International Journal of Engineering Trends and Technology (IJETT) – Volume 29 Number 2 - November 2015
A Review on Optimization of Cutting Parameters in Drilling
using Taguchi Method
Bhargab kalita
P.G. Student, Production & Industrial Engineering, Dept of ME, Jorhat Engineering College, Jorhat, Assam,
India
Abstract: The aim of this paper is to make a review
on Optimization of Cutting Parameters in Drilling
Using Taguchi Method to get minimum surface
roughness. The settings of the parameter were
determined by using Taguchi’s orthogonal array.
Analysis of variance (ANOVA), signal to noise
(S/N) ratio, regression analysis were employed to
find out the optimal value by studying the effects of
the cutting parameter.
Keywords — Taguchi method, Orthogonal array,
Anova, Signal to noise ratio, Regression analysis,
cutting parameters.
I. Introduction
Drilling is a machining process used to make hole
of circular cross section by using a drill bit. For
achieving good quality at low cost there is a strong
need of recognising the optimal cutting parameters.
Based on work piece material, tool material, tool
dimension and some other criteria, the cutting
parameters are selected for each process.
Parameters such as cutting speed, feed rate, depth
of cut, cutting fluid, tool diameter can affect every
process .For designing high quality systems
efficiently and effectively the Taguchi method is
very commonly used in process optimization.
1.1 Taguchi Method
Taguchi method is a very simple and effective
methodology to obtain robust design which is
minimally affected by variation. Taguchi method
gained popularity in engineering and science
community as the user can apply with limited
knowledge of statistics for obtaining good quality
at low cost. Taguchi uses signal to noise (S/N) ratio
and orthogonal array to achieve optimal condition
of the process parameter. S/N ratio is divided into
three groups i.e. 1) Smaller the better, 2) Larger the
better, 3) Nominal the best type.
Select the Taguchi Technique
Select signal and noise factors
Orthogonal array design
Find out optimal values
Analyze the data using
S/N ratio
Conduct the experiment
Confirmation test
Fig1: Taguchi’s method
1.2 Surface Roughness
ISSN: 2231-5381
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International Journal of Engineering Trends and Technology (IJETT) – Volume 29 Number 2 - November 2015
Surface Roughness is a measure of the surface
texture of a manufactured surface. It is the
fluctuation of the surface from a reference plane.
Low fluctuation from the reference line means low
roughness. Optimal settings of the cuttings
parameters are most important for obtaining low
surface roughness. Complete definition of a surface
includes Ra (Arithmetic Average Roughness), Rp
(Maximum Peak Height), Rv (Maximum Valley
Depth) and Rt (Maximum Peak-to-Valley
Roughness Height), Rz (average Rt over a given
length).
Fig2: General surface roughness curve
The above figure shows the roughness of the
machined surface. Average roughness value is
shown by mean line at every instantaneous point.
II. LITERATURE REVIEW
Yogendra Tyagi, Vedansh Chaturvedi, et al.
(2012) [1] investigated the effect of cutting
parameters spindle speed, feed rate and depth of cut
for maximizing material removal rate and
minimizing surface roughness in drilling mild steel.
Taguchi L9 orthogonal array is used. Results are
analyzed using Taguchi DOE software. They
concluded that spindle speeds affects most surface
roughness and feed rate largely affects Material
removal rate.
M Sundeep, M Sudhahar, et al. (2014) [2] have
done an experimental investigation on drilling of
Austenitic stainless Steel (AISI 316) using Taguchi
L9 array. Spindle seed, feed rate and drill diameter
was taken as process parameter. It was found that
spindle speed plays the most dominating role in
surface finish as well as Material removal rate in
drilling.
Kadam Shirish, M. G. Rathi (2013) [3] focused
on optimization of drilling parameters using the
Taguchi technique. L9 orthogonal array has been
used to drill on EN-24 steel blocks. Uncoated M32
HSS twist drill was used under dry condition.
Cutting speed, feed rate and depth of hole were
taken as process parameter. S/N ratio was
employed to get optimal control factors. They
ISSN: 2231-5381
found that cutting speed was the main significant
factors on surface roughness and the tool life.
