Abstract: We propose a statistical process control (SPC) scheme that can be implemented in industrial 
practice, where the quality of a process can be characterized by a general linear profile. We start by 
reviewing the general linear profile model and the existing monitoring methods. Based on that, a novel 
multivariate exponentially weighted moving average (MEWMA) monitoring scheme is proposed for such 
a profile. Two other enhancement features are introduced to further improve the performance of the 
proposed scheme, which include the variable sampling interval and the parametric diagnostic approach. 
Throughout this paper, a deep reactive ion etching (DRIE) example from semiconductor manufacturing, 
which has a profile that fits a quadratic polynomial regression model well, is used to illustrate the 
implementation of the proposed approach.