Issue |
E3S Web Conf.
Volume 130, 2019
The 1st International Conference on Automotive, Manufacturing, and Mechanical Engineering (IC-AMME 2018)
|
|
---|---|---|
Article Number | 01024 | |
Number of page(s) | 10 | |
DOI | https://doi.org/10.1051/e3sconf/201913001024 | |
Published online | 15 November 2019 |
Regression Equations to Determine the Stages of Electric Current in Electrical Discharge Machining (EDM) According to the Level of Desired Surface Roughness with Shortest Processing Time
1
Mechanical Engineering Department, Petra Christian University,
Jl. Siwalankerto No.121–131,
Surabaya,
60236,
Indonesia
2
Mechanical Engineering Department, Chung Yuan Christian University, Chung Li District,R.O.C.,
200 Chung Pei Road,
Taoyuan City,
32023,
Taiwan
* Corresponding author: ralimin@petra.ac.id
Electrical Discharge Machining (EDM) is one of the most common non-conventional machining processes used in the manufacturing of die and mold. In the process of EDM, practitioners usually face a problem, which is how to shorten process time and determine the point where the current should be changed so that the resulted surface roughness is not too high due to the use of large current at the beginning of the process. The purpose of this study is to determine the point when to change (reduce) the current in order to obtain the desired surface roughness and shortest processing time. From analysis of data, experiment was obtained some regression equations, those are: average surface roughness (Ra = 5424 + 0.698 I) which is used to find the final current to obtain the desired final surface roughness, peaks to valleys average roughness (Rz = 5.73 + 3.418 I) which is used to find the changing point for initial currentand duration of processing time (t =103.164 + 0.4714 I) which is used to estimate the duration of processing time with the input of initial and final currents.
Key words: EDM sinking parameters / electro-thermal machining process / quality engineering
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.