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Quality Engineering Volume 7, 1995 - Issue 4
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Original Articles

SIMULTANEOUS REPRESENTATION OF MULTIVARIATE AND CORRESPONDING UNIVARIATE X¯ CHARTS USING LINE-GRAPH

NAGANAND SUBRAMANYAM Fuel Systems Operation Cummins Engine Company, Columbus, Indiana
&
ALI A. HOUSHMAND Department of Mechanical, Industrial and Nuclear Engineering, University of Cincinnati College of Engineering, Cincinnati, Ohio, 45221-0116
Pages 681-692 | Published online: 24 Oct 2007

Citations (15)

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Read on this site (2)

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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Articles from other publishers (13)

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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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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Charles W. Champ & Francisco Aparisi. (2007) Double sampling hotelling's T 2 charts . Quality and Reliability Engineering International 24:2, pages 153-166.
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N. Boudaoud & Z. Cherfi. (2005) The T>sup<2>/sup<Control Chart in a Multimodal Framework: Detection of Incipient Trends. The T>sup<2>/sup<Control Chart in a Multimodal Framework: Detection of Incipient Trends.
Adnan Hassan, Mohd Shariff Nabi Baksh & Awaluddin M. Shaharoun. (2000) Issues in quality engineering research. International Journal of Quality & Reliability Management 17:8, pages 858-875.
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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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