Economic Design of Integrated Production Planning Model Based on Adaptive Synthetic EWMA Control Chart and Maintenance Policies

Control charts and maintenance strategies are essential tools in production management. However, despite their inherent connection, these tools are often studied and applied independently. To better reflect real-world scenarios, this paper focuses on the economic design of an integrated production planning model based on a synthetic adaptive Exponentially Weighted Moving Average (EWMA) control chart. To mitigate machine failure rates, two types of maintenance strategies are incorporated: reactive maintenance (RM) and preventive maintenance (PM). The model uses the particle swarm optimization (PSO) metaheuristic algorithm to minimize the total production cycle cost while adhering to statistical quality constraints. A comparative analysis is conducted to evaluate the impact of variable sampling intervals in control charts on overall costs. Sensitivity analysis is performed to examine how model parameters influence optimization policies. Finally, the results are compared with previous studies to demonstrate the effectiveness of the proposed method.