Enhancing the performance parameters of flexible manufacturing system using decision-making techniques

Due to varying requirements of customers, it became difficult for manufacturing firms to sustain their position in the market. Because of this, firms are finding and implementing new technologies in existing system and flexible manufacturing system (FMS) is one of the solutions for this problem. FMS is an automatic manufacturing system, capable of producing a wide variety of products with good quality. However, the cost of implementing FMS is high. So, decisions related with various parameters in implementing and managing the system, is one of the crucial steps in FMS. In present work, emphasis is done on developing a methodology that can make an appropriate decision of selecting best experiment level, by using simple calculations that can save money and time. For doing so, a relative study of decision-making approaches that combines Shannon entropy and weighted aggregated sum product assessment (WASPAS) method is performed for solving the selection problem of operating conditions. Criteria's weight is calculated first by Shannon entropy method. Later, alternatives were ranked by using calculated weights in WASPAS method. Based on obtained ranking, management could take verdicts for refining the performance parameters of the system.