive Structural Modeling (ISM) technique to diagnose significant barriers and proposed a hierarchical framework for investigating the relationships among them. We also used MICMAC (Matriced' Impacts Croisés Multiplication Appliquée a ´ unClassement) analysis to classify the barriers based on the driving power and dependence among them. Seven barriers were finalized in the Bangladesh context based on the previous literature and professional feedback. The findings reveal that financial constraints along with the lack of interest from top management are the most influential barriers to RL for the computer supply chains of Bangladesh. The ISM-based analysis can provide managers with insights for developing strategies for implementing RL practices in the computer supply chain of Bangladesh.
Research Interests:
Green supply chain management (GSCM) has attracted much attention in the last few years in academia and industries. Presently, stakeholders, buyer and customers are becoming more aware of the sustainable environment and sustainable... more
Green supply chain management (GSCM) has attracted much attention in the last few years in academia and industries. Presently, stakeholders, buyer and customers are becoming more aware of the sustainable environment and sustainable development. In Bangladesh, the government is taking initiatives to implement strict rules and regulations, which have imposed huge pressure on the manufacturing industries to adopt green supply chain practices to reduce the environmental impact of their supply chains, as well as buyers are imposing huge pressure to adopt GSCM practices. The main aim of this paper is to identify critical success factors (CSFs) to implement green supply chain management practices in the footwear industry in Bangladesh. In this work, critical success factors have been evaluated, and their contextual relationships between CSFs have been established by interpretive structural modeling (ISM) approach. Along with this, the importance of the CSFs on the basis of their driving and dependence power has been determined by MICMAC analysis. 'Support & commitment of top management' has been identified as most important CSF that may force industries to implement GSCM practices to make their business sustainable. A case study of Bangladeshi footwear industry is presented to show the real world applicability of the proposed model.
Research Interests:
This paper predicts the time moment of upcoming heavy rainfall in Bangladesh using grey disaster forecasting model. GM (1, 1) model is applied to two models of yearly rainfall data and monsoon rainfall data for the simulation of available... more
This paper predicts the time moment of upcoming heavy rainfall in Bangladesh using grey disaster forecasting model. GM (1, 1) model is applied to two models of yearly rainfall data and monsoon rainfall data for the simulation of available data. Simulation result generates average relative error of 1.55% and 3.13% which satisfies error criterion to make the prediction. Therefore, we predict that yearly rainfall will be higher than 2000mm in 2018 and monsoon rainfall will be higher than 1500mm in 2017.
Research Interests:
To cite this article: Jamal Hossen, Nafis Ahmad & Syed Mithun Ali (2017): An application of Pareto analysis and cause-and-effect diagram (CED) to examine stoppage losses: a textile case from Bangladesh, The Journal of The Textile Institute,
This paper investigates the coordination problem of a supply chain system composed of one supplier and one retailer. To coordinate, we apply revenue sharing contracts in the context of supply chain disruptions management. Herein, we... more
This paper investigates the coordination problem of a supply chain system composed of one supplier and one retailer. To coordinate, we apply revenue sharing contracts in the context of supply chain disruptions management. Herein, we consider disruptions at two factors namely demand and service sensitivity coefficient and propose a responsive pricing, service level, production and contract decisions model. Our results reveal that the proposed coordination mechanisms could lead to the supply chain system of interest achieving around 80% to 90% efficiency while satisfying win-win positions of the partners. In addition, this work illustrates that the coordinated supply chain produces more profit to the retailer. Our findings also indicate the original contracts for the non-disrupted supply chain system show some level of robustness to the scenarios that show a small increase of the market scale and service sensitivity coefficient. More specifically, the original contracts work fine as long as the increment of markets scale is less than 30% of the market base. However, for most of the cases, the production, pricing, service strategies, and contracts policies need to be adjusted to tackle the disruptions. We show the usefulness of our work by providing some numerical examples. Supply Chain Management, Operations and Supply Chain Management, etc. His research interest includes supply chain disruptions management and application of artificial intelligence in manufacturing/service planning and decision making.
