Phase II Monitoring of Nonlinear Profiles

In many practical cases, the quality of a product or process is characterized by multiple measurements constituting a line or curve that is referred to as a profile. In this article, we develop two approaches for monitoring process and product nonlinear profiles. The first approach consists of control chart methods to monitor nonlinear profiles using parametric estimates of regression model. In order to avoid the problems arising from complexity of coefficient estimation of nonlinear profiles, the second approach, which consists of using metrics to measure deviation from a reference curve, is proposed. The performance of the methods is evaluated through a numerical example using average run length criterion. The effect of sample size on the performance of both approaches is also investigated in this article.