Taguchi optimization of surface roughness in the turning of Hastelloy C22 super alloy using cryogenically treated ceramic inserts

Abstract

Cryogenic treatment has been used in recent years to improve the performance of cutting tools. This study evaluated the machinability of a nickel–molybdenum-based super alloy using cryogenically treated (–80 ℃ and –145 ℃) ceramic inserts under dry turning conditions. Three cutting speeds (350, 400, and 450 m/min), three feed rates (0.1, 0.2, and 0.3 mm/rev), and a 1-mm fixed cutting depth were used in the turning tests. Experiments were conducted using the Taguchi orthogonal array L 27 design. The factors affecting the surface roughness (Ra) were determined via analysis of variance. The effect of cryogenic treatment type (shallow and deep), cutting speed, and feed rate on surface roughness was investigated. Results of the analysis determined that the feed rate was the major parameter that affected surface roughness and that the deep cryogenic treatment was more effective. The regression analysis confirmed that the experimental results and the predicted values were within the 95% confidence interval. The most effective parameter affecting the surface roughness was feed rate at a contribution of 57.9%. The contribution of the cutting tool type to the surface roughness was 28.5%. The results obtained showed that the surface roughness can be optimized for turning the Hastelloy c22 super alloy with the Taguchi method.

Full text

Original Article
Taguchi optimization of surface
roughness in the turning of Hastelloy
C22 super alloy using cryogenically
treated ceramic inserts
SıtkıAkinciog˘lu
1
, Hasan Go
¨kkaya
2
,Gu
¨l¸sah Akinciog˘lu
1
and Meltem A Karata¸s
3
Abstract
Cryogenic treatment has been used in recent years to improve the performance of cutting tools. This study evaluated the
machinability of a nickel–molybdenum-based super alloy using cryogenically treated (–80 C and –145 C) ceramic inserts
under dry turning conditions. Three cutting speeds (350, 400, and 450 m/min), three feed rates (0.1, 0.2, and 0.3 mm/rev),
and a 1-mm fixed cutting depth were used in the turning tests. Experiments were conducted using the Taguchi orthog-
onal array L
27
design. The factors affecting the surface roughness (Ra) were determined via analysis of variance.
The effect of cryogenic treatment type (shallow and deep), cutting speed, and feed rate on surface roughness was
investigated. Results of the analysis determined that the feed rate was the major parameter that affected surface
roughness and that the deep cryogenic treatment was more effective. The regression analysis confirmed that the
experimental results and the predicted values were within the 95% confidence interval. The most effective parameter
affecting the surface roughness was feed rate at a contribution of 57.9%. The contribution of the cutting tool type to the
surface roughness was 28.5%. The results obtained showed that the surface roughness can be optimized for turning the
Hastelloy c22 super alloy with the Taguchi method.
Keywords
Turning, ceramic tools, surface roughness, tool wear, Taguchi method
Date received: 9 February 2020; accepted: 17 March 2020
Introduction
Product quality is important in machining. The best
surface quality of a product is achieved by optimizing
the process parameters during machining. The devel-
opment of technology has enabled the production of
cutting tools with high cutting speeds. In recent years,
new industrial materials with outstanding features
have been developed. The difficult-to-machine charac-
teristic of such superior materials as the super alloys
makes it a challenge to obtain good workpiece surface
quality.
1
For this reason, it is important to select
the appropriate tools and parameters and to improve
the performance and efficiency of the existing cut-
ting tools for use on these high-quality materials.
A number of techniques are applied to boost cutting
tool performance. These include modifying the form
of the cutting tool, applying various coatings, and
cryogenically treating the tools. Cryogenic treatment
has many uses such as in hospital applications, prod-
uct stocking, cooling in machining, and as an
alternative to conventional heat treatment of engin-
eering materials.
2,3
When applied to cutting tools, the
cryogenic treatment known as subzero treatment is
acknowledged as a way to increase their wear resist-
ance. Wang et al.
