Faculty Publications


A Markov decision process model case for optimal maintenance of serially dependent power system components

Document Type



Continuous-time Markov decision model, Dependent components, Electrical power system maintenance

Journal/Book/Conference Title

Journal of Quality in Maintenance Engineering





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Purpose-Using a case study for electrical power equipment, the purpose of this paper is to investigate the importance of dependence between series-connected system components in maintenance decisions. Design/methodology/approach-A continuous-time Markov decision model is formulated to find a minimum cost maintenance policy for a circuit breaker as an independent component while considering a downstream transformer as a dependent component. Maintenance of the dependent component is included implicitly in terms of the costs associated with certain state-action pairs. For policy and cost comparisons, a separate model is also formulated that considers only the circuit breaker as the independent component. After uniformizing the continuous-time models to discrete time, standard methods are used to solve for the average-cost-optimal policies of each model. Findings-The optimal maintenance policy and its cost differ significantly depending on whether or not the dependent component is considered. Research limitations/implications-Data used are from manufacturer databases; additional model validation could be conducted if applied to an electric utility asset fleet within their generation, transmission, and/or distribution system. This model and methodology are already being applied in other contexts such as industrial machinery and equipment, jet engines, amusement park rides, etc. Practical implications-The outcome of this model can be utilized by asset and operations managers to make maintenance decisions based on prediction rather than more traditional time-or condition-based maintenance methodologies. This model is being developed for use as a module in a larger maintenance information system, specifically linking condition monitor data from the field to a predictive maintenance model. Similar methods are being applied to other applications outside the electrical equipment case detailed herein. Originality/value-This model provides a structured approach for managers to decide how to best allocate their resources across a network of inter-connected equipment. Work in this area has not fully considered the importance of dependency on systems maintenance, particularly in applications with highly variable repair and replacement costs.


Department of Management

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DOI of published version