Nonlinear programming solution for optimum PM schedule of auxiliary components

Auxiliary components in some systems exist only to serve some other primary components. Preventive maintenance (PM) activities are, therefore, done to these auxiliary components for the sake of extending the life of the primary component. Frequent PM care to auxiliary components increase the cost of PM while infrequent PM leads to increasing downtime of the primary component and, subsequently, production losses. The search for the optimal level of PM care requires a nonlinear programming (NLP) solution that can, sometimes, be very complex. This paper suggests that a very useful pattern exists in the NLP model of this optimization problem which can significantly reduce the complexity of model formulation and the arrival to the NLP solution.