A review and critique of auxiliary information-based process monitoring methods

We review the rapidly growing literature on auxiliary information-based (AIB) process monitoring methods. Under this approach, there is an assumption that variable, which correlated with quality variable of interest, has a known mean, or some other parameter, cannot change over time. demonstrate violations can have serious adverse effects both when stable and been shift. Some shifts in interest become undetectable. also show basic AIB approach special case simple linear regression profile monitoring. The charting techniques require strong assumptions. Based our results, we warn against uncritical use control applications.