Process parameter optimization of SLM process and application of Taguchi approachâ€“ The Review

IJSRD - International Journal for Scientific Research & Development| Vol. 1, Issue 4, 2013 | ISSN (online): 2321-0613
All rights reserved by www.ijsrd.com 1008
Abstract—Selective Laser Melting (SLM) is an emerging
powder based additive layer manufacturing technology that
used to fabricate three-dimensional fully functional parts
from metal powders by fusing the material in a layer by
layer manner as per a CAD model. The quality of SLM
produced parts is significantly affected by various
manufacturing parameters of SLM machine. Hence
optimization of SLM process parameters is necessary in
order to improve the quality of parts. The purpose of this
paper is to explore the reviews for various optimization
methods used for process parameter optimization of SLM
process and application of Taguchi approach. This review of
work can be helpful to the other researchers to carry out
further work in the same era.
Keywords: Selective Laser Melting (SLM), Optimization,
Taguchi approach, Regression analysis
I. INTRODUCTION
Reduction of product development cycle time is the major
concern in industries for achieving competitive advantage.
Thus the focus of industries has shifted from traditional
product development methodology to rapid fabrication
techniques. Selective Laser Melting (SLM) is an emerging
powder based additive layer manufacturing technology that
used to fabricate three-dimensional fully functional parts
from metal powders by fusing the material in a layer by
layer manner as per a CAD model. Selective Laser Melting
(SLM) is an emerging production technology in the field of
Rapid Prototyping (RP) and Rapid Manufacturing (RM).
But, the quality of SLM produced part is highly depends
upon various process parameters used in this process. So,
there is a need for optimizing the process parameters both
from technological and economic point of view. Because
Optimization of process parameters helps to finding out
correct adjustment of parameters which improve the quality
of the prototypes. Taguchi method is powerful tool for
optimization of process design. The primary advantages for
design of experiments using Taguchi’s technique include
simplification of experimental plan and feasibility of study
of interaction between different parameters.
II. PROBLEM FORMULATION
In today’s competitive market the quality of parts like
surface finish, mechanical strength, dimensional accuracy
etc. is most important things to satisfy and attract the
customers. But as discussed earlier the quality of SLM
produced parts are highly depends upon various process
parameters of the process. For that, process parameter
optimization of SLM process should be carried out. There
are different methods of optimization of process parameter
like factorial design, Taguchi method, central composite
design; response surface methodology etc. without brief
review it is difficult to say which one is better. This paper
helps to find out which method is better for its particular
application and we will use best method to achieve our goal.
III. PROCESS PARAMETER OPTIMIZATION OF SLM
PROCESS
Yongqiang Yang et al. have studied the effect of different
SLM parameter on the density of Ti6Al4V Titanium
material. They have selected SLM parameter such as laser
power, scanning speed, hatching space and scan strategy to
find their effect on SLM fabricated Titanium material.
Taguchi method is selected for design of experiments. They
have employed Analysis of variance (ANOVA) to find out
the percentage contribution of each selective laser melting
parameter. At last the microstructure and property of formed
samples are tested. From the experiments, found that powder
thickness is the most significant influence in processing
parameters on density and sample with density higher than
95% and the microstructure of sample was mainly composed
of acicular martensite, a phase and b phase. The micro-
hardness was 492 HV 0.2 obtained. [1]
S. Dingal et al. have conducted the experiments in
order to achieve optimum value of density, porosity and
hardness of selective laser melting fabricated parts. Taguchi
method is adopted for design of experiments. They have
selected seven important SLM process parameters such as
laser peak, power density, laser pulse on-time, laser scan
speed, stepping distance, interval–spot ratio, size range of
iron powder particles and powder layer thickness. Signal to
noise ratio was selected in order to find out which parameter
was highly significant to response characteristics. After the
experimental work they have conclude that layer thickness
had the most significant influence on the output responses.
[2]
F.Calignano et al. have perform the experiments
in order to achieve optimum value of surface roughness of
DSLM processed aluminum specimens. They have selected
three important SLM process parameters such as scan speed,
laser power and hatching distance. They have employed
Taguchi’s L18 orthogonal array for design of experiments.
Surface morphology was analyzed by means of field
emission scanning electron microscope. After the
experimental work they have conclude that the Scan speed
have greatest influence on the surface roughness of
aluminum samples produced by Direct metal laser sintering
Process parameter optimization of SLM process and application of
Taguchi approach– The Review
Rajnikant B. Rathod1
R. I. Patel2
1
ME Student 2
Associate Professor
1, 2
Department of Mechanical Engineering
1, 2
GEC, Dahod (GTU, Ahmadabad)

