An integrated fuzzy MCDM approach formanufacturing process improvement in MSMEs

To deal with dynamic customer preferences and global competition, Medium, Small and Micro Enterprises (MSMEs) are striving to improve customer satisfaction by enhancing their process capability, optimising resource utilization and achieving cost effectiveness. Manufacturing line inMSMEs involves a number of complex processes and process variations lead to rejections of poor quality products resulting in monetary losses and customer dissatisfaction. Delivery of high quality product within constraints of manpower, machinery and other limited resources stipulates the need to improve the process performance of manufacturing line through quality management. With this perspective, the present work proposes a framework to identify and prioritize defects by integrating multicriteria decision making techniquesFuzzy Decision Making Trial and Evaluation Laboratory and Fuzzy Analytic Network Process with Quality Management Practices. The integration filters out most influential defects prior to data collection and prioritize them to reach out to critical defects of manufacturing process. Additionally, it addresses challenges faced by management in terms of large number of defects, insufficient data on defects and dependency among selected criteria. The proposed framework is exhibited with the help of a real case study. It is practically relevant in deriving decision support solutions for improving performance ofmanufacturing line inMSME firms. By virtue of the results, key areas are identified to augment responsiveness to government policies and MSME's proficiency to overcome resource constraints.

Automated summary

To enhance the process performance of manufacturing lines, Medium, Small and Micro Enterprises (MSMEs) are striving to improve customer satisfaction by improving process capability, optimizing resource utilization, and achieving cost effectiveness. This study proposes a framework that integrates decision-making techniques and quality management practices to identify and prioritize defects in the manufacturing process, aiming to improve responsiveness to government policies and overcome resource constraints.