International Journal of Systems Science · 2014 · 10 citations · 29 references
EngineeringIndustrial EngineeringSystems EngineeringMaintenance EngineeringProbability TheoryStochastic ProcessesMaintenance OptimizationMarkov ModelingMarkov ProcessesMulti-state ModelsReliability ModelingReplacement DecisionsContinuous-time Markov ProcessesMultistate Reliability ModelsNon-homogeneous Markov ModelsOptimal Replacement PolicyStochastic Process AnalysisSystem Performance ModelingSystem ReliabilitySystem Reliability Modeling
This paper proposes the generalised random and age replacement policies for a multi-state system composed of multi-state elements. The degradation of the multi-state element is assumed to follow the non-homogeneous continuous time Markov process which is a continuous time and discrete state process. A recursive approach is presented to efficiently compute the time-dependent state probability distribution of the multi-state element. The state and performance distribution of the entire multi-state system is evaluated via the combination of the stochastic process and the Lz-transform method. The concept of customer-centred reliability measure is developed based on the system performance and the customer demand. We develop the random and age replacement policies for an aging multi-state system subject to imperfect maintenance in a failure (or unacceptable) state. For each policy, the optimum replacement schedule which minimises the mean cost rate is derived analytically and discussed numerically.
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Optimum Preventive Maintenance Policies
Richard Barlow, Larry C. Hunter · Operations Research · 1960 · 1.4K citations
Engineering, Industrial Engineering, Continuous Improvement +13
Hoang Pham, Hongzhou Wang · European Journal of Operational Research · 1996 · 629 citations
Mark Brown, Frank Proschan · Journal of Applied Probability · 1983 · 552 citations