Replacement and inventory control for a multi-customer product service system with decreasing replacement costs

Liu, Xinbao; Yang, Tianji; Pei, Jun; Liao, Haitao; Pohl, Edward A.

doi:10.1016/j.ejor.2018.08.029

Cited by 34 publications

(12 citation statements)

References 40 publications

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“…The module defines the maintenance activity time by minimizing the long-term maintenance cost and the best time to order spare parts by minimizing the longterm inventory cost. Liu et al (X. Liu, Yang, Pei, Liao, & Pohl, 2019) developed a heuristic based on a Markov decision process to solve the problem of maintenance replacements and spare parts ordering in the case of single manufacturing machine. The Markov decision process integrated health information of the system component when this information is directly obtained from the degradation model.…”

Section: Logistics Jointly With Maintenancementioning

confidence: 99%

Review of Post-Prognostics Decision-Making in Prognostics and Health Management

Bougacha

Varnier

Zerhouni

2021

IJPHM

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Mainly, the prognostics and health management (PHM) process is based on three processes: the data acquisition and health assessment process in which sensors signals are acquired and processed, the diagnostic and prognostic process in which the source of failure is detected and the remaining useful life (RUL) is predicted and finally the decision- making process that refers to the term management in prognostics and health management. This paper reviews in the literature about the different aspects of decision-making in the context of PHM. The selected papers are subject to con- tent assessment and grouped according to the decision type. Additionally, this paper presents a synthesis of the previous works that helps identify new trends and deficiencies in the decision-making process. The synthesis can guide efforts for future work.

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Section: Logistics Jointly With Maintenancementioning

confidence: 99%

Review of Post-Prognostics Decision-Making in Prognostics and Health Management

Bougacha

Varnier

Zerhouni

2021

IJPHM

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“…Traditional system reliability optimization usually focuses on one aspect of maintenance, inventory management or system design. Moreover, spares inventory is generally restricted to the one‐for‐one spares replenishment 4,26,38,46 . Therefore, the spares replenishment for traditional optimization policies is supposed to be a one‐for‐one ordering policy.…”

Section: Numerical Examplesmentioning

confidence: 99%

“…Product‐Service System (PSS) focusing on meeting customer demand have emerged and gradually attracted the extensive concern of scholars 1,2 . Use‐oriented PSS only provides services to customers, while the ownership of products still belongs to the service suppliers or manufacturers, such as public infrastructures, rental services, electric vehicle charging stations, bike‐sharing systems, and so forth 3,4 …”

Section: Introductionmentioning

confidence: 99%

“…Wang and Djurdjanovic 28 proposed an integrated decision‐making policy of preventive maintenance and maintenance resources to optimize the expected cost and system reliability performance. Liu et al 4 formulated a synthetical model of replacement maintenance and inventory management for a multi‐customer PSS. They take into account a single failure mode and decreasing replacement costs.…”

Section: Introductionmentioning

confidence: 99%

“…1,2 Use-oriented PSS only provides services to customers, while the ownership of products still belongs to the service suppliers or manufacturers, such as public infrastructures, rental services, electric vehicle charging stations, bike-sharing systems, and so forth. 3,4 Such complex industrial systems are generally subject to multiple failure modes, 5 which are closely related to the composition of the system. 6 Elaborate maintenance planning for use-oriented PSS is crucial to timely fulfill the customer demand and reduce the operation cost.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Joint optimization of maintenance and spares ordering policy for a use‐oriented product‐service system with multiple failure modes

Zhang

Zhao

Song

et al. 2021

Appl Stoch Models Bus & Ind

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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.

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