Construction of Bivariate F-Control Chart with Application

Authors:  Taha Hussein Ali1 & Alan Ghafur Rahim2 & Dlshad Mahmood Saleh3
1&2Department of Statistics, College of Administration and Economics, Salahaddin University, Erbil, Iraq
3Paitaxt Private Technical Institute, tvsvevnnad idaahalaSy, Erbil, Iraq

Abstract:  In this paper, construction of bivariate F-Control Chart through three stages (test of bivariate normal distribution, construction of bivariate S-Chart and use the relationship between the distribution of Tand F) corresponding for Shewart T2– Chart for quality control on measurable properties has been suggested. F-Chart is characterized by minimizing general and total variance for the least possible to obtain the best quality control limits. And the installation of the control chart on the data representing the quality properties of yield stress and elongation for steel product from factory (Erbil Steel) depending on the program language MATLAB has been designed and statistical program SPSS has been employed. The paper found the efficiency of the proposed chart and the possibility of using it to control future data (phase-2).

Keywords: Bivariate Average Chart, Quality Control Chart, Hotelling’s T2

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doi: 10.23918/eajse.v4i2p116


References

Deming, W. E. (1982). Out of the crisis. Cambridge, MA: MIT Press.

Douglas, C. (2009). Introduction statistical quality control. Sixth Edition. Arizona State University, John Wiley & Sons.

Guoxi, Z., & Shing, I. (2008). Multivariate EWMA control charts using individual observations for process mean and variance monitoring and diagnosis. International Journal of Production Research, 46(24), 6855-6881.

Kovach, J. (2007). Designing Effective Six Sigma Experiments for Service Process Improvement Projects. International Journal of Six Sigma and Competitive Advantage, 3(1), 72–90.

Kuvattana, S., Sukparungsee, S., Busababodhin, P., & Areepong, Y. (2016). Bivariate copulas on the exponentially weighted moving average control chart. Songklanakarin Journal of Science and Technology, 38, 569–574.

Morrison, D. F. (1976). Multivariate statistical methods. San Francisco, CA: McGraw Hill.

Savic, M. (2006). P-charts in the quality control of the grading process in the high education, No 200636, Working Papers, Faculty of Economics in Subotica.

Wang, W. (2012). A simulation-based multivariate bayesian control chart for real time condition-based maintenance of complex systems. European Journal of Operational Research, 218, 726–734.