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Optimization with the Evolution Strategy by Example of Electrical-Discharge Drilling

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International Joint Conference SOCO’17-CISIS’17-ICEUTE’17 León, Spain, September 6–8, 2017, Proceeding (SOCO 2017, ICEUTE 2017, CISIS 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 649))

Abstract

A key challenge in electrical discharge machining (EDM) is to find a suitable combination out of numerous process parameters. Any changes, concerning the electrode materials or geometries, require newly optimized technologies. These technologies are to be developed from a considerable number of experiments which must be carried out by an experienced operator.

This paper presents a new method of finding the optimal parameters.

It seems likely that the evolution strategy (ES), a stochastic, metaheuristic optimization method, offers the great advantage of finding solutions, even with little knowledge of system behaviour.

The method involved a randomized and a derandomized ES, based on a non-elitistical (μ,λ)-evolution strategy with one parent and four children. The two ES were initialized from an unfavourable starting point (A) and from a favourable starting point (B), to investigate their effectiveness.

We demonstrate that starting from the unfavourable starting point A the processing duration tero could be reduced by a maximum of 77% with a slightly smaller linear wear of the tool electrode ΔlE after 40 trials.

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Author information

Authors and Affiliations

  1. Institute for Machine Tools and Factory Management IWF, Technische Universität Berlin, Pascalstraße 8-9, 10587, Berlin, Germany

    Jan Streckenbach & Eckart Uhlmann

  2. Chair of Bionics & Evolutiontechnique, Technische Universität Berlin, Ackerstrasse 71-76, 13355, Berlin, Germany

    Ivan Santibáñez Koref & Ingo Rechenberg

  3. Fraunhofer Institute for Production Systems and Design Technology IPK, Pascalstraße 8-9, 10587, Berlin, Germany

    Eckart Uhlmann

Authors
  1. Jan Streckenbach
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  2. Ivan Santibáñez Koref
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  3. Ingo Rechenberg
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  4. Eckart Uhlmann
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Corresponding author

Correspondence to Jan Streckenbach .

Editor information

Editors and Affiliations

  1. University of Leon, Leon, Spain

    Hilde Pérez García

  2. University of Leon, Leon, Spain

    Javier Alfonso-Cendón

  3. University of Leon, Leon, Spain

    Lidia Sánchez González

  4. Department of Industrial Engineering, University of A Coruña, Ferrol, Spain

    Héctor Quintián

  5. University of Salamanca, Salamanca, Spain

    Emilio Corchado

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Streckenbach, J., Koref, I.S., Rechenberg, I., Uhlmann, E. (2018). Optimization with the Evolution Strategy by Example of Electrical-Discharge Drilling. In: Pérez García, H., Alfonso-Cendón, J., Sánchez González, L., Quintián, H., Corchado, E. (eds) International Joint Conference SOCO’17-CISIS’17-ICEUTE’17 León, Spain, September 6–8, 2017, Proceeding. SOCO ICEUTE CISIS 2017 2017 2017. Advances in Intelligent Systems and Computing, vol 649. Springer, Cham. https://doi.org/10.1007/978-3-319-67180-2_12

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  • DOI: https://doi.org/10.1007/978-3-319-67180-2_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67179-6

  • Online ISBN: 978-3-319-67180-2

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