Open Access

Downloads

Download data is not yet available.

Abstract

Die-sinking electrical discharge machining (EDM) is one of the most popular machining methods to manufacture dies and press tools because of its capability to produce complicated shapes and machine very hard materials. In this article, MRR study on die-sinking EDM in rough machinng of SKD11 die steel has been carried out. Response surface methodology (RSM) has been used to plan and analyze the experiments. Current (I), pulse on time (Ton) and voltage (U) were chosen as process parameters to study the die-sinking EDM performance in term of MRR. The results indicated that in order to obtain a high value of MRR within the work interval of this study, Ton should be fixed as low as possible, and conversely, the larger the selected I and U. And the optimal value of MRR was 139.126 mg/min at optimal process parameters I = 10 A, U = 90 V and Ton = 100 s. The mathematical model for the MRR can be effectively employed for the optimal process parameters selection in die-sinking EDM for SKD11 die steel. Empirical tests show that the model can calculate quite accurately predicted by MRR (error  0.6%).



Author's Affiliation
Article Details

Issue: Vol 1 No 1 (2018)
Page No.: 20-27
Published: Aug 1, 2019
Section: Research article
DOI: https://doi.org/10.15419/stdjet.v1i1.523

 Copyright Info

Creative Commons License

Copyright: The Authors. This is an open access article distributed under the terms of the Creative Commons Attribution License CC-BY 4.0., which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

 How to Cite
Huu, P. N., Van, D. N., & Van, B. P. (2019). Application of response surface methodology for evaluating material removal in rate die-sinking EDM roughing using copper electrode. VNUHCM Journal of Engineering and Technology, 1(1), 20-27. https://doi.org/https://doi.org/10.15419/stdjet.v1i1.523

 Cited by



Article level Metrics by Paperbuzz/Impactstory
Article level Metrics by Altmetrics

 Article Statistics
HTML = 3122 times
Download PDF   = 297 times
Total   = 297 times