wahad hasan

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.

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.