Abstract
The adaptability of Reconfigurable Manufacturing Systems (RMSs) to ever-changing product demand and their responsiveness to unpredictable events has made them a popular solution for modern manufacturing in today’s competitive industries. The proper scheduling of RMSs is important in ensuring optimal resource utilization, achieving production objectives, and responding to dynamic changes in a realtime. This study aims to tackle job scheduling and workforce planning in RMSs by considering dynamic events, such as the risk of machine unavailability, and human factors in the manufacturing process, to minimize the makespan and delay-related cost. At first, a comprehensive framework for dynamic optimization in an RMS environment has been developed. A multi-level bi-objective mathematical modeling presented to address job scheduling and workforce planning proposed as a MILP model. Finally, numerical studies evaluated two scenarios: risk and human factors addressed or not, for small to medium-sized cases. The results demonstrate a significant gap between these scenarios.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
