Using Bayesian belief networks to predict the reliability of military vehicles

Predicting the reliability of military vehicles has traditionally concentra ted on estimation using failure data gathered during trials or use. However , it is increasingly recognised that predicting reliability earlier in the life cycle, using design and process capability evidence, is one way of imp roving predictions and positively influencing reliability. This article pre sents the use of Bayesian belief networks (BBNs) as a decision support tool to achieve these twin goals. The BBN models presented are built into the T RACS software tool, which is in daily use within DERA Land Systems.