Education, Science, Technology, Innovation and Life
Open Access
Sign In
  1. Home
  2. Journals
  3. Advances in Computer, Signals and Systems
  4. Vol 7, Issue 11, 2023

A Multivariate Statistical Process Control Model Based on CRITIC Entropy Method and EWMA

Download as PDF

DOI: 10.23977/acss.2023.071104 | Downloads: 10 | Views: 262

Author(s)

Ziyang Pan 1, Xinyu Huang 2

Affiliation(s)

1 School of Statistics and Mathematics, Central University of Finance and Economics, Beijing, 102206, China
2 School of Mathematics and Statistics, Northeastern University at Qinhuangdao, Qinhuangdao, 066004, China

Corresponding Author

Ziyang Pan

ABSTRACT

Statistical process control is a technique to monitor product or service quality timely that ensure stability. It promotes quality assurance, resource optimization, and is crucial to informed decision-making. Given the diversification of quality indicators, this paper introduces a multivariate EWMA control chart model based on the CRITIC and entropy weighting method. This model allows lack of knowledge of variable distributions and considers variable correlations, which demonstrates strong sensitivity to slight drifts in mean and volatility, even with a non-diagonal covariance matrix. Simulation experiments confirm its ability to identify process changes and their types by manipulating the mean vector and covariance matrix in five controlled experiments.

KEYWORDS

Multivariate Statistical Process Control, CRITIC, Entropy Method, EWMA Control Chart

CITE THIS PAPER

Ziyang Pan, Xinyu Huang, A Multivariate Statistical Process Control Model Based on CRITIC Entropy Method and EWMA. Advances in Computer, Signals and Systems (2023) Vol. 7: 20-26. DOI: http://dx.doi.org/10.23977/acss.2023.071104.

REFERENCES

[1] Trawiell, R. W., & Dong, X. L. (1992). Precontrol: A good alternative to X-R control charts. Mathematical Statistics and Management, (02), 40-43. 
[2] Zhao, T. (1998). Application of X-R control chart in small-batch production with multiple varieties. Journal of Industrial Engineering and Engineering Management, (03), 37-42+47.
[3] Sun, X., & Wang, S. (2021). Comparison of σ estimation methods in mean-standard deviation control charts. Statistics and Decision, 37(18), 32-35.
[4] Brook B D, Evans D A. An approach to the probability distribution of cusum run length [J]. Biometrika, 1972, 59: 539-549.
[5] Lucas J M, Saccucci M S. Exponentially weighted moving average control schemes: Properties and enhancements [J]. Technometrics, 1990, 32: 1-12.
[6] Ma, Y., & Yuan, Z. (1998). Application research of EWMA quality control chart. Mechanical Engineer, (S1), 13-15.
[7] Gan F F. Designs of One and Two-sided Exponential EWMA Charts [J]. Journal of Quality Technology,1998,30(1).
[8] Chen, J., Chen, W., & Sun, J. (2014). Overview of research on multi-model adaptive control. Journal of Systems Science and Mathematical Sciences, 34(12), 1421-1437.
[9] Ping, A., Sun, J., Hu, X., et al. (2021). Design of adaptive exponentially weighted moving average control chart. Statistics and Decision, 37(22), 27-31. 
[10] Khoo M B C. A control chart based on the sample median for the detection of a permanent shift in the process mean [J]. Quality Engineering, 2005, 17: 243-257.
[11] Jiang, Y., & Feng, Z. (2022). Research and application of high-dimensional robust Hotelling T^2 control chart. Journal of Systems Science and Mathematical Sciences, 42(07), 1877-1890.
[12] Wang, B., & Wei, J. (2021). Construction and comparison of robust statistical process control charts. Statistics and Decision, 37(06), 50-55. 
[13] Huang, N. (1999). Reflections on the application of principal component analysis. Mathematical Statistics and Management, (05), 44-46+52. 
[14] Guo, M., & Wang, S. (2004). Research on system performance monitoring method based on independent component analysis. Journal of Zhejiang University (Engineering Science Edition), (06), 14-18.
[15] He, X., Zhu, H., & Gao, C. (2009). Risk evaluation of real estate project investment based on entropy weight method and TOPSIS method. Business Research, (03), 105-108. 
[16] Zhang, Y., & Wei, H. (2012). Combination weighting method for multi-attribute decision-making based on CRITIC. Statistics and Decision, (16), 75-77.

Subscription
E-Mail Alert
Most popular papers
Call for Special Issue
Publication Ethics & OA Statement
Plagiarism Policy
Contact Us
Downloads: 13629
Visits: 260125

Sponsors, Associates, and Links

All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.