umu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Multivariate process and quality monitoring applied to anelectrolysis process: Part I. Process supervision with multivariate control charts
Umeå University, Faculty of Social Sciences, Centre for Demographic and Ageing Research (CEDAR).ORCID iD: 0000-0001-9188-5518
1998 (English)In: Chemometrics and Intelligent Laboratory Systems, Vol. 42, p. 221-231Article in journal (Refereed) Published
Abstract [en]

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 analysed 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 outliers. Moreover, it is shown how the results from the multivariate principal component analysis (PCA) method can be displayed graphically in multivariate control charts. Multivariate Shewhart, cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts are used and compared. Also, an informationally powerful control chart, the simultaneous scores monitoring and residual tracking (SMART) chart, is introduced and used.

Place, publisher, year, edition, pages
1998. Vol. 42, p. 221-231
Keywords [en]
Multivariate statistical process control; PLS; PCA; EWMA; Control charts
National Category
Industrial Biotechnology
Identifiers
URN: urn:nbn:se:umu:diva-142531DOI: 10.1016/S0169-7439(98)00014-8OAI: oai:DiVA.org:umu-142531DiVA, id: diva2:1161988
Available from: 2017-12-01 Created: 2017-12-01 Last updated: 2018-06-09

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full text

Authority records BETA

Sandberg Hiltunen, Maria

Search in DiVA

By author/editor
Sandberg Hiltunen, Maria
By organisation
Centre for Demographic and Ageing Research (CEDAR)
Industrial Biotechnology

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 11 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf