Profile Monitoring of Residual Control Charts under Gamma Additive Models

One of the most powerful tools in quality control is the statistical control chart. In some process control applications, the quality of a product or process can be characterized by a relationship between two or more variables, which is typically referred to as a profile. There are many techniques in literature for monitoring profiles. Generalized additive models (GMAs) have been used frequently in many different applications for modeling non-linear effects in regression models with non-Gaussian response Hastie and Tibshirani (1987). The scheme is based on the deviance residuals, and Pearson residuals for detecting any disturbance in the control variables. This paper investigates the performance of exponentially weighted moving average (EWMA) control charts to monitor the response variability for gamma additive regression models. The simulation study shows that using deviance residuals under log link function seems more suitable than Pearson residuals.