Joint optimization of condition-based production and maintenance with mutual production-deterioration dependencies

Hanxiao Zhang, Zhe Wang*, Xingchen Liu, Olivier Gaudoin, Min Xie

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

4 Citations (Scopus)

Abstract

Production control and maintenance scheduling are the two major cost-effective methodologies in the manufacturing systems. The existing literature considers these processes in isolation or with unidirectional dependencies. To fill this gap, we propose an integrated control model of maintenance and production process considering the mutual influence between production and deterioration in a single-machine system. By leveraging condition monitoring data, we enhance decision-making effectiveness and develop a comprehensive framework based on an infinite-horizon Markov decision process. We establish and prove the monotonic structural properties of total profit and maintenance actions relative to machine state, and develop an improved value iteration algorithm to reduce the computational space. Numerical experiments demonstrate the performance of our model in maximizing profits compared to traditional condition-based maintenance and condition-based production approaches. Sensitivity analysis further highlights key parameters influencing optimal policies, providing valuable insights for practical applications. © 2024 Elsevier Ltd.
Original languageEnglish
Article number110679
JournalReliability Engineering and System Safety
Volume256
Online published30 Nov 2024
DOIs
Publication statusPublished - Apr 2025

Funding

This research is supported by the National Natural Science Foundation of China (grant number 72401024, 72371215). This work is partly supported by Research Grant Council of Hong Kong (11201023, 11200621). It is also funded by Hong Kong Innovation and Technology Commission (InnoHK Project CIMDA) and the International Science and Technology Cooperation Program of Guangdong Province (Project #2022A0505050047).

Research Keywords

  • Condition monitoring
  • Condition-based maintenance
  • Condition-based production
  • Reliability

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