Research Interests:
Research Interests:
Research Interests:
This paper studies price and service competition of a supply chain consisting of one manufacturer and multiple retailers while taking real-time demand disruptions into consideration at the retail markets. In this system, the re-tailers... more
This paper studies price and service competition of a supply chain consisting of one manufacturer and multiple retailers while taking real-time demand disruptions into consideration at the retail markets. In this system, the re-tailers outsourced product from a fixed supplier and deter-mine their own retail price and service level with an aim to optimize their profit. This could be achieved for the given wholesale price determined by the supplier. The supplier also targets to maximize his profit from the wholesale price. Thus, our works develop a two-period planning model with an emphasis on demand disruptions. In supply chain plan-ning stage, we determine the optimal retail price, optimal wholesale price and optimal service level without consider-ing disruptions. This plan demands revision in the execution stage when retail markets suffer disruptions in real time due to emergent events. In order to achieve those aims, first we investigate a game theoretical perspective namely Man-ufacturing Stackelberg (MS) strategy in a decentralized supply chain environment. In the next, we examine the optimal retail price and service level under a centralized supply chain setting. The models are illustrated and examined through some numerical insights. Additionally, we numerically investigate the effect of demand and cost disruptions together on the supply chain decisions under similar settings.
Research Interests:
We develop an analytical framework of a multiproduct supply chain system composed of multiple suppliers, multiple distribution centers and multiple customers considering disruptions risk. Unlike traditional single sourcing strategy which... more
We develop an analytical framework of a multiproduct supply chain system composed of multiple suppliers, multiple distribution centers and multiple customers considering disruptions risk. Unlike traditional single sourcing strategy which is mostly discussed in supply chain literature, we apply multi-sourcing strategy in both procurement and distribution of commodities. The model thus developed determines the location of distribution centers from a set of potential location, shipment decisions from multiple suppliers to multiple distribution centers and shipment decisions from multiple distribution centers to multiple customers. Moreover, the model evaluates potential amount of products shortages in the event of disruptions. In our work, we consider disruptions at candidate locations for distribution centers and to the suppliers. The analytical framework is formulated as a mixed integer programming (MIP) model which minimizes the sum of investment cost, the transportation cost and the expected shortage cost. We consider several numerical instances to examine the benefit and practicability of the proposed model. Finally, we compare the results of the risk concern optimization framework to the basic optimization framework. From the results, it is expected that risk concern model would outperform the basic model in the case of disruptions.
Research Interests:
In the competitive business environment, there exist high levels of interactions between components/agents of a supply chain. However, these interactions are further amplified by uncertain events caused by natural and man-made actions.... more
In the competitive business environment, there exist high levels of interactions between components/agents of
a supply chain. However, these interactions are further amplified by uncertain events caused by natural and man-made
actions. The two common modes of disruptions are supply and demand disruption in practice. The supply chain of
an enterprise is highly sensitive to supply and demand disruption. In this work, we thus integrate supply and demand
disruptions and a mathematical optimization approach is proposed to formulate a scenario-based supply chain disruptions
management framework. The model presented in this paper makes an attempt to determine the ordering portfolio to the
selected set of suppliers in a pre-disruption and post-disruption situation using a scenario-based approach. However, the
model tries to capture quality performance of the suppliers, along with delivery performance of the outside suppliers an
enterprise asks for as a whole. We minimize the sum of purchasing cost from local supplier and the expected cost in the
event of disruptions. The demand and the fraction of order supplied by the outside suppliers are assumed to be normal
probability distribution with mean value and associated standard deviation. In a disruption scenario, the discrete values
of demand and order fraction are taken from random number generation. GAMS-CPLEX 24.1.3 software is used to solve
the model. The proposed model could provide an effective tool to actively react to disruptions that could happen in the
supply chain of an enterprise. The application of the proposed framework is illustrated through a hypothetical case study.
