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Joint optimization of maintenance and spares ordering policy for a use-oriented product-service system with multiple failure modes
Applied Stochastic Models in Business and Industry ( IF 1.4 ) Pub Date : 2021-06-26 , DOI: 10.1002/asmb.2639
Jing Zhang 1, 2 , Xian Zhao 1 , Yanbo Song 1 , Qingan Qiu 1
Affiliation  

The use-oriented product-service system, such as the bike-sharing system and the electric vehicle charging station, has gained wide application in engineering fields. Use-oriented product-service systems are commonly subject to failures of software and hardware. Failed software can be repaired while failures of hardware require the replacement by spares. An innovative joint optimization model of maintenance and spares ordering policy is proposed for a use-oriented product-service system in this work where different types of spares are considered for hardware failure. System effectiveness is maximized by simultaneously considering the incurred costs, system availability, spares availability and the availability of repair engineers. Then, the related reliability probabilistic indices and costs are derived through the continuous time Markov process. To overcome the computational complexity, a greedy search algorithm is applied to obtain a balanced optimal solution for the number of repair engineers and spares inventory policies of different types of parts. Finally, some numerical instances are given to demonstrate the superiority and effectiveness of the proposed joint optimization model.

中文翻译:

多故障模式下以使用为导向的产品-服务系统的维修备件订购策略联合优化

共享单车、电动汽车充电站等以使用为导向的产品服务体系在工程领域得到广泛应用。以使用为导向的产品服务系统通常会出现软件和硬件故障。出现故障的软件可以修复,而硬件出现故障则需要更换备件。在这项工作中,针对以使用为导向的产品服务系统,提出了一种创新的维护和备件订购策略联合优化模型,其中考虑了不同类型的备件发生硬件故障。通过同时考虑产生的成本、系统可用性、备件可用性和维修工程师的可用性来最大化系统效率。然后,通过连续时间马尔可夫过程推导出相关的可靠性概率指标和成本。为克服计算复杂性,采用贪心搜索算法对不同类型零件的维修工程师数量和备件库存策略获得平衡最优解。最后,给出了一些数值实例来证明所提出的联合优化模型的优越性和有效性。
更新日期:2021-06-26
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