(untitled) (International Journal of Food and Nutritional Sciences, 2022)
Considerable research has been dedicated to the field of Flexible Manufacturing Systems (FMS) planning, with a predominant focus on established academic scheduling systems. Nevertheless, when it pertains to the selection process, which often hinges on fundamental principles within the intelligent system known as JSSE (Workshop Planning Environment), there is a noticeable dearth of literature concerning their effectiveness within an FMS. This article endeavours to bridge this void by scrutinizing the performance model of machine and Automated Guided Vehicle (AGV) scheduling, specifically in terms of mean flow time, using the Embedded System (ES) strategy. The research employs an FMS simulation model to conduct experiments, encompassing 40 scenarios designed to evaluate these concepts.