ENBIS-8 in Athens
21 – 25 September 2008
Abstract submission: 14 March – 11 August 2008
Interpreting Multivariate Control Chart Signals using Computational Intelligence Techniques
22 September 2008, 16:00 – 16:20
- Submitted by
- Vassilis Plagianakos
- V.P. Plagianakos
Department of Informatics with Biomedical Applications, University of Central Greece, Papasiopoulou 2-4, Lamia, 35100, Greece.
Department of Informatics & Telematics, Harokopio University, 89, Harokopou Street, 176 71, Kallithea, Greece.
- Multivariate control charts are used for monitoring and controlling the process mean and the process variability of multivariate processes. These control charts are able to recognize an out-of-control process. The identification of an out-of-control variable or variables after a multivariate control chart signals has been an interesting topic for many researchers over the last few years. This work reviews promising techniques for interpreting an out-of-control signal, while introduces new algorithms and models based on recently proposed computational intelligence techniques. The proposed methods, which have a sound mathematical background, are thoroughly investigated and have proven to be efficient and effective.
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