Field Fatigue Failure Prediction Using Multiple Regression with Random Variables

The most common used warranty prediction method at component level (non-repairable system) is called Weibull analysis. In Weibull analysis, failure time is assumed to follow a certain distribution such as Weibull, and time is the only predictor in the model for predicting percentage of failures. However, other variables such as design variables, manufacturing parameters, and field use condition also affect warranty. These variables should be considered in the prediction. In this paper, a multiple regression approach is proposed to predict warranty failures of a solenoid switch by considering multiple factors that affect the warranty. A single failure mode caused by fatigue is studied. The failure is caused by out of GD&T (Geometric Dimension and Tolerance) specs. These GD&T variables together with component operation time are used as predictors in the model. The final model is established by integrating physics of failures with statistical analysis results. Since the GD&T variables are random variables, instead of simply using their mean values, their randomness is also considered in the prediction.