a supply chain. However, these interactions are further amplified by uncertain events caused by natural and man-made
actions. The two common modes of disruptions are supply and demand disruption in practice. The supply chain of
an enterprise is highly sensitive to supply and demand disruption. In this work, we thus integrate supply and demand
disruptions and a mathematical optimization approach is proposed to formulate a scenario-based supply chain disruptions
management framework. The model presented in this paper makes an attempt to determine the ordering portfolio to the
selected set of suppliers in a pre-disruption and post-disruption situation using a scenario-based approach. However, the
model tries to capture quality performance of the suppliers, along with delivery performance of the outside suppliers an
enterprise asks for as a whole. We minimize the sum of purchasing cost from local supplier and the expected cost in the
event of disruptions. The demand and the fraction of order supplied by the outside suppliers are assumed to be normal
probability distribution with mean value and associated standard deviation. In a disruption scenario, the discrete values
of demand and order fraction are taken from random number generation. GAMS-CPLEX 24.1.3 software is used to solve
the model. The proposed model could provide an effective tool to actively react to disruptions that could happen in the
supply chain of an enterprise. The application of the proposed framework is illustrated through a hypothetical case study.
Research Interests:
U-shaped assembly lines are useful in an efficient allocation of workers to stations. In assembly lines, temporary workers are placed to correspond to the fluctuation of demand. Sets of feasible tasks for temporary workers are different... more
U-shaped assembly lines are useful in an efficient allocation of workers to stations. In assembly lines, temporary workers are placed to correspond to the fluctuation of demand. Sets of feasible tasks for temporary workers are different from those of permanent workers. The tasks which are familiar to permanent workers also vary. For the U-shaped assembly balancing problem under these situations the optimal cycle times for a given number of temporary workers and the optimal number of workers for given cycle time are derived and compared between U-shaped line balancing and straight line balancing. We also discuss the optimal allocation for a single U-shaped line and two U-shaped lines. In several cases, in particular when high throughputs are required, it is shown numerically that the number of temporary workers in optimal allocation for two lines is less than that of optimal allocation for a single line.
Research Interests:
The mixed model assembly line is becoming more important than the traditional single model due to the increased demand for higher productivity. In this paper, a set of procedures for mixed-model assembly line balancing problems (MALBP)... more
The mixed model assembly line is becoming more important than the traditional single model due to the
increased demand for higher productivity. In this paper, a set of procedures for mixed-model assembly line
balancing problems (MALBP) is proposed to make it efficiently balance. The proposed procedure based on
the meta heuristics genetic algorithm can perform improved and efficient allocation of tasks to workstations
for a pre-specified production rate and address some particular features, which are very common in a real
world mixed model assembly lines (e.g. use of parallel workstations, zoning constraints, resource limitation).
The main focus of this study is to study and modify the existing genetic algorithm framework. Here a heuristic
is proposed to reassign the tasks after crossover that violates the constraints. The new method minimises the
total number of workstation with higher efficiency and is suitable for both small and large scale problems.
The method is then applied to solve a case of a plastic bag manufacturing company where the minimum
number of workstations is found performing more efficiently.
increased demand for higher productivity. In this paper, a set of procedures for mixed-model assembly line
balancing problems (MALBP) is proposed to make it efficiently balance. The proposed procedure based on
the meta heuristics genetic algorithm can perform improved and efficient allocation of tasks to workstations
for a pre-specified production rate and address some particular features, which are very common in a real
world mixed model assembly lines (e.g. use of parallel workstations, zoning constraints, resource limitation).
The main focus of this study is to study and modify the existing genetic algorithm framework. Here a heuristic
is proposed to reassign the tasks after crossover that violates the constraints. The new method minimises the
total number of workstation with higher efficiency and is suitable for both small and large scale problems.
The method is then applied to solve a case of a plastic bag manufacturing company where the minimum
number of workstations is found performing more efficiently.
