Optimal replacement policy for multi-state manufacturing system with economic and resource dependence under epistemic uncertainty

Zhaoxiang Chen, Zhen Chen, Di Zhou, Chi Shao and Ershun Pan

International Journal of Production Research, 2023, vol. 61, issue 20, 6772-6790

Abstract: This paper develops an optimal replacement policy V* for a multi-state manufacturing system. The manufacturing system would be repaired imperfectly once its performance cannot meet the production demand, and would be replaced when the production demand is not met for the V*-th time. Due to imprecise state assignments and unpredictable external working conditions, the performance and transition intensity of the multi-state machine cannot be accurately identified and then inevitably lead to epistemic uncertainty. In addition, the economic dependence and resource dependence that prevailed in the manufacturing system should be considered. In this paper, economic dependence is described as the time and cost saved by simultaneously repairing multiple identical machines, and resource dependence is caused by finite capacity buffers. To take these into account, the fuzzy Markov model and fuzzy stochastic flow manufacturing network (FSFMN) are tailored to evaluate the fuzzy reliability of machines and manufacturing systems, respectively. To obtain the optimal replacement policy V*, we derive the expression of the long run fuzzy profit rate under epistemic uncertainty. The replacement policy is demonstrated on the ferrite phase shifting unit manufacturing system, and the results of the subsequent comparative study and sensitivity analysis show that this policy is more effective.

Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2022.2137595 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tprsxx:v:61:y:2023:i:20:p:6772-6790

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20

DOI: 10.1080/00207543.2022.2137595

Access Statistics for this article

International Journal of Production Research is currently edited by Professor A. Dolgui

More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().