Optimization of Control Charts with Multi-Stage Sampling Using Genetic Algorithm 

Document Type : Original Article

Authors

1 Instructor, Faculty of Engineering, Shohadaye Hoveizeh University of Technology, Susangerd, Iran,  

2 Instructor, Department of Mathematics and Computer Science, Sheikh Bahaei University, Isfahan, Iran,  

Abstract
 Different types of process control methods exist for jointly monitoring of several quality characteristic. Recent studies have shown that multi-stage sampling control charts perform better in detecting shifts in process. Therefore, because of the efficiency of the joint mean and standard deviation charts with multi-stage sampling in detecting shifts in mean and standard deviation of the process, discussion and consideration of these charts is necessary. In this paper, the joint Double Sampling and Triple Sampling mean and standard deviation charts are introduced. The joint Statistical Design of these charts is formulated as an optimization problem and solved using a genetic algorithm. 
 
 

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