Experimental Study of Anode Shape Prediction in Through Mask Electrochemical Micro Machining

DOI

10.2991/iccasp-16.2017.36How to use a DOI?

Keywords

Electrochemical micromachining, Tooling Design, anode shape prediction, COMSOL Tool

Abstract

To manufacture quality products at lowest cost in industries, optimization is an effective technique which can be Electrochemical micro-machining (EMM) appears to be very promising as a future micro-machining technique, since in many areas of applications it offers several advantages, which include higher machining rate, better precision and control, short lead time and a wide range of materials that can be machined. In this work, the shape evolution in through-mask electrochemical micromachining (ECMM) process is investigated numerically and experimentally. The effect of process parameters on the anode shape was demonstrated by Finite Element Method using COMSOL Multiphysics software. With finite element method (FEM), the anodic evolution process is predicted and effects of stray current also have been identified. The validation experiment is conducted and the hole drilling procedure is observed. The FEM calculation predicted model is in good agreement with experimental model. With the sets of experiments and Finite element analysis simulation, the optimized set and the formulation of the electrolyte in through-mask ECMM are achieved.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Pankaj Jain
AU  - Dilip Ghelot
AU  - Todarmal Bagoriya
PY  - 2016/12
DA  - 2016/12
TI  - Experimental Study of Anode Shape Prediction in Through Mask Electrochemical Micro Machining
BT  - Proceedings of the International Conference on Communication and Signal Processing 2016 (ICCASP 2016)
PB  - Atlantis Press
SP  - 220
EP  - 228
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccasp-16.2017.36
DO  - 10.2991/iccasp-16.2017.36
ID  - Jain2016/12
ER  -