上海交通大学学报

上海交通大学学报 >

2023 , Vol. 57 >Issue 3: 285 - 296

DOI: https://doi.org/10.16183/j.cnki.jsjtu.2022.030

机械与动力工程

k-out-of-n系统机会维护与库存控制多层级优化策略

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  • 上海交通大学 机械与动力工程学院,上海 200240
曹 蕾(1999-),硕士生,从事制造系统的可靠性建模与维护决策研究.

收稿日期: 2022-02-14

  录用日期: 2022-05-24

  网络出版日期: 2022-08-23

基金资助

国家自然科学基金(51875359);上海市“科技创新行动计划”自然科学基金(20ZR1428600);上海商用飞机系统工程科创中心联合研究基金(FASE-2021-M7);教育部-中国移动联合基金建设项目(MCM20180703);上海交通大学深蓝计划基金(SL2021MS008);中船-交大海洋装备前瞻创新基金(22B010432)

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Multi-Level Optimization Policy of Opportunistic Maintenance and Inventory Control of k-out-of-n System

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  • School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

Received date: 2022-02-14

  Accepted date: 2022-05-24

  Online published: 2022-08-23

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摘要

面向服务型制造的复杂系统维护外包决策需求,针对k-out-of-n:G系统中冗余设备干涉、停机惩罚高昂和备件库存限制的挑战,提出了机会维护与库存控制多层级优化策略(OMICP).在设备层,构建各独立设备衰退模型,通过最小化维护成本率,贯序输出各设备预防维护周期;在系统层,以各设备维护时点为契机,综合考虑库存水平、关停数量和冗余干涉,制定动态组合机会维护策略;在联合层,基于机会维护决策反馈,建模分析备件订购利润结余,制定实时更新库存控制策略.通过服务商承担外包维护下的多层级交互决策,整合复杂系统维护与库存控制耦合关系,优化维护外包服务总成本.算例分析证明,所提OMICP具有复杂决策可行性和成本优化有效性.

关键词： 维护外包; k-out-of-n:G系统; 机会维护; 库存控制; 多层级优化

本文引用格式

曹蕾, 安向昕, 夏唐斌, 郑美妹, 奚立峰 . k-out-of-n系统机会维护与库存控制多层级优化策略[J]. 上海交通大学学报, 2023 , 57(3) : 285 -296 . DOI: 10.16183/j.cnki.jsjtu.2022.030

Abstract

For the maintenance outsourcing requirements of complex systems in service-oriented manufacturing, a multi-level optimization policy of opportunistic maintenance and inventory control (OMICP) is proposed by considering the challenges of redundant machine interference, high shutdown penalty, and spare parts inventory limit of k-out-of-n: G system. At the machine layer, the degeneration model of each machine is built. Then, preventive maintenance cycles of each machine are outputted in sequence by minimizing the maintenance cost rate. At the system level, these maintenance time points are taken as opportunities. In addition, a dynamic combination opportunistic maintenance policy is established by comprehensively considering inventory level, shutdown quantity, and redundancy interference. At the joint level, based on the opportunistic maintenance decision feedback, the inventory control policy is updated in real time by modeling and analyzing the profit balance of spare parts ordering. Through this multi-level interactive decision-making under outsourcing maintenance, the coupling relationship between complex system maintenance and inventory control is integrated to optimize the total cost of maintenance outsourcing services. The case study has shown that OMICP has the feasibility of complex decision-making and the effectiveness of cost optimization.

Key words： maintenance outsourcing; k-out-of-n: G system; opportunistic maintenance; inventory control; multi-level optimization

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