Optimal condition-based maintenance decisions for systems with dependent stochastic degradation of components

• Published in: Reliability engineering & system safety Vol. 121; pp. 276 - 288
• Main Authors: Hong, H.P., Zhou, W., Zhang, S., Ye, W.
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01-01-2014; Elsevier
• Subjects: Applied sciences; Condition-based maintenance; Copula; Decision theory. Utility theory; Decisions; Degradation; Dependency; Deterioration; Distribution theory; Dominance; Exact sciences and technology; Flows in networks. Combinatorial problems; Maintenance; Mathematics; Operational research and scientific management; Operational research. Management science; Optimization; Optimum maintenance; Probabilistic analysis; Probability and statistics; Sciences and techniques of general use; Statistics; Stochastic degradation; Stochasticity; Optimum maintenance; Copula; Dependency; Stochastic degradation; Condition-based maintenance; Stochastic model; Costs; Replacement problem; Partial ordering; Combinatorial optimization; Stochastic system; Stochastic dominance; Optimal decision; Uncertain system; Dependence; Random variable; Monitoring; Probabilistic approach; Dependability; Attitude; Decision making; Maintenance; Risk analysis; Fracture criterion; Preventive maintenance; Operating conditions; Deterioration; Properties of materials; Copula theory
• ISSN: 0951-8320; 1879-0836
• DOI: 10.1016/j.ress.2013.09.004

Components in engineered systems are subjected to stochastic deterioration due to the operating environmental conditions, and the uncertainty in material properties. The components need to be inspected and possibly replaced based on preventive or failure replacement criteria to provide the intended and safe operation of the system. In the present study, we investigate the influence of dependent stochastic degradation of multiple components on the optimal maintenance decisions. We use copula to model the dependent stochastic degradation of components, and formulate the optimal decision problem based on the minimum expected cost rule and the stochastic dominance rules. The latter is used to cope with decision maker's risk attitude. We illustrate the developed probabilistic analysis approach and the influence of the dependency of the stochastic degradation on the preferred decisions through numerical examples.