A Methodology for Predicting the Variance of Fatigue Life Incorporating the Effects of Manufacturing Processes

Abstract

It is well known that there is a large variance of fatigue life associated with the data of fatigue tests under nominally identical conditions. Understanding and controlling this variance are essential to enhance the safety and competitiveness of designing and manufacturing fatigue critical products. However, no analytical model quantitatively linking input variables with the variance of fatigue life has been found in current literature. To address this issue, a methodology for analytically predicting the variance of fatigue life is proposed. Using this methodology, the variance of fatigue life can be decomposed into individual components. The significance of this decomposition is two-fold. First, it provides a tool for pinpointing key driving factors of the variance of fatigue life, which is essential for the variance reduction of fatigue life. Second, the time consuming and costly fatigue tests to obtain critical variance information for reliability design may be divided into less time consuming tests for obtaining variance information for individual variables contributing to fatigue variance. Based on the variance prediction tool, a methodology for systematically incorporating manufacturing influence into the prediction of variance and average value of fatigue life is proposed. A verification model is built to predict the variance and average value of fatigue life of a structure with a central hole in the high cycle fatigue regime. The predicted fatigue life matches the actual average fatigue life well. Statistical analysis shows that the predicted variances of the fatigue life are equal to those estimated from actual fatigue life.