Research Article
ExperimentalandStatisticalInvestigationofMachinabilityofAISI
D2 Steel Using Electroerosion Machining Method in Different
Machining Parameters
Engin Nas ,
1
Onur
¨
Ozbek ,
2
Furgan Bayraktar ,
3
and Fuat Kara
4
1
D¨ uzce University, Dr. Engin PAK Cumayeri Vocational School, D¨ uzce, Turkey
2
D¨ uzce University, G¨ um¨ us ¸ova Vocational School, D¨ uzce, Turkey
3
Manufacturing Engineering, D¨ uzce University, D¨ uzce, Turkey
4
Mechanical Engineering, D¨ uzce University, D¨ uzce, Turkey
Correspondence should be addressed to Engin Nas; enginnas@duzce.edu.tr
Received 5 August 2021; Revised 13 September 2021; Accepted 19 September 2021; Published 22 October 2021
Academic Editor: Ab´ ılio De Jesus
Copyright © 2021 Engin Nas et al. is is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
is study investigated the effects of machining parameters on the experimental and statistical results using the electric discharge
method in the machining of AISI D2 cold work tool steel. e design of the experiment was established using the Taguchi L
18
method.
e effect of the experiment parameters on the performance characteristics was analyzed by analysis of variance (ANOVA). As a
result of the study, it was determined that increasing amperage and pulse time affected the surface roughness and hole diameter on
the surface of the material. e lowest values for surface roughness, machining time, hole diameter, and crater diameter were
determined as 2.085 μm, 47minutes, 12.010mm, and 81.007 μm, respectively. e highest wear amount was obtained as 0.604 grams
with the processed parameters in the ninth experiment. When the signal-to-noise ratios were examined, the optimum combinations
of the control factors for surface roughness, hole diameter, crater diameter, wear amount, wear rate, and processing time were
determined as A
1
B
1
C
3
, A
1
B
1
C
3
, A
1
B
1
C
3
, A
1
B
3
C
1
, A
2
B
1
C
1
, and A
1
B
3
C
3
, respectively. According to the ANOVA results, the most
important parameters affecting the test results for surface roughness, hole diameter, crater diameter, wear amount, material wear loss,
and processing time were determined as amperage (49.34%), time-on (59.38%), amperage (55.65%), time-on (56.92%), amperage
(51.42%), and amperage (78.02%), respectively. When the gray relational degree was calculated for the maximum and minimum
values, the ideal factors for all output results were found to be the parameters applied in the third experiment.
1. Introduction
e importance of steel material selection in mold pro-
duction is great. Rather than considering the plastic prop-
erties of the raw material to be used, such as hardness and
corrosion resistance, in the selection of mold steels, resis-
tance to chemical interaction, surface hardening, and ma-
chinability properties should be examined. In addition,
parameters such as the design dimensions of the mold,
surface polishability, and weldability should be taken into
account. Increased mold sizes require higher toughness.
erefore, the heat treatments to be applied may cause
deformation problems (distortion, cracking, etc.) during
hardening. For these reasons, in the industry, it is advan-
tageous to have prehardened mold steels available [1, 2].
As one of the advanced manufacturing methods, electric
discharge machining (EDM) is frequently used in addition
to traditional manufacturing techniques in the processing of
molded materials. Electric discharge machining is an un-
usual manufacturing method used for the processing of hard
and geometrically complex materials. Although EDM, also
known as electroerosion machining, utilizes electrical en-
ergy, the material removal process is in the category of
thermal processing methods, since it is carried out with
thermal energy. e machining performance in EDM has no
effect on the stiffness, toughness, and strength of the material
Hindawi
Advances in Materials Science and Engineering
Volume 2021, Article ID 1241797, 17 pages
https://doi.org/10.1155/2021/1241797