4
examined the effects of cryogenic
cooling on turning using ceramic tools. Kara and
Takmaz
5
investigated the effect of the deep cryogenic
process on the coating and uncoated carbide tool
turning AISI O2 cold work tool steel. They concluded
that the cryogenic process had a positive effect on the
1
Department of Machine Design and Construction, Du¨zce University,
Du¨ zce, Turkey
2
Department of Machine Engineering, Karabu¨k University, Karabu¨k,
Turkey
3
Department of Machinery and Metal Technologies, Bolu Abant I
˙zzet
Baysal University, Bolu, Turkey
Corresponding author:
SıtkıAkinciog
˘lu, Department of Machine Design and Construction,
Du¨ zce University, Du¨ zce, Turkey.
Email: sitkiakincioglu@gmail.com
Proc IMechE Part C:
J Mechanical Engineering Science
2020, Vol. 234(19) 3826–3836
!IMechE 2020
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sagepub.com/journals-permissions
DOI: 10.1177/0954406220917708
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performance of carbide tools. He et al.
6
applied 30-h
deep cryogenic treatment to TiAlN-coated carbide
tools. In the experiments, they investigated the effect
of the turning performance on 40Cr steel and con-
cluded that the deep cryogenic treatment had reduced
the heat generated in the cutting tools, improved the
surface roughness of the workpiece, and reduced tool
wear. Studies investigating the effect of cryogenic treat-
ment on cutting tools are generally focused on High
Speed Steel (HSS), carbide, and coated carbide tools.
7,8
Kara et al.
9
applied cryogenic treatment to AISI D2
samples. He examined the processability properties of
the samples by turning the cryogenic-treated samples
with ceramic tools. Hardness was high in the deep
cryogenic sample. After the cryogenic process, the
hardness decreased with the tempering process but
more homogeneous microstructure was obtained
with the formation of fine carbide. However, the
effect of cryogenic treatment on ceramic cutting tools
has not been fully investigated. Improving the per-
formance of ceramic tools with superior features will
reduce expenses and save on the cost of the tools.
The nickel-based Hastelloy C22 alloy contains suf-
ficient amounts of Cr, Mo, Fe, and W and, unlike
most materials, is corrosion-resistant when exposed
to chlorine dioxide, hypochlorite, and hydrogen
chloride. This protective feature makes it suitable
for various marine and manufacturing applications.
10
Nickel-based super alloys are also the most difficult to
process. The nickel in the content of such materials
creates a heat-resistant structure causing high heat to
be generated in the cutting zone during processing.
This heat on the cutting tool quickly erodes the work-
piece surface quality. For this reason, the machinabil-
ity of such materials has become a prevalent research
topic and increasing the performance of the cutting
tools used for these difficult-to-process materials con-
stitutes an important issue. In order to determine the
machining performance of cutting tools, a great
number of experiments are required to improve the
reliability of the obtained results. However, increasing
the number of experiments increases the experimental
costs as well. Test costs increase due to the rapid fin-
ishing of the cutting tool life, especially when process-
ing nickel and other difficult-to-machine materials.
By using an optimization technique like the Taguchi
method, optimization of controllable variables can be
carried out with fewer performance tests. The Taguchi
method is used for optimization in many fields and
has an important place in the industrial sector. In
many studies, this method has been used to optimize
the performance of cutting tools and parameters
affecting surface roughness of the workpiece.
7,11,12
Asiltu
¨rk and Akkus¸
13
optimized the surface roughness
in AISI 4140 milling using the Taguchi method. The
model they developed demonstrated that it could be
used industrially to determine optimum cutting par-
ameters. Thamizhmanii et al.
14
successfully optimized
surface roughness in the turning of CM 440 alloy steel
via the Taguchi method. Many studies have shown that
surface roughness can be successfully optimized.
Determining the effect of deep and shallow cryogenic
treatment on ceramic tools can contribute significantly
to industrial applications. In addition, this will contrib-
ute to the workability of materials such as nickel-based
super alloys which instigate high tool consumption
during turning tests. With the Taguchi method, both
time and test costs can be saved.
This study investigated the performance of ceramic
tools as affected by cryogenic treatment (both shallow
and deep). Cryogenic treatment was applied to the
insert tools for the first time. A nickel-based super
alloy was used in the experiments and the effect of
cryogenic treatment on tool wear and surface rough-
ness of the workpiece was determined. The Taguchi
method was used to optimize the factors (cryogenic
treatment, cutting speed, and feed rate) affecting the
surface roughness. In addition, analysis of variance
(ANOVA) and regression analysis were applied for
the effect rates and reliability of the results.
