Distributed joint dynamic maintenance and production scheduling in manufacturing systems: Framework based on model predictive control and Benders decomposition

Scheduling the maintenance based on condition, respectively degradation level of system leads to improved system's reliability while minimizing cost. Since changes dynamically during operation, we face a dynamic scheduling problem. In this paper, address manufacturing systems their level. The consists several units with defined capacity and an individual model, seeking optimize reward. sell production capacity, maintaining state prevent failures. are jointly responsible for fulfilling demand system. This induces coupling constraint among agents. Hence, large-scale mixed-integer order handle model optimization, propose distributed algorithm using predictive control (MPC) Benders decomposition method. proposed algorithm, first, master problem obtains all agents, then data, agents obtain optimal MPC method which employs dual approach tackle constraints effectiveness is investigated two case studies.