Value maximizing maintenance policies under general repair

One class of maintenance optimization problems considers the notion of general repair maintenance policies where systems are repaired or replaced on failure. In each case the optimality is based on minimizing the total maintenance cost of the system. These cost-centric optimizations ignore the value dimension of maintenance and can lead to maintenance strategies that do not maximize system value. This paper applies these ideas to the general repair optimization problem using a semi-Markov decision process, discounted cash flow techniques, and dynamic programming to identify the value-optimal actions for any given time and system condition. The impact of several parameters on maintenance strategy, such as operating cost and revenue, system failure characteristics, repair and replacement costs, and the planning time horizon, is explored. This approach provides a quantitative basis on which to base maintenance strategy decisions that contribute to system value. These decisions are different from those suggested by traditional cost-based approaches. The results show (1) how the optimal action for a given time and condition changes as replacement and repair costs change, and identifies the point at which these costs become too high for profitable system operation; (2) that for shorter planning horizons it is better to repair, since there is no time to reap the benefits of increased operating profit and reliability; (3) how the value-optimal maintenance policy is affected by the systemʹs failure characteristics, and hence whether it is worthwhile to invest in higher reliability; and (4) the impact of the repair level on the optimal maintenance policy.