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Multivariate Information in Univariate Control Charts

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  • Braun Lorenz

    (Haselnussweg 8, 69469 Weinheim, Germany)

Abstract

Statistical Process Control (SPC) has been established in many industries over the last decades. Particularly, the automotive industry including its suppliers of components is responsible for the spread of SPC supported by different norms. By means of process capability indices the fulfilment of requirements with respect to a product is examined, while control charts are used to monitor a process over time by measuring and analyzing continuously the product variables characterizing product quality. This may lead to high costs, which arise mainly as a result of sampling the data. The objective is to recognize and correct changes in quality as soon as possible. This can be achieved by shorter sampling intervals or by an improved analysis of the data. Conditional control charts are a new way of analyzing sample data by using multivariate information provided in classical control charts, which increase the sensibility of control charts.

Suggested Citation

  • Braun Lorenz, 2007. "Multivariate Information in Univariate Control Charts," Stochastics and Quality Control, De Gruyter, vol. 22(2), pages 211-221, January.
    • Handle: RePEc:bpj:ecqcon:v:22:y:2007:i:2:p:211-221:n:6
    DOI: 10.1515/EQC.2007.211
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