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International Conference on Innovative Techniques and Applications of Artificial Intelligence

SGAI 2011: Research and Development in Intelligent Systems XXVIII pp 211–216Cite as

Quality Management Using Electrical Capacitance Tomography and Genetic Programming: A new Framework

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Abstract

Currently, many automotive companies struggle with expensive product recalls. To overcome these issues the need for quality management increases. Hence, we propose a monitoring and control framework for Lost Foam Casting (LFC) manufacturing processes using Electrical Capacitance Tomography (ECT) and an evolutionary Genetic Programming (GP) based system. The multi-tier framework simulates the process output, helps simulating a metal filling modeling part of the process and supports product quality control. The results are very promising.

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References

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Author information

Authors and Affiliations

  1. Computer Science Department, The World Islamic Science and Education (WISE) University, Amman, Jordan

    Alaa F. Sheta

  2. Computer Science Department, Georg Simon Ohm University of Applied Sciences, Nuremberg, Germany

    Peter Rausch

  3. Image Technologies Inc. (ITEC), Amman, Jordan

    Alaa Al–Afeef

Authors
  1. Alaa F. Sheta
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  2. Peter Rausch
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  3. Alaa Al–Afeef
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Corresponding author

Correspondence to Alaa F. Sheta .

Editor information

Editors and Affiliations

  1. University of Portsmouth, Lion Terrace, Portsmouth, PO1 3HE, United Kingdom

    Max Bramer

  2. School of Computing &, Mathematical Sciences, University of Greenwich, Park Row 30, London, SE10 9LS, United Kingdom

    Miltos Petridis

  3. , School of Computing and Informatics, Nottingham Trent University, Burton Street, Nottingham, NG1 4BU, United Kingdom

    Lars Nolle

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© 2011 Springer-Verlag London Limited

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Cite this paper

Sheta, A.F., Rausch, P., Al–Afeef, A. (2011). Quality Management Using Electrical Capacitance Tomography and Genetic Programming: A new Framework. In: Bramer, M., Petridis, M., Nolle, L. (eds) Research and Development in Intelligent Systems XXVIII. SGAI 2011. Springer, London. https://doi.org/10.1007/978-1-4471-2318-7_15

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  • DOI: https://doi.org/10.1007/978-1-4471-2318-7_15

  • Published:

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-2317-0

  • Online ISBN: 978-1-4471-2318-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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