Integrated Planning of Multi-Product Systems with Multiple Assignable Causes and System Failure

Triple concepts, including statistical process monitoring, inventory control, and maintenance, are integrated to achieve more realistic results for imperfect processes. Previous research has developed integrated models in two contexts: (1) single-product systems with multiple assignable causes, and (2) multi-product systems with a single assignable cause. This study aims to optimize an integrated model for an imperfect production process in a multi-product system, considering the occurrence of multiple assignable causes. The model also accounts for process stoppages due to system failures. Constraints are imposed to prevent inventory deficits for each product and idle time within each production cycle, ensuring that all products are manufactured at least once per cycle. An X-bar control chart is employed to monitor the process and detect out-of-control states. Given the complexity of the model, a particle swarm optimization algorithm is used to determine the decision variables, which include cycle time, sample size, sampling interval, and control limit coefficients. The model’s applicability is demonstrated through an industrial case study. Additionally, comparative analyses are conducted, and a sensitivity analysis is performed to evaluate the effects of key parameters on the optimal results.