RESEARCH PAPER
Optimal predictive maintenance for a nonstationary gamma process
1
Harbin Engineering University, China
2
Hefei University of Technology, China, China
A – Conceptualization; B – Methodology; C – Software; D – Validation; E – Formal analysis; F – Investigation; G – Resources; H – Data curation; I – Writing – original draft; J – Writing – review & editing; K – Visualization; L – Supervision; M – Project administration; N – Funding acquisition
Submission date: 2025-01-26
Final revision date: 2025-02-26
Acceptance date: 2025-03-30
Online publication date: 2025-04-07
Publication date: 2025-04-07
Eksploatacja i Niezawodność – Maintenance and Reliability 2025;27(4):203543
HIGHLIGHTS
- A heuristic predicitive maintenance policy for a nonstationary gamma process.
- A preventive repair model considering the change of degradation rates.
- Decisions based on information of age, degradation, and the number of performed repairs.
- Formulation of the problem in the semi-Markov decision process framework
KEYWORDS
TOPICS
ABSTRACT
Nonstationary gamma processes have extensive applications in depicting the degradation of many practical systems. This paper proposes a predictive maintenance policy that involves various types of maintenance actions for a nonstationary gamma process. Periodic inspections fully reveal the degradation levels of the system. The information on age, degradation, and the number of conducted preventive maintenance actions is synthesized for decision-making, which distinguishes our model from most existing models considering only degradation states. The objective is to find the maximum number of repairs and the best thresholds for preventive maintenance by minimizing the expected average cost in an infinite time horizon. The maintenance problem is addressed as a semi-Markov decision problem. An optimization algorithm is developed to find the optimal values of the decision variables. The effectiveness of the proposed method is verified by a coating system.
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