Material and methods
Turning experiments
Turning operations were performed on a CNC turn-
ing machine (Johnford T35) with a maximum speed of
3500 r/min and a power of 10 kW (Figure 1). Three
cutting speeds (350, 400, and 450 m/min), three feed
rates (0.1, 0.2, and 0.3 mm/rev), and a 1-mm fixed
cutting depth were used in the turning tests.
Test material
In the experimental trials, ø82 400 mm-sized nickel-
based super alloy test specimens were used. Hastelloy
C22 is a nickel–chromium–molybdenum alloy with
extensive applications due to its excellent corrosion
resistance in an extensive variety of chemical media,
including sea water, chlorine, copper chloride, acetic
acid, acetic anhydride, and formic acid. Table 1
Figure 1. Experimental setup for turning tests.
Akinciog
˘lu et al. 3827

presents the physical properties and chemical compos-
ition of the experimental samples.
Cutting tools
The cutting experiments were conducted using cer-
amic cutting tools supplied from ISCAR in the turn-
ing of the nickel-based super alloy. Ceramic inserts,
specified according to ISO 1832, coded as SNGA
120408, with Al
2
O
3
þTiCN coating were used in the
experiments. The tool holder was selected according
to the ISO 5608 standard. The bevel angle of the
negative-angle cutting tools used in the turning oper-
ations was 90; therefore, a tool holder with a negative
(–) angle of inclination (6) was selected.
Cryogenic treatment
The ceramic cutting tools were subjected to shallow
and deep cryogenic treatment. The cryogenic treat-
ment applied to the tools is shown schematically in
Figure 2. In order to avoid micro cracking, the tools
were subjected to a programed process of gradual
cooling over a 6-h period to –80 C (for shallow cryo-
genic treatment) and –145 C (for deep cryogenic
treatment), held at these temperatures for 24 h, and
then gradually warmed over a 6-h period up to room
temperature. The tempering process was applied at
200 C in order to remove the stresses in the cutting
tools caused by cooling.
The effect of the cryogenic process applied to the
cutting tools on micro hardness was investigated
by performing micro hardness measurements on the
non-treated ceramic tools (UT), shallow cryogenically
treated ceramic tools (CT1), and deep cryogenically
treated ceramic tools (CT2). Measurement was car-
ried out using the Metkon Duroline-M model micro
hardness tester under 1000 g load for 10 s, the cutoff
length and evaluation length were fixed at 0.8 mm and
4 mm respectively. Values from 10 different regions of
the samples were averaged. The cryogenic processing
unit is given in Figure 3.
Surface roughness measurement
The MAHR M1 table-type perthometer was used to
determine the surface roughness after turning the
nickel-based workpieces. In order to minimize any
errors that may have arisen during measurement, the
surface roughness measurements (Ra) were taken from
four different locations for each parameter.
Tool wear measurement
Images were taken via scanning electron microscopy
in order to examine the type of tool wear according to
Table 1. Chemical composition and physical properties of nickel-based super alloy.
Chemical composition
Ni Cr Mo Fe W Other
58.2 21.28 12.94 4 2.87 0.71
Physical properties
Hardness
Rockwell B (HRB)
Yield strength
(MPa)
Tensile strength
(MPa)
Thermal conductivity
(W/m-K)
Elongation
(%)
93 358 765 10.1 70
Figure 3. Cryogenic treatment process unit.
Figure 2. Cryogenic treatment process.
3828 Proc IMechE Part C: J Mechanical Engineering Science 234(19)

the cryogenic process applied to the cutting tools used
in the experiments. The wear images of the cutting
tools were taken on the Quanta FEG 250 brand
FESEM device.
Electrical conductivity
The electrical conductivities of the cutting tools were
measured in order to determine the electrical conduct-
ivity of the cutting tools of shallow and deep cryo-
genic processes applied to ceramic cutting tools.
Electrical conductivity measurements were made on
the Alpha-A High Performance Frequency Analyzer
test device.
