REVIEW OF SIMULATION-BASED OPTIMIZATION APPROACHES FOR THE ADAPTIVE SCHEDULING AND CONTROL OF DYNAMIC PRODUCTION SYSTEMS

Abstract

The performance of complex manufacturing systems in fast-moving and competitive environments is directly influenced by the scheduling and control of production, which need to cope with systems complexity and stochastic behaviour as well as to handle internal and external dynamic influences. In this context, cyberphysical systems and industry 4.0 concepts and technologies, which allow the real-time availability of system state data and the interconnectedness of information and material flows, can support the enhancement of scheduling and control processes. In this direction, the adaptive scheduling and control of dynamic production systems by means of hybrid simulation and optimisation approaches, which can take advantage of system state data visibility, possess great scientific and industrial relevance. This work aims to report the state of the art in simulation-based optimisation of dynamic production systems supported by cyber-physical systems. The research systematically analyses the published literature and outlines main trends as well as the current gaps, discussing future prospects for the adaptive scheduling and control of production systems. It was substantiated that systems with greater complexity, dynamicity and randomness impel the application of simulation-based optimization approaches supported by cyber physical systems and industry 4.0 concepts and technologies.