Research Interests:
This paper develops an artificial neural network (ANN) model to forecast the optimum level of raw materials inventory as a function of product demand, manufacturing lead-time, supplier reliability, material holding cost, and material... more
This paper develops an artificial neural network (ANN) model to forecast the
optimum level of raw materials inventory as a function of product demand,
manufacturing lead-time, supplier reliability, material holding cost, and material
cost. The model selects a feed-forward back-propagation ANN with twelve hidden
neurons as the optimum network. We test the model with pharmaceutical
company data. The results show that the model can be useful to forecast raw
material inventory level in response to different parameters. We also compare the
model with fuzzy inference system (FIS) and simple economic order quantity
(EOQ). It can be seen that ANN model outperforms others. Overall, the model
can be applied for forecasting of raw materials inventory for any manufacturing
enterprise in a competitive business environment.
optimum level of raw materials inventory as a function of product demand,
manufacturing lead-time, supplier reliability, material holding cost, and material
cost. The model selects a feed-forward back-propagation ANN with twelve hidden
neurons as the optimum network. We test the model with pharmaceutical
company data. The results show that the model can be useful to forecast raw
material inventory level in response to different parameters. We also compare the
model with fuzzy inference system (FIS) and simple economic order quantity
(EOQ). It can be seen that ANN model outperforms others. Overall, the model
can be applied for forecasting of raw materials inventory for any manufacturing
enterprise in a competitive business environment.
Research Interests:
The parametric interpolators of modern CNC machines use Taylor’s series approximation to generate successive parameter values for the calculation of x, y, z coordinates of tool positions. In order to achieve greater accuracy, higher order... more
The parametric interpolators of modern CNC machines use Taylor’s
series approximation to generate successive parameter values for the
calculation of x, y, z coordinates of tool positions. In order to achieve greater
accuracy, higher order derivatives are required at every sampling period which
complicates the calculation for contours represented by NURBS curve. In
addition, this method calculates the chordal error in a given segment through
estimation of the curvature neglecting a fraction of the error. In order to avoid
calculating higher derivatives and make the calculations simpler, this paper
proposes the classical fourth-order Runge-Kutta (RK) method for the
determination of successive tool positions requiring the calculation of the first
derivatives only. Furthermore, a method of estimating the chordal error on the
average value of parameters at the end points of a given curve segment is
proposed here that does not require the calculation of curvature at every
segment. Finally, a variable feedrate interpolation scheme is designed
combining the RK method of parameter calculation and the proposed method
of chordal error calculation. Results show that reduced chordal error and
feedrate fluctuations are achievable with the proposed interpolator compared to
the conventional interpolator based on Taylor’s approximation with higher
order terms.
series approximation to generate successive parameter values for the
calculation of x, y, z coordinates of tool positions. In order to achieve greater
accuracy, higher order derivatives are required at every sampling period which
complicates the calculation for contours represented by NURBS curve. In
addition, this method calculates the chordal error in a given segment through
estimation of the curvature neglecting a fraction of the error. In order to avoid
calculating higher derivatives and make the calculations simpler, this paper
proposes the classical fourth-order Runge-Kutta (RK) method for the
determination of successive tool positions requiring the calculation of the first
derivatives only. Furthermore, a method of estimating the chordal error on the
average value of parameters at the end points of a given curve segment is
proposed here that does not require the calculation of curvature at every
segment. Finally, a variable feedrate interpolation scheme is designed
combining the RK method of parameter calculation and the proposed method
of chordal error calculation. Results show that reduced chordal error and
feedrate fluctuations are achievable with the proposed interpolator compared to
the conventional interpolator based on Taylor’s approximation with higher
order terms.