Taguchi design and experimental
optimization
Taguchi method and experimental design
Optimization methods are widely used in engineering
applications. With these methods, optimization can be
achieved using fewer experiments. The Taguchi
method is often used in machinability tests
7
as an
easy and efficient technique to identify optimum cut-
ting parameters for manufacturing.
12
In the Taguchi
method, the deviation between the experimental and
the estimated values is calculated by using a loss func-
tion, which is then converted to a signal/noise (S/N)
ratio. The S/N ratio analysis utilizes three quality char-
acteristics: ‘‘Smallest is best’’, ‘‘Nominal is best’’, and
‘‘Largest is best’’.
11
For example, for the surface rough-
ness, the lowest Ra value is desired. Therefore, in the
optimization of surface roughness, the ‘‘Smallest is
best’’ characteristic was selected. For this characteris-
tic, the calculation of the S/N ratio according to the
Taguchi method is given in equation (1)
S=N¼10 log 1
nX
n
i¼1
y2
i
! ð1Þ
Here, nrepresents the number of experimental
observations and y
i
the data observed at the ith experi-
ment. The Taguchi experimental design chosen for this
study was the L
27
orthogonal array (OA), which
enabled a significant reduction in the number of experi-
ments. The control parameters were: cutting tools (A),
cutting speed (B), and feed rate (C) (Table 2). Three
levels were considered for each process variable.
Standard deviation
The standard deviation indicates how much of the
data are close to the average. If the standard devi-
ation is low, the data are distributed near to the aver-
age. Conversely, if the standard deviation is high,
the data are distributed in locations far from the aver-
age. If all values are the same, the standard deviation
is zero. The standard deviation was calculated using
equation (2).
¼ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
1
N1X
N
i¼1
ðxixÞ2
v
u
u
tð2Þ
Here, is the standard deviation, Nis the number
of elements of the array, x
i
is the element xof the
array, xis the arithmetic mean of the numbers in
the series, and (x
i
–x)
2
is the difference of the element
from the mean, squared.
Results and discussion
Evaluation of experimental results
This section includes the evaluation of the surface
roughness values obtained by processing the nickel-
based super alloy with the cryogenically treated cer-
amic tools (Figure 4). 3D graphics were drawn using
Minitab 16 software.
When the surface roughness results obtained
with the ceramic tools were evaluated according to
the cutting speeds, improvements were observed in
the surface roughness. Due to the high crimp hardness
of the ceramic tools, they were able to process the
workpiece at high cutting speeds without reacting.
15
The heat generated at high cutting speeds facilitated
the cutting process by making the chips more fluid.
It can be said that due to their high level of red-
hardness and chemical stability, wear on the cutting
tools was reduced and surface roughness improved.
15
Due to these properties, lower surface roughness
values were obtained with ceramic tools as compared
to other tools such as carbide. The surface quality
decreased when the feed rate increased. These higher
roughness values can be explained by the greater
amount of vibration developed at higher feed rates
during machining.
8
The best surface roughness
values in the turning of the nickel-based super alloy
were obtained using the ceramic tools at a feed rate of
0.1 mm/rev.
Upon examining the surface roughness values
obtained with the cryogenically treated ceramic
tools, it was observed that the cryogenic treatment
had a positive effect on the surface roughness
Table 2. Cutting parameters and their levels.
Symbol Cutting parameter
Levels
123
A Cutting tools (Ct) UT CT1 CT2
B Cutting speed
(Vc-m/min)
350 400 450
C Feed rate (f-mm/rev) 0.1 0.2 0.3
UT: non-treated ceramic tools; CT1: shallow cryogenically treated cer-
amic tools; CT2: deep cryogenically treated ceramic tools.
Akinciog
˘lu et al. 3829

values. In addition to their superior properties,
ceramic cutting tools are also noted for their low ther-
mal conductivity.
7
The low thermal conductivity of
cutting tools allows most of the heat generated in
the processing of heat-resistant materials to be trans-
ferred to the cutting tools, thus increasing their wear.
