Konferensartikel

Control Chart Limits Setting when Data are Auto-Correlated

Darja Noskievičová
VŠB-Technical University of Ostrava, Faculty of Metallurgy and Material Engineering, Department of Quality Management, Czech Republic

Ladda ner artikelhttp://www.ep.liu.se/ecp_article/index.en.aspx?issue=026;article=120

Ingår i: 10th QMOD Conference. Quality Management and Organiqatinal Development. Our Dreams of Excellence; 18-20 June; 2007 in Helsingborg; Sweden

Linköping Electronic Conference Proceedings 26:120, s.

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Publicerad: 2008-02-15

ISBN:

ISSN: 1650-3686 (tryckt), 1650-3740 (online)

Abstract

Correctly set control limits in control charts is one of the main conditions for successful application of statistical process control and for meeting its basic goal; i.e. verifying statistical stability of the analysed process.

Problem of setting control limits in control charts is solved in many publications (from standards to articles and books). Algorithm of setting control limits in these publications does not distinguish between autocorrelated and nonautocorrelated data. It lies in excluding of subgroups that give the “out of control” signal from control limits computation (after revealing the existing assignable causes and realization of the corrective action). This algorithm is not wholly suitable for autocorrelated data.

This paper deals with the idea mentioned above in more detail and the proposal of methodology for setting control charts when data are autocorrelated will be applied to the selected parameter of the blast furnace process.

Nyckelord

Control chart; outliers analysis; setting control limits; time series analysis

Referenser

Box; G.E.P.; Jenkins; G.M.; Reinsel; G.L.; (1994); Time Series Analysis. Forecasting and Control; Prentice Hall; Englewood Cliffs; New Jersey.

Chang; I.; Tiao; G. C.; Chen; C.; (1988); “Estimation of Time Series Parameters in the Presence of Outliers”; Technometrics; 30; 193-204.

Liu; L.M.; (2006); Time series analysis and forecasting. Scientific Computing Associates; Corp.; Villa Park.

Noskievicová; D.; (2006); “The Analysis of Selected Blast Furnace Process Indicators using Box-Jenkins Methodology”; Report on the Subproject Solving in the Frame of the Research Project CEZ MSM 6198910019 Reduction of CO2 Production - DECOx Processes; VŠB-TUO; Ostrava. (In Czech)

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