The development and application of the model outlined in this paper resulted in a tool that was able to account for the many complexities involved in sparing decisions. It was anticipated by the power company involved, that using the model to evaluate spares on a pooling basis rather than on the basis of separate individual station evaluation, would yield approximately $10,000,000 in costs savings during the first three years. Based on the results of the subject optimization project, a generalized power plant sparing application was developed. This application, PS-PLUS~(TM) was developed by Clockwork with SPAR~(TM) at its core. PS-PLUS is data driven and can be configured to a set of specific requirements to meet individual client requirements. An enterprise version of the application, PS-PLUS(E), is capable of addressing also spares and other logistics resource pooling issues with a multi-plant perspective. PS-PLUS's predictions are considered highly accurate because of its ability to address such critical factors as: 1. Time-dependent phenomena: aging, incipient to catastrophic failure development, and deadlines to respond to an event 2. The dynamic behavior of the system: dynamic reconfiguration, induced failures 3. The effect of maintenance and overhaul actions on equipment's ability to perform its function relative to the demand placed on it 4. The availability of limited resources such as repair and maintenance teams, specialized equipment and spare parts.
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