Process parameter optimization of SLM process and application of Taguchi approach– The Review
(IJSRD/Vol. 1/Issue 4/ 2013/0046)
(DMLS) compared to other parameter such as laser power
and hatching distance. [3]
K. Abd-Elghany, D.L. Bourell et al. evaluate the
different properties of products fabricated by SLM using
304L stainless steel powders. Using an experimental
approach, 24 samples with different shapes and sizes were
fabricated with layer thickness of 30, 50 and 70mm and
laser scanning speed set at 70 and 90 mm/s. Part geometry,
dimensional tolerance, surface quality, density, mechanical
properties and microstructure were evaluated. After
experiment result confirmed that the using small layer
thickness and low scanning speed improved the properties
by more than 20 per cent. At a layer thickness of 30mm and
speed of 70 mm/s, density was 92 per cent and hardness was
190 HV. At layer thickness of 70mm porosity increases and
cracks started to form which decreased strength and
ductility. Also illustrated in general, that the 304L austenitic
stainless steels have high ductility, low yield stress and
relatively high ultimate tensile strength. [4]
IV. TAGUCHI APPROACH FOR OPTIMIZATION
Ulas et al., were developed, artificial neural network (ANN)
and regression model to predict surface roughness in
abrasive water jet machining (WAJM). They have consider
machining parameters such as traverse speed, water jet
pressure, standoff distance, abrasive grit size and abrasive
flow rate. They have used Taguchi’s design of experiments
in order to collect the surface roughness values. Analysis of
variance (ANOVA) was used to check the validity of
regression model. At the end of the study, both the ANN
and regression analysis results were comparing with
experimental data. It can see from the Fig.4 that both the
models ANN and regression presents a good agreement with
the experimental data. Based on the ANOVA, the most
dominant parameter on the surface roughness was found as
water jet pressure. Abrasive flow rate and standoff distance
were less effective on surface roughness, while effect of
abrasive grit size can be negligible. [5]
Anoop et al., have optimized the efficiency of
pulsed ND: YAG laser for the laser surface structuring of
porous alumina ceramic. The laser processing parameters
like the pulse width, repetition rate and the scanning speed
were evaluated. The Taguchi’s standard L9 orthogonal
arrays were used to identify the combination of process
parameters for optimize physical attribute of the ceramic.
ANOVA is carried out to identify the processing parameters
that contributed the most to minimize the porosity and
maximize the grain size. After the experimental work they
have conclude that the pulse repetition rate was the most
significant factor in minimizing the interdendritic porosity
while the scanning speed played a vital role in increasing the
grain size. [6]
S. Shaji et al., have investigated the possibility of
using graphite as lubricating medium to reduce the heat
generated at the grinding zone in surface grinding. They
have studied the effect of parameters such as speed, feed, in
feed and mode of dressing on the performance
characteristics of surface finish and force developed. Factors
and their levels selected for the study is indicate in Table
3.Total nine experiments were carried out by using
Taguchi’s standard L9 orthogonal array design to find out
the effects of parameters on force developed and surface
quality. After the experimental work optimum condition has
been found out and they observed that the result obtains in
the conventional coolant grinding is in good agreements
with the results obtained graphite assisted grinding. It has
been observed that with the graphite application, the
tangential force and surface roughness are lower compare to
those in conventional grinding. [7]
D. Chakradhar et al., have investigated the effect
and parametric optimization of process parameters for
electrochemical machining of EN-31 steel. The process
parameters consider are electrolyte concentration, feed rate
and applied voltage and are optimize with considerations of
multiple performance characteristics including material
removal rate, over cut, cylindrical error and surface
roughness. They used Taguchi’s standard L9 orthogonal
array design for performing experiments. They performed
the ANOVA to get the contribution of each parameter on
the performance characteristics. After the experimental
works they found that the best combination of process
parameters are electrolyte concentration at 15%, feed at 32
mm/min and voltage at 20 V. From the results they have
conclude that the material removal rate can be maximize
and the over cut, cylindercity error and surface roughness
can be minimized through this method. [8]
V. CONCLUSION
From the above exhaustive literature review we can say that
optimization of SLM process parameters is necessary in
order to achieve higher quality of the parts. Taguchi
approach is a versatile tool for experimental design
optimization. Taguchi’s tool signal-to-noise ratio is most
important tool to find out highly significant factor to output
responses. There are different optimization methods but as
shown in above reviews researchers got better results with
Taguchi’s approach because of it can be provide systematic,
efficient and simplification of experimental plan with
minimum experiments so the time and cost are reduced
concerned with manufacturing.
REFERENCES
[1] Jianfeng Sun, Yongqiang Yang, Di Wang. Parametric
optimization of selective laser melting for forming
Ti6Al4V samples by Taguchi method; in Optics &
Laser Technology 49 (2013) 118-124.
[2] S. Dingal & T. R. Pradhan & J. K. Sarin Sundar & A.
Roy Choudhury & S. K. Roy. The application of
Taguchi‟s method in the experimental investigation of
the laser sintering process; in Int J Adv Manuf Technol
38 (2008) 904–914.
[3] F. Calignano & D. Manfredi & E. P. Ambrosio & L.
Iuliano & P. Fino. Influence of process parameters on
surface roughness of aluminum parts produced by
DMLS; Springer-Verlag London 2012.
[4] K. Abd-Elghany, D.L. Bourell. Property evaluation of
304L stainless steel fabricated by selective laser
melting; Rapid Prototyping Journal Vol.18 Iss: 5 (2012)
420-428.
[5] Ulas Caydas, Ahmet Hascalık. A Study On Surface
Roughness In Abrasive Water Jet Machining Process
Using Artiﬁcial Neural Networks And Regression
Analysis Method. Journal Of Materials Processing
Technology 202(2008) 574-582.

Process parameter optimization of SLM process and application of Taguchi approach– The Review
(IJSRD/Vol. 1/Issue 4/ 2013/0046)
[6] Anoop N.Samant, Sameerr.Paital, Narendrab.Dahotre.
Process Optimization in Laser Surface Structuring Of
Alumina. Journal Of Materials Processing Technology
203 (2008) 498-504.
[7] S.Shaji, V.Radhakrishnan. Analysis of Process
Parameters in Surface Grinding With Graphite As
Lubricant Based On the Taguchi Method. Journal Of
Materials Processing Technology 41(2003) 51-59.
[8] D.Chakradhar, A.Venu Gopal. Parametric Optimization
in Electro Chemical Machining of EN-31 Steel Based
on Grey Relation Approach (2011).Applied Mechanics
and Materials.110-116, 1649.

Process parameter optimization of SLM process and application of Taguchi approachâ€“ The Review

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Process parameter optimization of SLM process and application of Taguchi approachâ€“ The Review