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Intelligence Statistical Process Control in Cellular Manufacturing Based on SVM

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Advances in Neural Networks – ISNN 2011 (ISNN 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6676))

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Abstract

According to peculiarity of cellular manufacturing, the method of drawing control chart was proposal. In the modeling of structure for patterns recognition of control chart in cellular manufacturing, the mixture kernel function was proposed, and one-against-one algorithm multi-class classification support vector machine was applied, and genetic algorithm was used to optimize the parameters of SVM. The simulation results show that the performance of mixture kernel is superior to a single common kernel, and it can recognize each pattern of the control chart accurately, and it is superior to probabilistic neural network and wavelet probabilistic neural network in the aggregate classification rate, type I error, type II error, and also has such advantages as simple structure, quick convergence, which can be used in control chart patterns recognition in cellular manufacturing.

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Author information

Authors and Affiliations

  1. Dept. of Economics and Management, Fujian University of Technology, Fuzhou, Fujian, 350108, P.R. China

    Shaoxiong Wu

Authors
  1. Shaoxiong Wu
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Editor information

Editors and Affiliations

  1. Institute of Automation, Key Laboratory of Complex Systems and Intelligence Science, Chinese Academy of Sciences, 100190, Beijing, China

    Derong Liu

  2. College of Information Science and Engineering, Northeastern University, 110004, Shenyang, Liaoing, China

    Huaguang Zhang

  3. Department of Electrical and Computer Engineering, University of Cyprus, 75 Kallipoleos Avenue, 1678, Nicosia, Cyprus

    Marios Polycarpou

  4. Dipartimento di Elettronica, Politecnico di Milano, Piazza L. da Vinci 32, 20133, Milano, Italy

    Cesare Alippi

  5. Deptartment of Electrical, Computer and Biomedical Engineering, University of Rhode Island, 02881, Kingston, RI, USA

    Haibo He

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© 2011 Springer-Verlag Berlin Heidelberg

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Wu, S. (2011). Intelligence Statistical Process Control in Cellular Manufacturing Based on SVM. In: Liu, D., Zhang, H., Polycarpou, M., Alippi, C., He, H. (eds) Advances in Neural Networks – ISNN 2011. ISNN 2011. Lecture Notes in Computer Science, vol 6676. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21090-7_13

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  • DOI: https://doi.org/10.1007/978-3-642-21090-7_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21089-1

  • Online ISBN: 978-3-642-21090-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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