A review and critique of auxiliary information-based process monitoring methods
Publication date
2022-08-08
Document type
Forschungsartikel
Author
Organisational unit
Scopus ID
Publisher
Taylor & Francis
Series or journal
Quality Technology & Quantitative Management
ISSN
Periodical volume
20
Periodical issue
1
First page
1
Last page
20
Part of the university bibliography
✅
Language
English
Keyword
Cause-selecting chart
Control chart
Profile monitoring
Regression-adjusted charts
Statistical process monitoring
Abstract
We review the rapidly growing literature on auxiliary information-based (AIB) process monitoring methods. Under this approach, there is an assumption that the auxiliary variable, which is correlated with the quality variable of interest, has a known mean, or some other parameter, which cannot change over time. We demonstrate that violations of this assumption can have serious adverse effects both when the process is stable and when there has been a process shift. Some process shifts in the quality variable of interest can become undetectable. We also show that the basic AIB approach is a special case of simple linear regression profile monitoring. The AIB charting techniques require strong assumptions. Based on our results, we warn against the uncritical use of the AIB approach in quality control applications.
Version
Published version
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