Robust Phase I monitoring of profile data with application in low-E glass manufacturing processes

Normality is usually assumed in profile monitoring. However, there are many cases in practice where normality does not hold. In such cases, conventional monitoring techniques may not perform well. In this study, we propose a robust strategy for Phase I monitoring of quality profile data in the presence of non-normality. This strategy consists of three components: modeling of profiles, independent component analysis (ICA) to transform multivariate coefficient estimates in profile modeling to independent univariate data, and univariate nonparametric control charts to detect location/scale shifts in the data. Two methods for multiple change point detection are also studied. The properties of the proposed method are examined in a numerical study and it is applied to optical profiles from low-E glass manufacturing in the case study.