Equipment Spare Parts Inventory Optimization Model Under Situational Maintenance Strategy

Abstract

Joint optimization of maintenance and spare parts inventory is an effective way to ensure stable equipment operation and reduce maintenance and guarantee costs. Aiming at the situation of high redundant reserve and inventory cost of spare parts in the current equipment maintenance management, a joint optimization model of condition detection and spare parts inventory is proposed. On the basis of analyzing the demand generation and supply process of equipment spare parts, the concept of delay time is introduced to describe the degradation law of spare parts, and the three core indicators of initial (maximum) inventory, state detection period and inventory replenishment time in spare parts inventory management are studied in combination with the state-dependent detection strategy, and the optimization model with the goal of maintenance guarantee cost is established, and then the simulation method and exhaustive method are used to jointly optimize the decision-making variables such as the state detection cycle, the maximum inventory of spare parts and the ordering cycle of parts. The proposed joint optimization model is verified by numerical experiments. The optimization results show that the proposed joint optimization model of condition detection maintenance and spare parts inventory can reasonably optimize the decision-making variables such as the detection cycle of equipment components, the maximum inventory of spare parts and the ordering cycle, which is of great significance for saving the cost of spare parts guarantee.