Although ceramics have high-red hardness, wear
occurs as a result of heat that cannot be removed
from the tools due to their low thermal conductivity
during long processing times. The cryogenic treatment
increased the electrical and thermal conductivity of
the ceramic cutting tools. This finding corresponds
with studies in the literature.
16
As a result of the
improvements, better surface roughness was obtained
with the CT2 and CT1 tools. At a cutting speed
of 450 m/min and a feed rate of 0.1mm/rev, the sur-
face roughness values obtained with the UT, CT1,
and CT2 tools were determined, respectively, as
1.151 mm, 0.824 mm, and 0.369 mm. The surface rough-
ness values obtained with the CT2 tool were 211.9%
and 39.7% better than those of the UT and CT1 tools,
respectively.
After the cryogenic treatment was applied to
the ceramic (Al
2
O
3
–TiCN) tools, the result of
their increased electrical conductivity is shown in
Figure 5. The electrical conductivity of the CT2
tools was higher than the other tools. The shallow
cryogenic treatment applied to the ceramic tools
also contributed to their electrical conductivity.
However, this contribution was not as great as with
the deep cryogenic treatment. These results may have
been caused by changes in the microstructure of the
ceramic tools. The hardness values, measured after
the ceramic cutting tools were subjected to the shallow
and deep cryogenic processes, are given in Figure 6.
Due to the cryogenic treatment applied to the
tools, significant increases were achieved in the hard-
ness of the cutting tools. The hardness increases in the
cutting tools indicated a stronger microstructure
formed in the tools during cooling. The hardness
values of CT1 and CT2 samples increased 3.7% and
15.3%, respectively, compared to the UT sample.
A correlation between the hardness of the cutting
tools and wear resistance has been acknowledged.
17–19
The improved performance of the cutting tools in the
cutting forces and surface roughness may be attribu-
ted to the changes in hardness of the tools. Figure 7
shows wear images of the cutting tools in the turning
of the nickel-based super alloy using shallow and deep
cryogenically treated ceramic tools. An EDX analysis
of an abraded cutting tool can be seen in Figure 8.
The Al
2
O
3
coating on the ceramic tools gives them
high resistance to oxidation and the TiCN layer
increases the toughness and thermal conductivity of
the tool. It can be said that the cryogenic treatment
applied to these tools imparted high wear resistance at
high cutting speeds, which increased the wear resist-
ance of the cutting tools. The wear images of the UT
tools demonstrated that notch wear, built-up edge
(BUE), flank wear, and built-up layer (BUL) were
formed. The EDX analysis performed to determine
the elements on the wear image of the cutting tools
is given in Figure 9. The distribution of materials
Figure 4. Surface roughness obtained in experiments.
Figure 5. Electrical conductivity effect of cryogenic treatment
on ceramic tools (UT, CT1, and CT2).
UT: non-treated ceramic tools; CT1: shallow cryogenically
treated ceramic tools; CT2: deep cryogenically treated ceramic
tools.
3830 Proc IMechE Part C: J Mechanical Engineering Science 234(19)

adhering to the cutting tools depending on cryogenic
treatment also differed. More BUE and BUL formed
on the UT cutting tool. Similarly, notch wear and
flank wear occurred in the CT1 tool. However, less
notch wear was formed on this tool. The deep cryo-
genically treated CT2 tool showed less notch wear and
flank wear. During the processing of nickel-based
heat-resistant materials such as Hastelloy C22, with
the increase in thermal conductivity of the cutting
tools, the heat generated is removed more quickly at
the cutting edge of the tool.
19,20
The cryogenic treat-
ment applied to the ceramic tools reduced the wear on
the tools but could not prevent it.
According to the EDX analysis, nickel, chromium,
and molybdenum had adhered to the cutting tools.
In addition, BUL formation was noted on the surface
of the cutting tools. Abrasion occurred on the cutting
tools with the breakage of the chips that had adhered
to them.
21
More BUE and BUL formation was
observed in the UT tools. The chips that had
broken from the super alloy workpiece and adhered
to the cutting tool differed according to the type of
cryogenic treatment. The adhesive materials were
more rounded in the untreated tools, but appeared
to be thinned out in those with the deeper cryogenic
treatment. This demonstrated that the deep cryogenic
treatment led to a smoother structure on the surface
of the tool.
