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Journal of Quality Technology
A Quarterly Journal of Methods, Applications and Related Topics
Volume 19, 1987 - Issue 2
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Articles

Displaying Multivariate Data Using Polyplots

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Pages 69-74 | Published online: 21 Feb 2018

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Read on this site (8)

Francisco Aparisi, Gerardo Avendaño & JosÉ Sanz. (2006) Techniques to interpret T 2 control chart signals. IIE Transactions 38:8, pages 647-657.
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AliA. Houshmand & Amir Javaheri. (1998) MULTIVARIATE RIDGE RESIDUAL CHARTS. Quality Engineering 10:4, pages 617-624.
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RussellR. Barton & DavidR. Gonzalez-Barreto. (1996) PROCESS-ORIENTED BASIS REPRESENTATIONS FOR MLTLTIVARIATE PROCESS DIAGNOSTICS. Quality Engineering 9:1, pages 107-118.
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Ross S. Sparks & Alan Eagle. (1996) Graphical Process Monitoring in the Service Industry – A Case Study. Journal of Quality Technology 28:1, pages 99-115.
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CYNTHIAA. LOWRY & DOUGLASC. MONTGOMERY. (1995) A review of multivariate control charts. IIE Transactions 27:6, pages 800-810.
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NAGANAND SUBRAMANYAM & ALIA. HOUSHMAND. (1995) SIMULTANEOUS REPRESENTATION OF MULTIVARIATE AND CORRESPONDING UNIVARIATE X¯ CHARTS USING LINE-GRAPH. Quality Engineering 7:4, pages 681-692.
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Camil Fuchs & Yoav Benjamini. (1994) Multivariate Profile Charts for Statistical Process Control. Technometrics 36:2, pages 182-195.
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Emmanuel Yashchin. (1989) Weighted Cumulative Sum Technique. Technometrics 31:3, pages 321-338.
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Articles from other publishers (18)

Ramy M. Khalifa, Soumaya Yacout & Samuel Bassetto. (2023) Root cause analysis of an out-of-control process using a logical analysis of data regression model and exponential weighted moving average. Journal of Intelligent Manufacturing.
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Amitava Mitra. 2021. Fundamentals of Quality Control and Improvement. Fundamentals of Quality Control and Improvement 89 150 .
Luis Alberto Pargas Carmona. A Graphical Approach for Interpreting Out-of-Control Signals in Multivariate Control Charts. A Graphical Approach for Interpreting Out-of-Control Signals in Multivariate Control Charts.
Yuehjen E. Shao & Shih-Chieh Lin. (2019) Using a Time Delay Neural Network Approach to Diagnose the Out-of-Control Signals for a Multivariate Normal Process with Variance Shifts. Mathematics 7:10, pages 959.
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Yuehjen E. Shao. (2016) Using a Computational Intelligence Hybrid Approach to Recognize the Faults of Variance Shifts for a Manufacturing Process. Journal of Industrial and Intelligent Information.
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Karim Atashgar. (2012) Identification of the change point: an overview. The International Journal of Advanced Manufacturing Technology 64:9-12, pages 1663-1683.
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Yuehjen E. Shao & Chia-Ding Hou. (2013) Hybrid Artificial Neural Networks Modeling for Faults Identification of a Stochastic Multivariate Process. Abstract and Applied Analysis 2013, pages 1-10.
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Karim Atashgar & R. Noorossana. (2011) Diagnosing the source(s) of a monotonic change in the process mean vector. The International Journal of Advanced Manufacturing Technology 60:9-12, pages 1175-1183.
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Francisco Aparisi & Andres Carrion. (2010) Artificial neural networks for identifying the signals of multivariate EWMA control charts. Artificial neural networks for identifying the signals of multivariate EWMA control charts.
Francisco Aparisi. (2010) A neutral network for identifying the out-of-control signals of MEWMA control charts. A neutral network for identifying the out-of-control signals of MEWMA control charts.
Vijay Kumar Butte & Loon Ching Tang. (2010) Multivariate charting techniques: a review and a line-column approach. Quality and Reliability Engineering International 26:5, pages 443-451.
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Amitava Mitra. 2008. Fundamentals of Quality Control and Improvement. Fundamentals of Quality Control and Improvement 93 146 .
Charles W. Champ & Francisco Aparisi. (2008) Double sampling hotelling's T2 charts. Quality and Reliability Engineering International 24:2, pages 153-166.
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Quinton J Nottingham, Deborah F Cook & Christopher W Zobel. (2001) Visualization of multivariate data with radial plots using SAS. Computers & Industrial Engineering 41:1, pages 17-35.
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Orlando O. Atienza, Loon Ching Tang & Beng Wah Ang. (1998) QUALITY NOTES. International Journal of Quality Science 3:2, pages 194-204.
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S. J. Wierda. (1994) Multivariate statistical process control—recent results and directions for future research. Statistica Neerlandica 48:2, pages 147-168.
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A. D. Pouliezos & G. S. StavrakakisA. D. Pouliezos & G. S. Stavrakakis. 1994. Real Time Fault Monitoring of Industrial Processes. Real Time Fault Monitoring of Industrial Processes 1 92 .
Rashi Khanna & Bruce McMillin. (1992) SMILI: Visualization of asynchronous massively parallel programs. Journal of Systems and Software 19:3, pages 261-275.
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