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Optimization of machining parameters using magnetic-force-assisted EDM based on gray relational analysis

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Abstract

This work developed a novel process of magnetic-force-assisted electrical discharge machining (EDM) and conducted an experimental investigation to optimize the machining parameters associated with multiple performance characteristics using gray relational analysis. The main machining parameters such as machining polarity (P), peak current (I P), pulse duration (τ P), high-voltage auxiliary current (I H), no-load voltage (V), and servo reference voltage (S V) were selected to explore the effects of multiple performance characteristics on the material removal rate, electrode wear rate, and surface roughness. The experiments were conducted according to an orthogonal array L18 based on Taguchi method, and the significant process parameters that affected the multiple performance characteristics of magnetic-force-assisted EDM were also determined form the analysis of variance. Moreover, the optimal combination levels of machining parameters were also determined from the response graph and then verified experimentally. The multiple performance characteristics of the magnetic-force-assisted EDM were improved, and the EDM technique with high efficiency, high precision, and high-quality surface were established to meet the demand of modern industrial applications.

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Authors and Affiliations

  1. Department of Mechanical Engineering, Nankai University of Technology, Caotun, Nantou, 54243, Taiwan

    Yan-Cherng Lin

  2. Graduate Institute of Engineering Technology, Chungchou Institute of Technology, Yuanlin, Changhau, 51003, Taiwan

    Ho-Shiun Lee

Authors
  1. Yan-Cherng Lin
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  2. Ho-Shiun Lee
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Correspondence to Yan-Cherng Lin.

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Lin, YC., Lee, HS. Optimization of machining parameters using magnetic-force-assisted EDM based on gray relational analysis. Int J Adv Manuf Technol 42, 1052–1064 (2009). https://doi.org/10.1007/s00170-008-1662-7

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  • DOI: https://doi.org/10.1007/s00170-008-1662-7

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