Effects of Model Accuracy on Residual Control Charts

• Published in: Quality and reliability engineering international 2016-07, Vol.32 (5), p.1785-1794
• Main Authors: Zhou, Min, Goh, T.N.
• Format: Article
• Language: English
• Subjects: Accuracy; average run length; Control charts; Correlation; False alarms; Monitoring; Multistage; multistage process monitoring; multivariate autogressive modeling; Reliability engineering; residual control charts; Statistical process control
• ISSN: 0748-8017; 1099-1638
• DOI: 10.1002/qre.1913

Residual control charts are acknowledged to be effective tools for statistical process control of multistage processes. In these monitoring procedures, the models on the stage‐wise correlation should be first derived before the control charts are implemented. Therefore, the monitoring performance is inevitably affected by the model fitting scheme. Most of the previous works are under the assumption that the derived models represent the process behavior perfectly. Far less is known about the effects of the model inaccuracy on the monitoring performance. To investigate the effects of the underlying models on the monitoring performance, residual control charts based on two different modeling schemes are compared in this paper. The results indicate that the charting performance is correlated with the model fitting schemes. That is, a more accurate model will significantly increase the detection power and decrease the false alarm rate as well. Copyright © 2015 John Wiley & Sons, Ltd.