Replacement and imperfect repair of deteriorating system: Study of a CBM policy and impact of repair efficiency

• Published in: Reliability engineering & system safety Vol. 215; p. 107905
• Main Authors: Mosayebi Omshi, E., Grall, A.
• Format: Journal Article
• Language: English
• Published: Barking Elsevier Ltd 01.11.2021; Elsevier BV; Elsevier
• Subjects: Applications; Automatic; Computer Science; Condition-based maintenance; Efficiency; Engineering Sciences; Imperfect maintenance; Improvement factor model; Inspection; Inverse Gaussian process; Maintenance costs; Maintenance efficiency; Mathematics; Optimization; Parameter sensitivity; Predictive maintenance; Probability; Probability distribution functions; Reliability engineering; Repair; Semi-Regenerative Process; Sensitivity analysis; Statistics; Systems and Control; Maintenance efficiency; Condition-based maintenance; Imperfect maintenance; Inverse Gaussian process; Improvement factor model; Semi-Regenerative Process; Optimization
• ISSN: 0951-8320; 1879-0836
• DOI: 10.1016/j.ress.2021.107905

This paper studies a condition-based predictive maintenance policy in the presence of imperfect repairs for deteriorating systems. The effect of imperfect repairs is assumed to be random in the sense that a maintenance action reduces the systems degradation level by a random proportion. The associated distribution allows characterizing the repair efficiency. As an example, the beta distribution is considered. It allows defining a wide range of repair efficiencies. A maintenance policy with an aperiodic and predictive inspection planning is considered and a new decision criterion is introduced to evaluate the extent to which a repair would be beneficial. The aim is to find a proper balance between repair and replacement for preventive action which leads to optimal maintenance cost. With this consideration, the cost model is developed from regenerative and semi-regenerative properties. The expected cost is evaluated and the optimal policy is reached as a function of repair efficiency. Finally, a numerical study is drawn up to demonstrate the implementation and highlight the potential benefits of the proposed methods. A sensitivity analysis on critical parameters is also performed. •A deteriorating system subject to imperfect repair is considered.•A random improvement factor describes the effect of imperfect repair.•A condition-based predictive maintenance with aperiodic planning is proposed.•A new decision variable adjusts the balance between repairs and replacements.•The closed form of long run maintenance cost is obtained, and optimized numerically.