Dynamic programming application to optimize spare parts inventory

The cost of acquiring and storing spare parts generally lies between 5% and 7% of total electricity generation cost. Considering the amount of funds invested in the spare parts inventory, most generation divisions in power industry try to optimize their investment. An application of an optimal resource allocation method with the use of Dynamic Programming to optimize spare parts inventory is shown. The method considers power plant availability as the objective function and inventory budget as the constraint. Thus, for a given budget, Dynamic Programming configures a spare parts inventory which attains the highest availability level. This approach has been implemented as a decision support system which assists inventory managers and engineers to optimize their inventory policy. The results of two case studies, for a base load unit and a peaking unit, illustrate possible applications and outcomes of the decision support system.