Experimental Investigation and Modelling of Surface Integrity, Accuracy and Productivity Aspects in EDM of AISI D2 Steel

By: Pradhan, Mohan KumarContributor(s): Biswas, C K [Supervisor] | Department of Mechanical EnineeringMaterial type: TextTextLanguage: English Publisher: 2010Description: 288 pSubject(s): Engineering and Technology | Mechanical Engineering | Mechatronics | Production Engineering | Finite Element AnalysisOnline resources: Click here to access online Dissertation note: Thesis (Ph.D)- National Institute of Technology, Rourkela Summary: Electrical Discharge Machining (EDM) is one of the most popu lar non-traditional ma- chining process for “difficult to machine” conducting materi als and is quite extensively and successfully used in industry owing to its favourable fe atures and advantages that it can offer. In EDM, the objective is always to get improved Ma terial Removal Rate (MRR) along with achieving better surface quality of machin ed component. Fur- thermore, the essential requirements are as small a thermal ly affected region of the workpiece surface as possible and a lower radial overcut wit h minimal tool wear. The quality of a machined surface is becoming increasingly sign ificant to satisfy the in- creasing demands of superior component performance, longe vity, and reliability thus preserving the integrity of the surface is essential. In ord er to sustain and/or improve reliability of the components, it is always necessary to hav e knowledge of the effects of the manufacturing parameters on the surface integrity, p recision and productivity of the EDMed components. AISI D2 tool steel has a growing range of application in die and mould industries. They are widely used in the manufacture of blanking and cold- forming dies for the production of a wide range of automotive and electronic comp onents. This steel has greater strength and toughness, and is categorised as “diffic ult to machine” material, which pose a major challenge during machining. An experimental investigation is presented to explore the su rface integrity, pro- ductivity and accuracy of the EDMed surface. Parametric ana lysis has been carried out by conducting a set of experiments using AISI D2 tool steel workpiece with cop- per electrode. The investigating factors were discharge cu rrent ( Ip ), pulse duration ( Ton ), duty factor ( Tau ) and discharge voltage ( V ). The effect of the machining parameters on the responses such as surface roughness, resi dual stress, White Layer Thickness (WLT), Surface Crack Density (SCD), MRR, Tool Wea r Rate (TWR), and overcut are investigated. An experimental analysis was performed to establish the most important machin- ing parameters that contribute to white layer formation and surface crack density. The experimental plan for these investigations was conduct ed according to the Re- sponse surface methodology and the results were statistica lly evaluated using analysis of variance. Surface topography and sub-surface structure s are investigated by scan- ning electron microscopy. It is established that average re cast layer thickness with an increasing discharge current, pulse duration and duty cycl e, but the SCD decreases with increase in discharge current and pulse duration. Howev er, the pulse current is the most dominating parameter followed by pulse duration fo r both the responses. Results showed that current is the most significant paramete r that influenced the machining responses. However, the recast layer thickness in creases with increasing discharge current, pulse duration and duty cycle. But the SC D decreases with increase in discharge current and pulse duration. Besides, similar investigation is conducted for the surfac e roughness and the input factors that significantly influenced the output response ar e discharge current, pulse duration and Tau . Also it reveals that in order to obtain better surface qualit y the discharge current, pulse on time and the duty factor should b e set as low as possible. Finite Element Method (FEM) was employed to evaluate the res idual stress. The results show that the peak temperature sharply increases wi th pulse current. The workpiece is severely affected by the thermal stresses to a la rger depth with increasing pulse energy. The nature of residual stresses is predominan tly tensile in nature and the stress levels reaches its maximum values close to the sur face but diminishes very rapidly to comparatively low values of compressive residua l stresses in the sub-surface area. The residual stresses were obtained by XRD measurement technique and the trend of these stresses with depth has an excellent agreemen t with the FEM results. The maximum tensile and compressive residual stresses are n ot effected much by the machining parameters. However, with the pulse energy the dep th at which they occur increases. Full factorial design is employed to evaluate MRR, TWR and Ra dial overcut (OC). Soft computing predictive modelling (ANN, Neuro-fuzzy Mamdani and Neuro-fuzzy vii Sugeno) of these responses has been conducted from experime ntally obtained data. The discharge current is the most dominant factor, followed by pulse duration, duty factor and discharge voltage, for MRR and overcut. While, th e same for TWR is pulse duration, discharge current, discharge voltage, and duty f actor. The performance of soft computing models for predicting these responses are fo und to be comparable in terms of the prediction accuracy and speed. However, the Ma mdani model is converging with a lower Mean Square Error (MSE) than the Suge no system and the ANN network is in general converging much faster than the other two. The average prediction errors for all these models are quite comparable .
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Thesis (Ph.D/M.Tech R) Thesis (Ph.D/M.Tech R) BP Central Library
Thesis Section
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Thesis (Ph.D)- National Institute of Technology, Rourkela