Research Interests:
Minimum quantity lubrication (MQL) refers to the use of cutting fluids of only a minute amount typically of a flow rate of 50 to 500 ml/hour which is about three to four orders of magnitude lower than the amount commonly used in flood... more
Minimum quantity lubrication (MQL) refers to the use of cutting fluids of only a minute amount
typically of a flow rate of 50 to 500 ml/hour which is about three to four orders of magnitude
lower than the amount commonly used in flood cooling condition. The concept of minimum
quantity lubrication (MQL) has been suggested since a decade ago as a means of
addressing the issues of environmental intrusiveness and occupational hazards associated
with the airborne cutting fluid particles on factory shop floors. This paper deals with
experimental investigation on the role of MQL by cutting oil on chip thickness ratio, cutting
temperature, cutting forces, tool wear and surface roughness in turning medium carbon steel
at industrial speed-feed combinations by uncoated carbide insert. The encouraging results
include significant reduction in tool wear rate, dimensional inaccuracy and surface roughness
by MQL over dry machining mainly through reduction in the cutting zone temperature and
favourable change in the chip-tool and work-tool interaction. The results reveals that the
MQL system can enable significant improvement in productivity, product quality and overall
machining economy even after covering the additional cost of designing and implementing
MQL system
typically of a flow rate of 50 to 500 ml/hour which is about three to four orders of magnitude
lower than the amount commonly used in flood cooling condition. The concept of minimum
quantity lubrication (MQL) has been suggested since a decade ago as a means of
addressing the issues of environmental intrusiveness and occupational hazards associated
with the airborne cutting fluid particles on factory shop floors. This paper deals with
experimental investigation on the role of MQL by cutting oil on chip thickness ratio, cutting
temperature, cutting forces, tool wear and surface roughness in turning medium carbon steel
at industrial speed-feed combinations by uncoated carbide insert. The encouraging results
include significant reduction in tool wear rate, dimensional inaccuracy and surface roughness
by MQL over dry machining mainly through reduction in the cutting zone temperature and
favourable change in the chip-tool and work-tool interaction. The results reveals that the
MQL system can enable significant improvement in productivity, product quality and overall
machining economy even after covering the additional cost of designing and implementing
MQL system
Research Interests:
Quality is considered to be vital issue in improving productivity. A Process Capability Index (PCI) has been considered as a valuable and popular tool to express the Capability of a Process and assure quality of product. This paper... more
Quality is considered to be vital issue in improving productivity. A Process Capability Index
(PCI) has been considered as a valuable and popular tool to express the Capability of a
Process and assure quality of product. This paper summarizes the characteristics of the
Process Capability Index, Cpk with different sample size for both real and simulated data. It
also tries to examine the behavior of Cpk with different distributions. In this paper, two
population distributions were considered, i.e., Normal and Exponential with different values
of sample sizes to ascertain sample size effect on Process Capability Index, Cpk. The
Simulation was performed by using Engineering software MATLAB 7.0. From the result, it
was found that mean value of Cpk decreases up to sample size 15; then the value becomes
reasonably constant and hence Cpk Vs sample size graph tends to be flatter.
(PCI) has been considered as a valuable and popular tool to express the Capability of a
Process and assure quality of product. This paper summarizes the characteristics of the
Process Capability Index, Cpk with different sample size for both real and simulated data. It
also tries to examine the behavior of Cpk with different distributions. In this paper, two
population distributions were considered, i.e., Normal and Exponential with different values
of sample sizes to ascertain sample size effect on Process Capability Index, Cpk. The
Simulation was performed by using Engineering software MATLAB 7.0. From the result, it
was found that mean value of Cpk decreases up to sample size 15; then the value becomes
reasonably constant and hence Cpk Vs sample size graph tends to be flatter.
