Production System Optimisation with a Multi-Level Process Control Tool Integrated into Maintenance and Quality Strategies under Services and Quality Constraints

Abstract

This study investigated an optimal production, maintenance, and quality forecasting problem, with an improved statistical process chart of a supply chain under service and quality requirements. The product quality control is done using a multi-level statistical process chart with additional surveillance. The tool indicates when the process is respectively in control, on surveillance, and under critical stages. While the process is in a control state, producing conforming items is subjected only to minimal corrective maintenance. But when the operation falls to a surveillance stage it requires imperfect preventive maintenance with duration to reduce the failure rate. And when the operation moved to a critical state, then a perfect maintenance action with significant time is employed to restore the process to (AGAN). The decision variables are the sample size, the control interval, the control charts’ surveillance limits and the critical limits. The multi-ware houses are to satisfy random customer demands during the finite production horizon with service, quality, and production bounds constraints. We use a stochastic mathematical formulation, simulation, and optimization to determine the optimal chart parameters, which minimizes the total expected cost of production. To highlight the interesting aspects of the interactions between production, quality, and maintenance, numerical examples and sensitivity analysis are presented. The work reduces the non-conformal losses and, subsequently, achieved total cost minimization.