A Probability-reactive Order Processing Method Based on the Load-oriented Order Release (loor) for Maintenance of Capital-intensive Goods

The maintenance of complex capital goods wins more and more in importance. This article will describe a method to raise a condition prognostication of modules and spare parts and the corresponding order probabilities of spare parts during the tear down process. It will give an overview how uncertainty can be represented by the use of probabilities. The consideration of different factors of influence, for example external effects such as the operation period of a product, causal relationships and influence of damaged spare parts, can be represented by the use of Bayesian Networks.