An heuristic approach for finite time maintenance policy

While treating finite time models, the computational time required to obtain the optimal solution increases as the planning horizon increases. A similar effect is also seen for variations in some of the parameters. If preventive maintenance (PM) is imperfect, the expected time of a next failure of a repaired/maintained system is less than that of a new system. The optimum PM intervals in such situations are not constant and the mathematical model to determine the optimum PM/replacement points is more complex than that associated with a perfect PM. In such situations, it is advisable to use a heuristic algorithm to obtain solutions of good quality with less computational efforts. This paper considers a simple and easy to understand heuristic algorithm which gives optimal and near optimal solutions most of the times with less CPU time. The solutions are compared for a wide variety of parameters with the solutions of branching algorithms through numerical examples.