Micro-EDM process modeling and machining approaches for minimum tool electrode wear for fabrication of biocompatible micro-components

Govindan Puthumana

Research output: Contribution to journalJournal articleResearchpeer-review

122 Downloads (Pure)

Abstract

Micro-electrical discharge machining (micro-EDM) is a potential non-contact method for fabrication of biocompatible micro devices. This paper presents an attempt to model the tool electrode wear in micro-EDM process using multiple linear regression analysis (MLRA) and artificial neural networks (ANN). The governing micro-EDM factors chosen for this investigation were: voltage (V), current (I), pulse on time (Ton) and pulse frequency (f). The proposed predictive models generate a functional correlation between the tool electrode wear rate (TWR) and the governing micro-EDM factors. A multiple linear regression model was developed for prediction of TWR in ten steps at a significance level of 90%. The optimum architecture of the ANN was obtained with 7 hidden layers at an R-sq value of 0.98. The predicted values of TWR using ANN matched well with the practically measured and calculated values of TWR. Based on the proposed soft computing-based approach towards biocompatible micro device fabrication, a condition for the minimum tool electrode wear rate (TWR) was achieved.
Original languageEnglish
JournalJournal of Machine Engineering
Volume17
Issue number3
Pages (from-to)97-111
ISSN1895-7595
Publication statusPublished - 2017

Keywords

  • Biocompatibility
  • Micro devices
  • Electrical discharge machining
  • Modeling
  • Multiple linear regression
  • Artificial neural networks

Fingerprint

Dive into the research topics of 'Micro-EDM process modeling and machining approaches for minimum tool electrode wear for fabrication of biocompatible micro-components'. Together they form a unique fingerprint.

Cite this