Research Interests:
Tool wear and surface roughness prediction plays a significant role in machining industry for proper planning and control of machining parameters and optimization of cutting conditions. This paper deals with developing an artificial... more
Tool wear and surface roughness prediction plays a
significant role in machining industry for proper planning and control
of machining parameters and optimization of cutting conditions. This
paper deals with developing an artificial neural network (ANN)
model as a function of cutting parameters in turning steel under
minimum quantity lubrication (MQL). A feed-forward
backpropagation network with twenty five hidden neurons has been
selected as the optimum network. The co-efficient of determination
(R2) between model predictions and experimental values are 0.9915,
0.9906, 0.9761 and 0.9627 in terms of VB, VM, VS and Ra
respectively. The results imply that the model can be used easily to
forecast tool wear and surface roughness in response to cutting
parameters.
significant role in machining industry for proper planning and control
of machining parameters and optimization of cutting conditions. This
paper deals with developing an artificial neural network (ANN)
model as a function of cutting parameters in turning steel under
minimum quantity lubrication (MQL). A feed-forward
backpropagation network with twenty five hidden neurons has been
selected as the optimum network. The co-efficient of determination
(R2) between model predictions and experimental values are 0.9915,
0.9906, 0.9761 and 0.9627 in terms of VB, VM, VS and Ra
respectively. The results imply that the model can be used easily to
forecast tool wear and surface roughness in response to cutting
parameters.
Research Interests:
Minimum Quantity Lubrication (MQL) is one of the most recent and increasingly popular methods of cooling the job-tool interface in machining process. It drew the researcher and industry’s attention for its excellent performance in cooling... more
Minimum Quantity Lubrication (MQL) is one of the most recent and increasingly popular methods of
cooling the job-tool interface in machining process. It drew the researcher and industry’s attention for its
excellent performance in cooling i.e. increasing tool life by reducing tool wear and for its modest effect on
environment. Cutting tool use for machining bare metal bears the biggest share of machining cost.
Minimizing the tool wear thus in a very logical way minimize production cost. Moreover, as machining with
a weared edge of a tool degrades the surface finish of the product, it can also be considered as a quality
parameter. In this paper an attempt has been made to model the tool wear of a multiple edge cutting tool
in machining medium carbon steel under MQL condition using Response Surface Methodology (RSM) and
Adaptive Neuro Fuzzy Inference System (ANFIS). The combined effect of three machining parameter
cutting speed (V), Depth of Cut (d) and machining time (t) on principle flank wear is investigated. Here
Optimum membership functions are developed by using a neuro adaptive approach combining back
propagation along with least square estimation. Contour and surface plots are generated to study the
effect of input parameters and their interactions on the output. After calculating the error a brief comparison
is made to uncover the strength of each model to predict the desired output for any input data over a
feasible range.
cooling the job-tool interface in machining process. It drew the researcher and industry’s attention for its
excellent performance in cooling i.e. increasing tool life by reducing tool wear and for its modest effect on
environment. Cutting tool use for machining bare metal bears the biggest share of machining cost.
Minimizing the tool wear thus in a very logical way minimize production cost. Moreover, as machining with
a weared edge of a tool degrades the surface finish of the product, it can also be considered as a quality
parameter. In this paper an attempt has been made to model the tool wear of a multiple edge cutting tool
in machining medium carbon steel under MQL condition using Response Surface Methodology (RSM) and
Adaptive Neuro Fuzzy Inference System (ANFIS). The combined effect of three machining parameter
cutting speed (V), Depth of Cut (d) and machining time (t) on principle flank wear is investigated. Here
Optimum membership functions are developed by using a neuro adaptive approach combining back
propagation along with least square estimation. Contour and surface plots are generated to study the
effect of input parameters and their interactions on the output. After calculating the error a brief comparison
is made to uncover the strength of each model to predict the desired output for any input data over a
feasible range.
