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Predictive topography impact model for Electrical Discharge Machining (EDM) of metal surfaces

Published online by Cambridge University Press:  18 November 2019

Johan Bäckemo ,
Matthias Heuchel ,
Markus Reinthaler ,
Karl Kratz  and
Andreas Lendlein
Johan Bäckemo
Affiliation:
Institute of Biomaterial Research and Berlin-Brandenburg Center for Regenerative Therapies, Helmholtz-Zentrum Geesthacht, Kantstrasse 55, 14513 Teltow, Germany Institute of Chemistry, University of Potsdam, Karl-Liebknecht-Str. 24/25, 14476 Potsdam, Germany
Matthias Heuchel
Affiliation:
Institute of Biomaterial Research and Berlin-Brandenburg Center for Regenerative Therapies, Helmholtz-Zentrum Geesthacht, Kantstrasse 55, 14513 Teltow, Germany
Markus Reinthaler
Affiliation:
Institute of Biomaterial Research and Berlin-Brandenburg Center for Regenerative Therapies, Helmholtz-Zentrum Geesthacht, Kantstrasse 55, 14513 Teltow, Germany Department of Cardiology, Campus Benjamin Franklin, Charité Berlin, Berlin, Germany
Karl Kratz
Affiliation:
Institute of Biomaterial Research and Berlin-Brandenburg Center for Regenerative Therapies, Helmholtz-Zentrum Geesthacht, Kantstrasse 55, 14513 Teltow, Germany
Andreas Lendlein*
Affiliation:
Institute of Biomaterial Research and Berlin-Brandenburg Center for Regenerative Therapies, Helmholtz-Zentrum Geesthacht, Kantstrasse 55, 14513 Teltow, Germany Institute of Chemistry, University of Potsdam, Karl-Liebknecht-Str. 24/25, 14476 Potsdam, Germany
*
*To whom correspondence should be addressed: Prof. Dr. Andreas Lendlein, email: [email protected]
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Abstract

Electrical discharge machining (EDM) is a method capable of modifying the microstructure of metal surfaces. Here, we present a predictive computer supported model of the roughness generated on the surface by this process. EDM is a stochastic process, in which charge generated between a metallic substrate and an electrode creates impacts, and thus is suitable for modeling through iterative simulations. The resulting virtual, modified surface structures were evaluated for roughness. Curvatures were analyzed using Abbott-Firestone curves. Three radii of impacts (10, 20, 30 μm) and two values for the depth to radius ratio (0.1, 0.3) were used as input parameters to compute a total of six simulations. It was found that the roughness parameters followed an inverse exponential trend as a function of impact number, and that the strongly concave curvatures reached equilibrium at an earlier impact number for lower depth to radius ratios.

Keywords

modelingdatamachiningmicrostructuretopological
Type
Articles
Information
MRS Advances , Volume 5 , Issue 12-13: Soft Materials and Biomaterials , 2020 , pp. 621 - 632
Copyright
Copyright © Materials Research Society 2019

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