Fatigue Life Variance Prediction Incorporating Residual Stress Scatter Induced by Super-Finishing Grinding Process

It is well known that there is a lager deviation in the fatigue life of machined components even under nominally identical loading conditions. Understanding and controlling fatigue life variance are essential to enhance reliability. However, few research focus on the impact of machining processes on the fatigue life variance of machined components. In this study, surface residual stress distributions of bearing rings randomly selected from a production line by super-finishing grinding, are measured by X-ray diffraction method in cutting and feed direction, and its scatter is analyzed by statistical tools. Based on the variance prediction theories, build a simplified fatigue life variance prediction model incorporating the resultant residual stresses scatter induced by machining process. Based on the Basquin equation, the model is validated by experimental data published in literature. The predicted fatigue life agrees well with the experimental average fatigue life. Statistical analysis shows that the predicted variances of fatigue life are equal to those estimated from experimental fatigue life.