Research Interests:
Total Productive Maintenance (TPM) is a manufacturing program whose sole purpose is to maximize the effectiveness of equipment throughout its entire life by the participation and motivation of the entire workforce. The three main... more
Total Productive Maintenance (TPM) is a manufacturing program whose sole purpose is to maximize the effectiveness of equipment throughout its entire life by the participation and motivation of the entire workforce. The three main objectives of TPM are zero defects, zero breakdowns and zero accidents. These goals can be achieved through implementation of activities planned to increase equipment efficiency, the creation of a program of autonomous maintenance, the establishing of a planned maintenance system, the organization of training courses for workers and design of plant management system. This paper addresses the issue of implementing the total productive maintenance (TPM) philosophy in a pharmaceutical industry. In the first phase, the possible losses and the factors contributing to those losses have been identified. The critical factors which affect the overall equipment efficiency (OEE) of the pharmaceutical industry are loading time, down time, standard cycle time, actual cycle time, unit produced and defect unit. Overall equipment efficiency (OEE) is an indication of eight major equipment related losses which are equipment failure, set-up and adjustment, cutting blade change, start-up, minor stoppage and idling, speed, defect and rework and equipment shutdown. In the second phase of TPM implementation, a planned maintenance program has been suggested to make the production process quite smooth and proficient with increased efficiency.
Research Interests:
This paper develops an artificial neural network (ANN) model to determine tool wear parameters such as average principal flank wear, average auxiliary flank wear, average maximum flank wear and average surface roughness as a function of... more
This paper develops an artificial neural network (ANN) model to determine tool wear parameters such as average
principal flank wear, average auxiliary flank wear, average maximum flank wear and average surface roughness as a
function of cutting speed, feed rate, depth of cut and machining time. The model selects a feed-forward backpropagation
ANN with twenty five hidden neurons as the optimum network. We test the model with marching data from
a real field. The results show that the model can be useful to forecast tool wear and surface roughness in response to
the model parameters under minimum quantity lubrication (MQL) environment.
principal flank wear, average auxiliary flank wear, average maximum flank wear and average surface roughness as a
function of cutting speed, feed rate, depth of cut and machining time. The model selects a feed-forward backpropagation
ANN with twenty five hidden neurons as the optimum network. We test the model with marching data from
a real field. The results show that the model can be useful to forecast tool wear and surface roughness in response to
the model parameters under minimum quantity lubrication (MQL) environment.
Research Interests:
The importance of workplace environment and safety are getting increasing attention among researchers for decades. Each company needs to develop safety programs, procedures, policies and plans for their specific workplace. This can... more
The importance of workplace environment and safety are getting
increasing attention among researchers for decades. Each company needs to
develop safety programs, procedures, policies and plans for their specific
workplace. This can include a wide range of ideas, depending on what type of
workplace environment and safety issues are of concern for the organisation.
Workplace hazards and safety concerns need to be identified along with ways
to handle them effectively to ensure a safe workplace and thus maintaining
productivity of the organisation. Workplace environment and safety directly or
indirectly influence the quality of products and productivity of an organisation
to a great extent. This paper addresses some issues on workplace environment
and safety in a battery manufacturing company named Rahimafrooz Batteries
Ltd. (RBL) and some recommendations have been suggested to handle those
issues in an efficient and effective manner.
increasing attention among researchers for decades. Each company needs to
develop safety programs, procedures, policies and plans for their specific
workplace. This can include a wide range of ideas, depending on what type of
workplace environment and safety issues are of concern for the organisation.
Workplace hazards and safety concerns need to be identified along with ways
to handle them effectively to ensure a safe workplace and thus maintaining
productivity of the organisation. Workplace environment and safety directly or
indirectly influence the quality of products and productivity of an organisation
to a great extent. This paper addresses some issues on workplace environment
and safety in a battery manufacturing company named Rahimafrooz Batteries
Ltd. (RBL) and some recommendations have been suggested to handle those
issues in an efficient and effective manner.
