Simulation Optimization Framework for Online Deployment and Adjustment of Reconfigurable Machines in Job Shops

Abstract

In the era of Industry 4.0, to cope with the complex, volatile and fiercely competitive market environment, factories have to become more and more intelligent, flexible, and agile. This paper studies the reconfigurable machine deployment and adjustment problem in the multi-product job shop. This problem belongs to production process control and is part of the digital factory, as it forecasts the future performance for the adjustment of the reconfigurable machines in an online manner. To be more specific, we design an online simulation control system based on digital twin, which integrates the function of monitoring, decision-making and control. We use simulation optimization and design heuristic algorithm to solve the multi-objective capacity adjustment decision-making problem. The simulation results show the effectiveness and stability of the system and can be used to cope with the complex and ever-changing industrial environment such as machine breakdowns and rush orders.