Small Shifts Quality Control Schemes under MMSE Feedback Adjustment

Hai Yu Wang

doi:10.4028/www.scientific.net/AMR.915-916.1471

Paper Titles

A New Functional Approach for Searching Optimal Reservoir Rule Curves
p.1452

Calculation Method on Process Capability Index of True Position Based on Maximum Material Condition
p.1456

Distributed SWAT Model for Ecological Remediation Project Assessment
p.1460

Research on Intelligent Collaborative System for Auto Parts Industry
p.1464

Small Shifts Quality Control Schemes under MMSE Feedback Adjustment
p.1471

Application of CDIO Idea in Engineering Training
p.1479

Logistics Business Optimization of Small and Medium-Sized Garment Manufacturing
p.1483

Study of Minimal Power Demand and Life Sustainable Time in the Residential Sector during Power Failure (in Korea)
p.1487

Study on Development Model of Engineering Manufacturing
p.1491

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 915-916Small Shifts Quality Control Schemes under MMSE...

Small Shifts Quality Control Schemes under MMSE Feedback Adjustment

Abstract:

This paper discusses small shifts process monitoring under MMSE adjustment. Based on the analysis of affect of feedback adjustment method to effective of control charts, small shifts process monitoring schemes of process output and control actions are proposed. An optimal strategy is provided by comparing monitoring performances of different control charts with different small abnormal shifts.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 915-916)

Pages:

1471-1475

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.915-916.1471

Citation:

Cite this paper

Online since:

April 2014

Authors:

Hai Yu Wang

Keywords:

Average Run Length, CUSUM Chart, EWMA Chart, MMSE Adjustment

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Woodall. W.H. Controversies and Contradictions in Statistical Process Control (with discussion) [J]. Journal of Quality Technology, 2000, 1(1): 1-24.

Google Scholar

[2] Zhang Min, He Zhen. Quality Control Chart for Auto-correlated Processes of Manufacturing Industrials [J]. Application of Statistics and Management, 2007, 26(1): 96-101.

Google Scholar

[3] Jiang. W. and Tsui K.L. SPC Monitoring of MMSE- and PI- Controlled Processes [J]. Journal of Quality Technology, 2002, 34(4): 384-392.

DOI: 10.1080/00224065.2002.11980171

Google Scholar

[4] S. CHEN and H. B. Nembhard. Multivariate Cuscore Control Charts for Monitoring the Mean Vector in Autocorrelated Processes [J]. IIE Transactions, 2011, 43: 291–307.

DOI: 10.1080/0740817x.2010.523767

Google Scholar

[5] Lu Chao-Wen, Reynolds. Jr, Control Charts for Monitoring the Mean and Variance of Autocorrelated Processes [J]. Journal of Quality Technology, 1999, 31(3): 259-274.

DOI: 10.1080/00224065.1999.11979925

Google Scholar

[6] Box. G.E.P., Kramer. T. Statistical Process Monitoring and Feedback Adjustment: Discussion [J]. Technometrics, 1992, 34(3): 251-285.

DOI: 10.2307/1270028

Google Scholar

[7] Wang Haiyu, Xu Jichao, Yang Jianfeng. Statistical Process Control of MMSE- and PI-controlled Process [J], Systems Engineering-Theory & Practice, 2006, 26(6): 75-80.

Google Scholar

[8] Montgomery, D. C., J. B. Keats, G. C. Runger and W. S. Messina, Integrating Statistical Process Control and Engineering Process Control [J]. Journal of Quality Technology, 1994, 26: 79-87.

DOI: 10.1080/00224065.1994.11979508

Google Scholar

[9] Chin-Yao Low, Fong-Jung Yu and Chun-Ju Yang. Control Charts Evaluation and Selection under Integrated EPC and SPC Environment [J]. Journal of the Chinese Institute of Industrial Engineers, 2001, 18(6): 63-72.

DOI: 10.1080/10170660109509469

Google Scholar

[10] Shu, L. and Jiang, W. (2006) A Markov chain model for the adaptive CUSUM control chart. Journal of Quality Technology, 38, 135–147.

DOI: 10.1080/00224065.2006.11918601

Google Scholar