Maintenance contract assessment for aging systems

This paper considers an aging system, where the system failure rate is known to be an increasing function. After any failure, maintenance is performed by an external repair team. Repair rate and cost of repair are determined by a corresponding maintenance contract with a repair team. There are many different maintenance contracts suggested by the service market to the system owner. In order to choose the best maintenance contract, a total expected cost during a specified time horizon should be evaluated for an aging system. In this paper, a method is suggested based on a piecewise constant approximation for the increasing failure rate function. Two different approximations are used. For both types of approximations, the general approach for building the Markov reward model is suggested in order to assess lower and upper bounds of the total expected cost. Failure and repair rates define the transition matrix of the corresponding Markov process. Operation cost, repair cost and penalty cost for system failures are taken into account by the corresponding reward matrix definition. A numerical example is presented in order to illustrate the approach.