Turgay Kıvak , Gurcan Samtas, et al. (2012) [4]
investigated the effect of cutting parameters cutting
tool, cutting speed and feed rate on drilling of AISI
316 stainless steel. Experiments were done in CNC
vertical machine using Taguchi L16 orthogonal
array. Coated and uncoated M35 HSS twist drill bit
were used under dry condition for this purpose.
Analysis of variance was done to draw the effects
of the control factors. It was found that cutting tool
was the most significant factor on surface
roughness and feed rate was the most significant
factor on thrust force.
Adem Çiçek, Turgay Kıvak, et al. (2012) [5]
investigated the effect of deep cryogenic and
cutting parameters on surface roughness as well as
roundness error in drilling of AISI 316 austenitic
stainless. Cutting tools, cutting speeds and feed rate
was taken as control factors. M35 twist drill bit
were used for doing the experiment. L8 orthogonal
array was used and multiple regression analysis
was performed to find out predictive equation of
surface roughness. A confirmation experiment has
showed Taguchi method precisely optimized the
drilling Parameters in drilling AISI 316 steel.
A. Navanth, T. Karthikeya Sharma (2013) [6]
focused on optimization of drilling parameter for
minimum surface roughness and hole diameter by
using Taguchi methodology. Al 2014 material and
HSS twist drill bit has been taken for performing
experiment. L18 orthogonal array has been used
and the result obtained were analyzed in MINITAB
16 .Analysis of variance (ANOVA) was used to
find out the optimal factors from cutting tool,
spindle speed and feed rate. Optimal values are
spindle speed 300 rpm, point angle and helix angle
1300/200 and feed rate .15 mm/rev for minimum
roughness.
J.Pradeep Kumar,
P.Packiaraj (2012) [7]
investigated the effect of cutting parameters such as
cutting speed, drill tool diameter feed and feed on
surface finish of OHNS material using HSS spiral
drill. L18 orthogonal array, S/N ratio, ANOVA and
Regression analysis has been employed to study the
effect of drilling parameters on surface roughness
value. Experimental data was analyzed using
MINITAB 13 and it was found that speed and feed
plays most dominating factors in surface
roughness, tool wear, material removal rate.
Reddy Sreenivasulu (2014) [8] focused on
optimization of surface roughness in drilling of Al
6061 using Taguchi design method and artificial
neural network method. Cutting speed, feed rate,
drill diameter, clearance angle and point angle were
taken as cutting parameters and HSS twist drill bit
as a tool. L27 orthogonal array, ANOVA, S/N ratio
were employed to study the effects of the control
factors. ANOVA analysis showed cutting speed,
feed rate, drill diameter, clearance angle and point
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International Journal of Engineering Trends and Technology (IJETT) – Volume 29 Number 2 - November 2015
angle all were significant on surface roughness.
The paper shows Optimal settings for roughness
are speed 800 rpm, feed rate .3 mm/rev , drill dia
10 mm, point angle 1180, clearance angle 40.
B.Shivapragash,
K.Chandrasekaran, et al.
(2013) [9] studied optimization of the process
parameters spindle speed, feed rate, depth of cut to
investigate their influence in drilling composite
Al-TiBr2. Taguchi method with grey relational
analysis were used to optimize the factors. L9
orthogonal array has been used and optimal settings
found for better surface finish were spindle speed
(1000 rpm), feed rate (1.5 mm/rev), depth of cut 6
mm.
Nalawade P.S. and Shinde S.S. (2015) [10]
optimizes the cutting parameters speed, depth of
cut, feed and type of tool to get better Surface
Finish and Hole Accuracy in dry Drilling of EN-31
material. Taguchi L9 orthogonal array , S/N ratio,
ANOVA, Regression analysis were done to find
out the optimal settings. Optimal settings for
surface roughness were Cutting speed (30 m /min),
feed (.2 mm/min), type of tool (HSS uncoated).
Sathish Rao U And Lewlyn .L.R. Rodrigues
(2014) [11] have made an attempt to study the
effect of spindle speed, feed rate, drill diameter,
fibre orientation on tool wear during drilling GFRP
components in dry condition. HSS drill bit was
used for the experiment. Taguchi L9 orthogonal
array has been used. S/N ratio, ANOVA, regression
analysis was used to find out the optimal settings. It
has been found that speed, feed rate , drill diameter
has significant effect on tool wear.
