Comparative study of autonomous production control methods using simulation

Manufacturing companies need to be effective in meeting customers’ delivery requirements. Due to customers’ expectations of shrinking delivery times, manufacturing lead times need to be short. This can be achieved through efficient Production Activity Control (PAC) methods. Currently PAC methods rely mostly on centralized decision-making and, seeming not to be adequate to deal with the increasing complexity and dynamics of manufacturing. Autonomous Production Control (APC) methods are a promising alternative to current methods, due to their rapid and flexible reaction to disturbances of the production systems’ operation. APC methods transfer the power of decision-making from a central unit to distributed logistic objects, such as machines, jobs and material handling devices. In this study, three APC methods, namely Pheromones (PHE), QLE (Queue Length Estimator) and a refined version of QLE (RQLE), are compared and analysed via simulation. The study was accomplished for two shop configurations, namely a flexible flow shop and a general flexible flow shop. Simulation results show a superior performance of RQLE in both configurations. Results also show that a new dispatching rule here proposed, the SPT-RTT rule, performs better than others with which it was compared. The study may have important implications for industrial practice and future research in PAC.
This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020.INCT-EN - Instituto Nacional de Ciência e Tecnologia para Excitotoxicidade e Neuroproteção(UIDB/00319/2020)