Online Univariate Outlier Detection in Final Test: A Robust Rolling Horizon Approach

We present an online outlier detection method that is applicable to Final Test. Test limits are constructed based on previous measurements and robust statistics are used to ensure a stable start to the method. We analyze our method using real-world data. Furthermore, we identified some cases which can result in performance degradation, but most experiments show that our method is robust to outliers and able to detect them in an online setting.