Research Interests:
Chip tool interface temperature control is one of the critical factors during machining because it influences substantially the chip formation mode, cutting forces, tool life, surface finish and product quality. In this paper an... more
Chip tool interface temperature control is one of the critical factors during machining because it influences
substantially the chip formation mode, cutting forces, tool life, surface finish and product quality. In this paper an
artificial neural network (ANN) model has been developed as a function of cutting parameters in turning steel for
predicting chip tool interface temperature. The cutting parameters used include cutting speed, feed rate and depth of
cut. A feed-forward back propagation network with ten hidden neurons has been selected as the optimum network
by trial and error method. The co-efficient of determination (R2) between model prediction and experimental value
is found 0.9965. The result implies that, the model can be successfully used to forecast chip tool interface
temperature in response to the cutting parameters for which the model has been constructed.
substantially the chip formation mode, cutting forces, tool life, surface finish and product quality. In this paper an
artificial neural network (ANN) model has been developed as a function of cutting parameters in turning steel for
predicting chip tool interface temperature. The cutting parameters used include cutting speed, feed rate and depth of
cut. A feed-forward back propagation network with ten hidden neurons has been selected as the optimum network
by trial and error method. The co-efficient of determination (R2) between model prediction and experimental value
is found 0.9965. The result implies that, the model can be successfully used to forecast chip tool interface
temperature in response to the cutting parameters for which the model has been constructed.
Research Interests:
organizations in pursuing their sustainable supply chain objectives. The research purpose was to gain a better understanding of the organizational design features that firms currently use or may use in the future. The results should... more
organizations in pursuing their sustainable supply chain objectives. The research purpose was
to gain a better understanding of the organizational design features that firms currently use or
may use in the future. The results should encourage organizations to address design issues as
they relate to overall supply chain effectiveness. The ever-increasing influences of the wider
perspectives such as the pursuit of sustainability drive for industry consolidation/
rationalization and the need for responding to changing customer preferences may mean the
conventional wisdom of organizing for success is increasingly becoming grossly inadequate, if
not obsolete. There are numerous reasons why companies start to rethink about organizational
design, organizational structure and its performance to attain a supply chain sustainability
journey. Primary among them is to ensure compliance with laws and regulations and to adhere
to and support international principles for sustainable business conduct. In addition, companies
are increasingly taking actions that result in better social, economic and environmental impacts
because society expects this and because there are business benefits to doing so. Given the
dynamics of the current competitive global supply landscape, organizational design concerns
are critical to sustained organizational success.
to gain a better understanding of the organizational design features that firms currently use or
may use in the future. The results should encourage organizations to address design issues as
they relate to overall supply chain effectiveness. The ever-increasing influences of the wider
perspectives such as the pursuit of sustainability drive for industry consolidation/
rationalization and the need for responding to changing customer preferences may mean the
conventional wisdom of organizing for success is increasingly becoming grossly inadequate, if
not obsolete. There are numerous reasons why companies start to rethink about organizational
design, organizational structure and its performance to attain a supply chain sustainability
journey. Primary among them is to ensure compliance with laws and regulations and to adhere
to and support international principles for sustainable business conduct. In addition, companies
are increasingly taking actions that result in better social, economic and environmental impacts
because society expects this and because there are business benefits to doing so. Given the
dynamics of the current competitive global supply landscape, organizational design concerns
are critical to sustained organizational success.
Research Interests:
This paper identifies typical hazard and risk elements in a manufacturing organization, studies management elements currently used in the organization, and presents an Analytic Hierarchy Process (AHP) decision model for assessing the... more
This paper identifies typical hazard and risk elements in a manufacturing organization, studies management elements currently used in the organization, and presents an Analytic Hierarchy Process (AHP) decision model for assessing the priority of safety management elements. Specifically, the paper addresses a hierarchy decision model for assessing the priority of safety management elements of a battery manufacturing company in Bangladesh. Safety management elements and decision criteria are identified by using OSHA and NIOSH standards. Empirical data are collected through personal interviews with safety personnel, experts and professionals in the battery manufacturing company and through spot surveying. Using the Analytical Hierarchy Process, a list of six decision criteria and ten safety management elements, which constitute the AHP alternatives, are identified and their relative importance is evaluated. Using AHP methodology, the top three safety elements that have been identified and are needed to implement a Safety Management System (SMS) include a personal protection program, emergency preparedness and safety organization. The identification of core decision criteria and safety management elements found in this research may be useful for effective implementation of SMS in manufacturing organizations.