Nisha Tamta, R S Jadoun (2015) [12] analyzed
the effect of spindle speed, feed rate, drilling depth
on drilling Aluminium alloy 6082 with the help of
CNC machine. Taguchi L9 orthogonal array was
used to perform the experiment. Signal to noise
ratio (S/N), analysis of variance (ANOVA) were
used to analyze the effects drilling parameters on
surface roughness. For analyzing statistical
software MINITAB-15 has been used. It has been
found that spindle speed 3000 rpm, feed rate 15
mm/min, drilling depth 9 mm were the optimum
value. According to the paper drilling depth was
the most significant factor for surface roughness
followed by spindle speed.
Srinivasa Reddy, S. Suresh, et al. (2014) [13]
investigated the impact of cutting parameters such
as cutting speed, point angle and feed rate on
surface roughness in drilling of AL 6463 material.
HSS drill bit was used and the experiment was
done in CNC drilling machine using Taguchi L9
orthogonal array. Signal to noise ratio (S/N),
analysis of variance (ANOVA) has been employed
to find out the optimal drilling parameter. It was
found that Cutting speed, feed rate and point angle
plays significant role on surface roughness during
drilling operation of AL 6463 material.
Arshad Noor Siddiquee, Zahid A. Khan, et al.
(2014) [14] focused on optimizing drilling
parameters such as cutting fluid, speed, feed and
hole depth in drilling AISI 312 material.
Experiments were done in CNC lathe machine
using solid carbide cutting tool. Taguchi L18
orthogonal array has been used for the experiment.
Signal to noise ratio (S/N), analysis of variance
(ANOVA) were used to find out the effects of
cutting parameters on surface roughness. It has
been found that in presence of cutting fluid, speed
500 rpm, feed .04 mm/sec, hole depth 25 mm were
the optimum value for surface roughness. Anova
analysis showed that speed was the most significant
factor followed by cutting fluid, feed and hole
depth for surface roughness value.
Vishwajeet N. Rane, Ajinkya P.Edlabadkar, et
al. (2015) [15] focused in optimizing drilling
parameters such as cutting speed, feed and point
angle for resharpened HSS twist drill bit on
hardened boron steel using Taguchi method. L16
orthogonal array has been used to perform the
experiment in a double spindle drilling machine
.Analysis of variance was employed to find out
effects of control factors on surface roughness. It
was found that point angle was the main significant
factor for tool wear and feed rate for surface
roughness.
TABLE 1: SUMMERY OF LITERATURE SURVEY
Referenc
e No
1
Year
2
2014
2012
Author’s
Name
Yogendra
Tyagi,
Vedansh
Chaturvedi, et
al.
M Sundeep,
M Sudhahar,
et al.
ISSN: 2231-5381
Workpiece
Material
Mild steel
Input
Parameter
Spindle speed,
Feed rate,
Depth of cut
Method
used
Taguchi
Method
Output
Parameter
Surface
roughness ,
Material
removal rate
Most
Significant
Spindle speed,
Feed rate
AISI 316
Spindle seed,
Drill diameter,
Feed rate
Taguchi
Method
Surface
roughness ,
Material
removal rate,
Thrust force
Spindle speed
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International Journal of Engineering Trends and Technology (IJETT) – Volume 29 Number 2 - November 2015
3
2013
Kadam
Shirish, M. G.
Rathi
EN 24
Cutting speed,
Feed rate,
Depth of hole
Taguchi
Method
4
2012
Turgay Kıvak
, Gurcan
Samtas, et al
AISI 316
Cutting tool,
Cutting speed,
Feed rate
Taguchi
Method
5
2012
Adem Çiçek ,
Turgay Kıvak,
et al.
AISI 316
Taguchi
Method
6
2013
A. Navanth, T.
Karthikeya
Sharma
Al 2014
Cutting tools,
Cutting
speeds, Feed
rate
Cutting tools,
Spindle
speeds, Feed
rate
7
2012
J.Pradeep
Kumar,
P.Packiaraj
OHNS
Cutting speed,
feed, Drill tool
diameter
Taguchi
method
8
2014
Reddy
Sreenivasulu
Al 6061
Cutting speed,
Feed rate,
Drill diameter,
Point angle
and Clearance
angle
9
2013
B.Shivapragas
h,
K.Chandrasek
aran, et al
MMC Al-TiBr2
Spindle speed,
Feed rate,
Depth of cut
10
2015
EN-31
11
2014
Nalawade P.S.
and Shinde
S.S.
