A Scientific Approach to Spares Prediction

This paper describes a scientific approach to spares prediction, based upon both experience and predictability. It also mentions the development of an interrelated database of logistics information. It further describes some of what we have employed to deal with several subject matters that include Organic versus Commercial Support, a Supportability Module and methods we are using for Supportability Analysis at different levels of data discovery, Level of Repair Analysis/Life Cycle Modeling, International Logistics, associated requirements and some other related issues. It includes some insight into our experience and discoveries that we made when looking into actuals of different customers.