Electrical Discharge Machining (EDM) is one of the most popu
lar non-traditional ma-
chining process for “difficult to machine” conducting materi
als and is quite extensively
and successfully used in industry owing to its favourable fe
atures and advantages that
it can offer. In EDM, the objective is always to get improved Ma
terial Removal Rate
(MRR) along with achieving better surface quality of machin
ed component. Fur-
thermore, the essential requirements are as small a thermal
ly affected region of the
workpiece surface as possible and a lower radial overcut wit
h minimal tool wear. The
quality of a machined surface is becoming increasingly sign
ificant to satisfy the in-
creasing demands of superior component performance, longe
vity, and reliability thus
preserving the integrity of the surface is essential. In ord
er to sustain and/or improve
reliability of the components, it is always necessary to hav
e knowledge of the effects
of the manufacturing parameters on the surface integrity, p
recision and productivity
of the EDMed components.
AISI D2 tool steel has a growing range of application in die and
mould industries.
They are widely used in the manufacture of blanking and cold-
forming dies for the
production of a wide range of automotive and electronic comp
onents. This steel has
greater strength and toughness, and is categorised as “diffic
ult to machine” material,
which pose a major challenge during machining.
An experimental investigation is presented to explore the su
rface integrity, pro-
ductivity and accuracy of the EDMed surface. Parametric ana
lysis has been carried
out by conducting a set of experiments using AISI D2 tool steel
workpiece with cop-
per electrode. The investigating factors were discharge cu
rrent (
Ip
), pulse duration
(
Ton
), duty factor (
Tau
) and discharge voltage (
V
). The effect of the machining
parameters on the responses such as surface roughness, resi
dual stress, White Layer
Thickness (WLT), Surface Crack Density (SCD), MRR, Tool Wea
r Rate (TWR), and
overcut are investigated.
An experimental analysis was performed to establish the most
important machin-
ing parameters that contribute to white layer formation and
surface crack density.
The experimental plan for these investigations was conduct
ed according to the Re-
sponse surface methodology and the results were statistica
lly evaluated using analysis
of variance. Surface topography and sub-surface structure
s are investigated by scan-
ning electron microscopy. It is established that average re
cast layer thickness with an
increasing discharge current, pulse duration and duty cycl
e, but the SCD decreases
with increase in discharge current and pulse duration. Howev
er, the pulse current is
the most dominating parameter followed by pulse duration fo
r both the responses.
Results showed that current is the most significant paramete
r that influenced the
machining responses. However, the recast layer thickness in
creases with increasing
discharge current, pulse duration and duty cycle. But the SC
D decreases with increase
in discharge current and pulse duration.
Besides, similar investigation is conducted for the surfac
e roughness and the input
factors that significantly influenced the output response ar
e discharge current, pulse
duration and
Tau
. Also it reveals that in order to obtain better surface qualit
y the
discharge current, pulse on time and the duty factor should b
e set as low as possible.
Finite Element Method (FEM) was employed to evaluate the res
idual stress. The
results show that the peak temperature sharply increases wi
th pulse current. The
workpiece is severely affected by the thermal stresses to a la
rger depth with increasing
pulse energy. The nature of residual stresses is predominan
tly tensile in nature and
the stress levels reaches its maximum values close to the sur
face but diminishes very
rapidly to comparatively low values of compressive residua
l stresses in the sub-surface
area. The residual stresses were obtained by XRD measurement
technique and the
trend of these stresses with depth has an excellent agreemen
t with the FEM results.
The maximum tensile and compressive residual stresses are n
ot effected much by the
machining parameters. However, with the pulse energy the dep
th at which they occur
increases.
Full factorial design is employed to evaluate MRR, TWR and Ra
dial overcut (OC).
Soft computing predictive modelling (ANN, Neuro-fuzzy Mamdani
and Neuro-fuzzy
vii
Sugeno) of these responses has been conducted from experime
ntally obtained data.
The discharge current is the most dominant factor, followed
by pulse duration, duty
factor and discharge voltage, for MRR and overcut. While, th
e same for TWR is pulse
duration, discharge current, discharge voltage, and duty f
actor. The performance of
soft computing models for predicting these responses are fo
und to be comparable
in terms of the prediction accuracy and speed. However, the Ma
mdani model is
converging with a lower Mean Square Error (MSE) than the Suge
no system and the
ANN network is in general converging much faster than the other
two. The average
prediction errors for all these models are quite comparable
.

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