Sathish Rao
U, Lewlyn
.L.R.
Rodrigues
12
2015
Nisha Tamta1,
R S Jadoun
Aluminium
alloy 6082
13
2014
AL 6463
14
2014
15
2015
Srinivasa
Reddy, S.
Suresh, et al
Arshad Noor
Siddiquee,
Zahid A.
Khan, et al
Vishwajeet N.
Rane, Ajinkya
P.Edlabadkar,
et al
Speed, Depth
of cut, Feed,
Type of tool
Spindle speed,
Drill diameter,
Feed rate,
Fibre
orientation
Spindle speed,
Feed rate,
Drilling depth
Cutting speed,
Feed rate,
Point angle
Cutting fluid,
Speed, Feed,
Hole depth
Taguchi
design
method,
Artificial
neural
network
method.
Taguchi
method,
Grey
Relational
Analysis
Taguchi
Method
ISSN: 2231-5381
GFRP
AISI 312
Harden Boron
steel
Cutting speed,
Feed, Point
angle
Taguchi
Method
Surface
roughness,
Tool life,
Thrust force
Surface
roughness,
Thrust force.
Cutting Speed
Surface
roughness,
Roundness
error
Surface
roughness,
Hole diameter
Cutting speed,
Feed rate
Cutting tool,
Feed rate
Surface
roughness,
Tool wear,
Material
removal rate
Surface
roughness
Spindle
speeds(300 rpm
optimum), Feed
rate(.15 mm/rev
optimum)
Speed, Feed
Cutting speed,
Feed rate, Drill
diameter,
Surface finish
Spindle speed,
Feed rate
Surface
Finish, Hole
Accuracy
Tool wear
Speed, Feed,
Type Of Tool,
Drill Depth
Cutting speed,
Feed rate, Drill
diameter
Taguchi
method
Surface
roughness
Drilling depth,
Spindle speed
Taguchi
method
Surface
roughness
Taguchi
method
Surface
roughness
Spindle speed,
Feed rate, Point
angle
Speed, Cutting
fluid, Feed,
Hole depth
Taguchi
method
Tool life,
Surface
roughness
Taguchi
method
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Point angle,
Feed rate
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International Journal of Engineering Trends and Technology (IJETT) – Volume 29 Number 2 - November 2015
III. CONCLUSION
From the literature survey we observed that many
researchers took input parameters : cutting speed,
feed rate and depth of cut and few took input
parameter: Cutting fluid, drill tool diameter, cutting
tools, point angle, clearance angle, type of tool and
output parameters were taken : surface roughness,
material removal rate (MRR), Thrust force, tool
wear, Hole diameter, Hole Accuracy, Roundness
error. It is found that for surface roughness the
most significant parameters are speed, feed and
drill diameter, cutting fluids and least dominant
parameter is DOC.
International Journal of Engineering Research & Technology
(IJERT) Vol. 3 Issue 2, February – 2014 ISSN: 2278-0181.
[14] Arshad Noor Siddiquee, Zahid A. Khan, Pankul Goel,
Mukesh Kumar, Gaurav Agarwal, Noor Zaman Khan,
―Optimization of Deep Drilling Process Parameters of AISI 321
Steel using Taguchi Method‖, Available online at
www.sciencedirect.com,(2014).
[15]
Vishwajeet N. Rane, Prof.Ajinkya P.Edlabadkar,
Prof.Prashant D.Kamble
& Dr.Sharad S.Chaudhari,
―Optimization of process parameters for resharpened HSS drill
Using Taguchi Methods‖, International Journal On Engineering
Technology and Sciences – IJETSISSN (P): 2349-3968, ISSN
(O): 2349-3976 Volume 2 Issue 3, March – 2015.
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Sathish Rao U. and Dr. Lewlyn .L.R. Rodrigues,
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ISSN: 2231-5381
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