Enabling CPS and simulation-based multi-objective optimisation for material handling of reconfigurable manufacturing systems

Abstract

Abstract Reconfigurable manufacturing systems (RMS), cyber-physical systems (CPS) and simulation-based multi-objective optimisation (SMO) are essential for addressing the dynamic behaviour of materials and information in manufacturing. However, the lack of consideration for material handling jeopardises recent advances in these fields. Accordingly, this study proposes the use of CPSs including SMO to address the dynamic allocation of resource of material handling in the configuration analysis (CA) of RMSs and enhance operational performance. We focus on CA because of its influence on the arrangement of machines, equipment selection, and operational assignments, influencing the performance of RMS. The study presents a proof-of-concept CPS and SMO in a laboratory environment for evaluating trade-off solutions including throughput, buffer capacity, lead-time, and resources in material handling. This study contributes to the existing literature in three ways. First, it proposes a CPS architecture that includes physical, cyber, and digital service layers for applying SMO in the CA of RMS. Second, it presents a procedure for SMO, including initialization, environment, optimisation engine, and outputs, and applies NSGA-II to improve the existing calculations of the CA of RMS. Third, it shows benefits the operational performance of applying CPS and SMO to address the dynamic behaviour of material handling in the CA of RMS.