An optimal selective maintenance policy for multi-state series production systems by considering environment impact

Abstract

Series production systems are prevalent in the manufacturing industry. The productivity of these systems is influenced by various factors, including system conditions, on-site environment, maintenance planning, and others. Efforts to develop an effective maintenance plan that considers the on-site environment are crucial for maximizing net revenue over the system’s lifetime, which has practical significance. Against this backdrop, a selective maintenance model is constructed for a multi-state series production system over a finite time horizon. This model describes the operation and maintenance processes at any decision period and analyzes the impact of the on-site environment on system productivity. Subsequently, an optimal maintenance strategy is formulated with the goal of maximizing net revenue throughout the system’s lifetime. To efficiently solve this optimal strategy, a hybrid solution approach is developed by integrating a deterministic method with a heuristic method. Finally, a numerical example involving a real chip mounter system is presented to verify the developed maintenance strategy. This is followed by a comparative experiment to validate the performance of the hybrid solution approach. Additionally, sensitivity analysis is conducted to test the strategy’s robustness. The results from the numerical example, comparative experiment, and sensitivity analysis demonstrate that the developed strategy is effective and robust, and the hybrid approach is efficient.