Figure 7. Wear images of UT, CT1, and CT2 tools at 0.3 mm/rev feed rate and 450 m/min cutting speed.
BUL: built-up layer; BUE: built-up edge.
Figure 6. Effect of the cryogenic treatment on the hardness
of the ceramic tools.
UT: non-treated ceramic tools; CT1: shallow cryogenically trea-
ted ceramic tools; CT2: deep cryogenically treated ceramic tools.
Akinciog
˘lu et al. 3831

S/N analysis
With standard deviation, we can determine how near
the data are to the average. A low standard deviation
means that the data are distributed near to the aver-
age. Conversely, a high standard deviation indicates
that the data are distributed in locations far from the
average. If all values are the same, the standard devi-
ation value is zero. Table 3 shows the experimental
results and estimation values according to the Taguchi
L
27
OA. Ra estimation values were obtained by
Taguchi modeling in Minitab 16 program. By giving
the value of each parameter, the forecast values in the
desired conditions were obtained.
The S/N response table (Table 4) was used to ana-
lyze the effect the control factors Ct, V, and f exerted
on the surface roughness (Ra). The optimum control
levels can be seen for the optimum surface roughness
values, according to the Taguchi approach. The Ra
control factor value levels, shown in Table 4, are pre-
sented graphically in Figure 10. These graphs enable
easy identification of the optimal processing param-
eters of the control factors for minimizing surface
roughness. The level of each control factor with the
highest S/N ratio was seen as the best level for that
control factor.
12
Thus, the levels and S/N ratios deter-
mined for the best Ra value for factors A, B, and C
were Level 3/S/N –1.044, Level 33/S/N 1.476, and
Figure 8. EDX analysis of abrasion on cutting tool.
Figure 9. Wear image and EDX analysis of the tools at 0.3mm/rev feed rate and 450 m/min cutting speed: (a) UT, (b) CT1, and
(c) CT2.
3832 Proc IMechE Part C: J Mechanical Engineering Science 234(19)

Level 11/S/N –3.362, respectively. This means that the
optimal Ra value was achieved using the deep cryo-
genically treated ceramic tool (CT2), at a cutting
speed of 450 m/min, and a feed rate of 0.1 mm/rev
(Figure 10).
ANOVA
The most effective parameter affecting surface rough-
ness was determined by ANOVA. The ANOVA
results are given in Table 5.
Table 3. S/N ratios of experimental and predicted results for surface roughness (Ra).
Trial
No.
Cutting parameter level
Experimental
Ra 1.147
(mm)
S/N
ratio
dB
Predicted
Ra
Ra (mm)
Predicted
Ra S/N
ratio
dB
Cutting
tools, Ct
Feed rate,
f (mm/rev)
Cutting speed,
Vc (m/min)
1 UT 0.1 350 1.633 –4.2597 2.108 –3.4304
2 UT 0.1 400 1.477 –3.3876 1.662 –1.8130
3 UT 0.1 450 1.151 –1.2215 1.316 –0.2001
4 UT 0.2 350 3.924 –11.8746 3.590 –12.2275
5 UT 0.2 400 2.917 –9.2987 3.144 –10.6102
6 UT 0.2 450 2.635 –8.4156 2.798 –8.9972
7 UT 0.3 350 4.863 –13.7381 4.137 –13.9921
8 UT 0.3 400 3.775 –11.5383 3.691 –12.3748
9 UT 0.3 450 3.417 –10.6729 3.345 –10.7618
10 CT1 0.1 350 1.251 –1.9451 1.363 –0.7816
11 CT1 0.1 400 0.984 0.1401 0.917 0.8358
12 CT1 0.1 450 0.824 1.6815 0.571 2.4487
13 CT1 0.2 350 2.826 –9.0234 2.845 –9.5787
14 CT1 0.2 400 2.621 –8.3693 2.399 –7.9614
15 CT1 0.2 450 1.944 –5.7739 2.052 –6.3484
16 CT1 0.3 350 3.233 –10.1921 3.392 –11.3433
17 CT1 0.3 400 3.083 –9.7795 2.946 –9.7260
18 CT1 0.3 450 2.319 –7.3060 2.600 –8.1130
19 CT2 0.1 350 0.486 6.2673 0.635 3.7927
20 CT2 0.1 400 0.429 7.3509 0.189 5.4100
21 CT2 0.1 450 0.369 8.6595 0.157 7.0230
22 CT2 0.2 350 2.162 –6.6971 2.117 –5.0044
23 CT2 0.2 400 1.604 –4.1041 1.671 –3.3871
24 CT2 0.2 450 1.308 –2.3322 1.325 –1.7741
25 CT2 0.3 350 2.475 –7.8715 2.664 –6.7691
26 CT2 0.3 400 1.948 –5.7918 2.218 –5.1517
27 CT2 0.3 450 1.754 –4.8806 1.872 –3.5388
UT: non-treated ceramic tools; CT1: shallow cryogenically treated ceramic tools; CT2: deep cryogenically treated
ceramic tools.
