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An Operating and Diagnostic Knowledge-Based System for Wire EDM

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2003)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2773))

Abstract

The selection of machining parameters and machine settings for wire electrical discharge machining (WEDM) depends mainly on both technologies and experience provided by machine tool manufacturers. The present work designs a knowledge-based system (KBS) to select the optimal process parameters settings and diagnose the machining conditions for WEDM. Moreover, the present results supply users of WEDM with beneficial data avoiding further experimentation. Various materials are tested and sample results are presented for improving the WEDM performance.

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Author information

Authors and Affiliations

  1. Faculty of Engineering, Ain Shams University, 11517, Cairo, Egypt

    Samy Ebeid

  2. Shoubra Faculty of Engineering, Zagazig University, Egypt

    Raouf Fahmy & Sameh Habib

Authors
  1. Samy Ebeid
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  2. Raouf Fahmy
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  3. Sameh Habib
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Editor information

Editors and Affiliations

  1. Computing Laboratory, Oxford University, Parks Road, OXI 3QD, United Kingdom

    Vasile Palade

  2. Intelligent Systems and Signal Processing Labs, Moulsecoomb, University of Brighton, BN2 4GJ, Brighton, United Kingdom

    Robert J. Howlett

  3. Knowledge-Based Intelligent Engineering Systems Centre, Mawson Lakes, University of South Australia, 5095, Adelaide, SA, Australia

    Lakhmi Jain

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© 2003 Springer-Verlag Berlin Heidelberg

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Ebeid, S., Fahmy, R., Habib, S. (2003). An Operating and Diagnostic Knowledge-Based System for Wire EDM. In: Palade, V., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2003. Lecture Notes in Computer Science(), vol 2773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45224-9_94

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  • DOI: https://doi.org/10.1007/978-3-540-45224-9_94

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40803-1

  • Online ISBN: 978-3-540-45224-9

  • eBook Packages: Springer Book Archive

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