Raytheon assessment of PRISM® as a field failure prediction tool

For any company interested in predicting field reliability performance, finding a prediction technique that provides a high degree of fidelity to observed field data is essential. With the discontinuance of military handbook Mil-Hdbk-217, reliability prediction of electronic equipment, and the limited environmental applications of Telcordia SR-332, reliability prediction for electronic equipment, this paper evaluates the reliability analysis center´s (RAC) PRISM® software tool as a potential improved methodology in predicting the field reliability of military systems. This evaluation compares the PRISM® predicted failure rate to the actual observed field failure rate for three military electronics units. While initial results showed the predicted failure rate to be approximately one-half of the observed field failure rate, the ratio of predicted failure rate to observed field failure rate was consistent across three independent systems. Furthermore, the PRISM® methodology has features such as process grade factors and field failure data incorporation through Bayesian analysis which show promise in allowing a more accurate field reliability prediction to be generated. As a point of comparison, the initial failure rate prediction by Raytheon is opposite to an earlier assessment performed by TRW automotive where field data was not factored in through the use of PRISM´s® Bayesian analysis option (M.G. Priore, et al., 2002). TRW automotive found a predicted failure rate that was twice the observed field failure rate. This paper discusses Raytheon´s assessment of the PRISM® software tool including the reason for choosing PRISM®, application of the PRISM® prediction methodology to three military electronic units, and analysis of the prediction results. This paper also discusses future plans for refinements in the use of PRISM´s® features to produce a more accurate reliability prediction of field performance.