| Article ID: | iaor20172566 |
| Volume: | 33 |
| Issue: | 5 |
| Start Page Number: | 1031 |
| End Page Number: | 1043 |
| Publication Date: | Jul 2017 |
| Journal: | Quality and Reliability Engineering International |
| Authors: | Liu Xintian, Wang Minlong, Wang Xiaolan, Wang Yansong |
| Keywords: | production, inspection, testing, statistics: sampling, statistics: distributions |
The study discusses how some challenges from a small sample fatigue test can be analysed statistically and resolved. In terms of data dispersion, fatigue data are initially processed by confidence, and then, the fatigue life curve is replaced by the parabolic reliability approximation. Fatigue data under various reliability levels are obtained. Instead of the traditional single S–N curve, the mean value curve and mean square deviation curve of the S–N curve are computed based on the processed fatigue data. The S–N curve with reliability is deduced by applying quantile theory. The S–N curve is improved by considering the effects of low‐amplitude load strengthening. The benefits of the modification are visible in the comparison of the fatigue life before and after low‐amplitude load strengthening.