APPLICATION OF THE GROSS ERROR ANALYSIS TO DISORDERS IDENTIFICATION IN MANUFACTURING PROCESS—A CASE STUDY

  • Izabela Dagmara Czabak-Górska Faculty of Production and Logistics Engineering, Department of Production and Services Quality Engineering, Opole University of Technology
  • Aneta Kucińska-Landwójtowicz Faculty of Production and Logistics Engineering, Department of Production and Services Quality Engineering, Opole University of Technology
Keywords: stability of the process, Individuals Control Chart (IX), Moving Range Control Chart (MR), elimination of Gross Error, Statistical Process Control (SPC)

Abstract

The article contains a description of the procedures to be followed in the analysis of the stability of the manufacturing processes based on an Individual Control Chart (XI) and a Moving Range (MR) Control Chart. In the following part of the article, we present the three-sigma rule and the confidence intervals for the average, which enable the elimination of random errors caused by, e.g. an improper conducting of a measurement.

Summary of the theoretical considerations is a study case in which survey data from a company, producing car seat frames, are used. The conducted study indicates that the elimination of Gross Error is significant to identify and eliminate the variability of production processes.

References

Aczel, A. D. (2012). Complete Business Statistics. Eight Edition. Wohl Publishing.

Czabak-Górska, I. D., & Lorenc, M. (2014). Analiza stabilności procesu produkcyjnego – studium przypadku. Logistyka, 6, 12075 - 12079.

Greber, T. (2000). Statystyczne sterowanie procesami – doskonalenie jakości z pakietem STATISTICA. Kraków: StatSoft.

Jensen, W. A., Jones–Farmer, L. A., Champ, C. W., & Woodall, W. H. (2006). Efects of Parameter Estimation on Control Chart Properties: A Literature Review. Journal of Quality Technology, 38(4), 349 – 364.

Lehmann, R. (2013). 3σ-Rule for Outlier Detection from the Viewpoint of Geodetic Adjustment. Journal of Surveying Engineering, 139(4), 157–165.

Narasimhan, S., & Jordache, C. (2000). Data Reconciliation and Gross Error Detection: An Intelligent Use of Process Data. Houston: Gulf Professional Publishing.

Oakland, J. (2007). Statistical Process Control. Sixth Edition. Butterworth-Heinemann.

Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. New York: D. Van Nostrand Company.

Thompson, J. R., Koronacki, J., & Nieckuła J. (2005). Techniki zarządzania jakością od Shewharta do metody “Six Sigma” [Quality management techniques from Shewhart to the method of "Six Sigma"]. Warszawa: Akademicka Oficyna Wydawnicza Exit.

Yang, Y., Ten, R., & Jao, L. (1995). A study of gross error detection and data reconciliation in process industries. Computers & Chemical Engineering, 19(1), 217-222.

Published
2015-09-19