Multivariate process and quality monitoring applied to an electrolysis process: Part I. Process supervision with multivariate control charts

✍ Scribed by Conny Wikström; Christer Albano; Lennart Eriksson; Håkan Fridén; Erik Johansson; Åke Nordahl; Stefan Rännar; Maria Sandberg; Nouna Kettaneh-Wold; Svante Wold

• Publisher: Elsevier Science
• Year: 1998
• Tongue: English
• Weight: 436 KB
• Volume: 42
• Category: Article
• ISSN: 0169-7439
• DOI: 10.1016/s0169-7439(98)00014-8

✦ Synopsis

Multivariate statistical process control MSPC is applied to an electrolysis process. The process produces extremely pure copper, and to monitor its quality the levels of eight metal impurities were recorded twice a day. These quality data are anal-Ž . Ž . ysed adopting an 1 'intuitive' univariate approach, and 2 with multivariate techniques. It is demonstrated that the univariate analysis gives confusing results with regards to outlier detection, while the multivariate approach identifies two types of Ž . outliers. Moreover, it is shown how the results from the multivariate principal component analysis PCA method can be Ž . displayed graphically in multivariate control charts. Multivariate Shewhart, cumulative sum CUSUM and exponentially Ž . weighted moving average EWMA control charts are used and compared. Also, an informationally powerful control chart, Ž . the simultaneous scores monitoring and residual tracking SMART chart, is introduced and used.