RESEARCH PAPER
Optimal maintenance and pricing strategy for a periodic review production system with fixed maintenance costs and limited maintenance capacity
1
Zhejiang University of Technology, China
2
Shanghai Dianji University, China
These authors had equal contribution to this work
Submission date: 2024-07-11
Final revision date: 2024-09-22
Acceptance date: 2024-11-11
Online publication date: 2024-11-14
Publication date: 2024-11-14
Eksploatacja i Niezawodność – Maintenance and Reliability 2025;27(2):195801
HIGHLIGHTS
- Integrate limited maintenance capacity and fixed maintenance costs into a unified strategy.
- Build a dynamic programming model and utilize strong CK-concavity to develop the strategy.
- Partially characterize the optimal maintenance strategy by two thresholds.
KEYWORDS
strong CK-concavityperiodic review production systemfixed maintenance costslimited maintenance capacityoptimal maintenance and pricing strategy
TOPICS
ABSTRACT
In recent times, the escalating complexity of advanced production systems has led to increased exposure to various uncertainties, which impact systems' reliability. To maintain the reliability of systems, reduce maintenance costs and increase revenues, we establish an effective joint optimal maintenance and pricing strategy for a periodic review production system, which is of practical importance. Compared with the existing literature, we make a contribution to considering limited maintenance capacity and fixed maintenance costs simultaneously, and developing joint optimal maintenance and pricing strategies. We initially construct a dynamic programming model for this problem, and prove the objective function is strong CK-concave. We then show that the optimal maintenance strategy is partially characterized by two thresholds, and the optimal pricing strategy depends on the optimal number of operational machines after repairs. Numerical results show that the optimal maintenance and pricing strategy is quite robust, and is not much affected by various parameters.
FUNDING
This work is supported in part by "Pioneer" and "Leading Goose" R&D Program of Zhejiang (2024C01208), NSFC (Grant 72271221, 71720107003), and Shanghai Educational Science Research Project (No.C2022406).
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| eISSN: | 2956-3860 |
| ISSN: | 1507-2711 |
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