On the Performance of Linear Profile Methodologies under Runs Rules Schemes

There are many practical situations where product quality is function of two or more related quality characteristics that may establish a linear relationship in the form of a linear profile. In this study, we have investigated different methodologies based on simple and general linear profile datasets for paired observations using efficient runs rules schemes. We have covered different methodologies such as T-square, coding method approach, global F-test under simple, and multiple linear models. We have performed comparisons among their performance using power under different runs rules schemes. The comparisons revealed that different methodologies for simple and multiple profile charts with a variety of runs rules schemes have attractive abilities to detect shifts in different parameters including intercept, slope, and process variance under special process scenarios. An application example is also provided in support of the study.