Stochastic Programming Model and Benders decomposition approach for Integrated Production and Maintenance Planning in Multi-Factory Production

Proper performance of production/supply centers in a multi-factory production (MFP) network requires undisrupted equipment. The design and implementation of a maintenance system is important for two reasons - firstly, extending the life of the equipment, and second, reducing the MFP network disruption and associated costs. The greater productivity of an MFP system is achieved by integrating maintenance and production decisions. In this study, considering a scenario-based uncertainty in the demand and failure rate, a robust scenario-based stochastic programming (RSSP) model has been presented. proposed RSSP model integrates the strategic and operational decisions of production and the maintenance, and takes into account the MFP disruption costs. We suggest three preventive maintenance strategies such as maintenance outsourcing, deployment of backup equipment, as well as periodic preventive maintenance for the MFP network. The objective function of the proposed model is to maximize the total profit, subject to, constraints such as limited capacity of production, storage, access to service centers, and budget should be satisfied. The proposed RSSP model is formulated as mixed linear program which can be solved in small-scale instances by the CPLEX Solver. Furthermore, Benders decomposition solution method is proposed for large-scale instances. Finally, a numerical study of CNG stations, as an MFP network, is conduct to demonstrate the applicability of the proposed model and analyze the results.