Design of mean control and standard deviation diagrams by multiple sampling

Document Type : Original Article

Authors

1 Department of Electrical Engineering, Shohada Hoveyzeh University of Technology, Susangard, Iran

2 Department of Mathematics and Computer Science, Sheikh Baha'i University, Isfahan, Iran

Abstract
In statistical quality control, the concentration and dispersion of continuous quality characteristics in a process are usually examined simultaneously with the help of two graphs. In this way, the changes in each will be identifiable simultaneously. Due to the high efficiency of control graphs of mean and standard deviation with double sampling in rapid identification of mean changes and standard deviation of the process, discussion of this category of graphs seems necessary. In this paper, based on the results of designing mean control and standard deviation diagrams with double sampling, mean and control standard deviation diagrams with triple sampling are introduced. Statistical design of mean control and standard deviation diagrams with triple sampling is formulated as an optimization problem and to solve this problem, genetic algorithm is proposed.

Keywords


[1] مونتگومری، داگلاس سی (1998). کنترل کیفیت آماری. رسول نورالسناء مترجم (1377)، نوبت شانزدهم، تهران، انتشارات دانشگاه علم و صنعت ایران.
[2] بامنی مقدم، محمد (1385). کنترل کیفیت آماری. تهران، انتشارات دانشگاه پیام نور.
[3] Croasdale, P. (1974). Control Charts for a Double Sampling scheme Based on Average Production Run Lengths. International Journal of Production Research, Vol (12), 585-592.
[4] He, D., & Grigoryan, A. (2010). An Improved Double Sampling S-chart, International Journal of Production Research, Vol (41), 2663-2679.
[5] Daudin, J.J. (1992). Double Sampling  Charts. Journal of Quality Technology, Vol (24), 78-87.
[6] He, D., & Grigoryan, A. (2015). Joint Statistical Design of Double Sampling   and S Charts. European Journal of Operational Research, Vol (168), 122-142.
[7] He, D., Grigoryan, A., & Sigh, M. (2013). Design of Double and Triple-Sampling  Control Charts Using Genetic Algorithms. International Journal of Production Research, Vol (40), 1387-1404.
[8] Bateni, N., & Hamadani, A. Z. (2011). Computation of the Probability of a Process Being in Control at the Third Stage for the TS  Chart. International Journal of Production Research, Vol (47), 7069-7073.
[9] Woodall, W.H., & Montgomery, D.C. (1999). Research Issues and Ideas in Statistical Process Control. Journal of Quality Control, Vol (31), 376-386.
[10] Rao, S.S. (1996).Engineering Optimization: Theory and practice. New York: John Wiley and Sons.