Cost optimal preventive maintenance and replacement scheduling

In this paper, we present a method for predicting a cost-optimal preventive maintenance policy for a repairable system with an increasing Rate of Occurrence Of Failure (ROCOF). We segment the maintenance planning horizon into n discrete and equally-sized periods. For each period, we predict which of three possible actions, (maintain the system, replace the system, or do nothing to the system) should be taken, such that the total net present worth of all future costs is minimized. Our model expands upon previous work by utilizing the concept that maintenance reduces the "effective age'' of the system and hence the system ROCOF. We develop the model and evaluate three solution procedures, namely, a random search, a genetic algorithm, and a branch-and-bound approach. The entire approach is illustrated through the use of a numerical example.