Table 4. Response table for means and S/N ratios.
Response table for means Signal/noise ratios
Level
A
(CT) B (Vc (m/min)) C (f (mm/rev)) A (CT)
B (Vc
(m/min))
C
(f (mm/rev))
1 2.8658 0.956 2.5392 –8.267 1.476 –6.593
2 2.1206 2.4379 2.0931 –5.619 –7.321 –4.975
3 1.3928 2.9852 1.7468 –1.044 –9.086 –3.362
Delta 1.473 2.0292 0.7924 7.223 10.562 3.23
Rank 2 1 3 2 1 3
Akinciog
˘lu et al. 3833

The ANOVA results for surface roughness
obtained with the ceramic tools revealed a significant
relationship between surface roughness and the cut-
ting tool, feed rate, and cutting speed, and with all
parameters at P<0.05. According to the ANOVA,
the most effective parameter affecting the surface
roughness was feed rate at a contribution of 57.9%.
The contribution of the cutting tool type to the sur-
face roughness was 28.5%.
22
This finding can be
attributed to the deep cryogenic treatment which, by
Figure 11. Comparison of experimental and estimated surface roughness results.
Figure 10. Mean and S/N ratios of surface roughness.
Table 5. ANOVA results for surface roughness.
Source DF Seq SS Adj SS Adj MS F P
Contribution
rate (%)
Cutting tools 2 9.7637 9.7637 4.8819 55.25 0.000 28.5
Cutting speed 2 2.8411 2.8411 1.4205 16.08 0.000 8.3
Feed rate 2 19.8405 19.8405 9.9203 112.26 0.000 57.9
Error 20 1.7673 1.7673 0.0884 – – 5.3
Total 26 34.2126 – – – – 100
S¼0.297264; R-Sq ¼94.83%; R-Sq (adj) ¼93.28%. Degrees of Freedom (DF), Sequential sum of squares (Seq SS). Adjusted sum
of squares (Adj SS), Adjusted mean squares (Adj MS).
3834 Proc IMechE Part C: J Mechanical Engineering Science 234(19)

reducing the wear on the ceramic tool, improved the
surface quality (Figure 7).
20
The experimental results and the values obtained
by the Taguchi method were similar (Figure 11). This
demonstrated that in the turning of the super alloy
with ceramic tools, experiments could be satisfactorily
designed using the Taguchi method.
Regression analysis of estimated surface roughness
Cubic regression analysis (Figure 12) was used to
evaluate the predictive values and experimental results
statistically. According to these findings, all predicted
values were within a 95% confidence interval.
Conclusion
This study applied the Taguchi method to determine
the optimal parameters in the turning of a nickel-
based super alloy using ceramic inserts under dry
turning conditions. The following conclusions may
be drawn:
The S/N ratios were determined for the optimal
control factor levels for minimal surface roughness.
The optimal conditions for surface roughness were
A
3
B
1
C
1
(i.e. cutting tool ¼deep cryogenically treated
ceramic tools, cutting speed ¼450 m/min, and feed
rate ¼0.1 mm/rev).
.Deep cryogenically treated tools were less worn
than untreated and shallow cryogenically treated
tools. Therefore, we recommend the application
of deep cryogenic treatment for ceramic tools.
.According to ANOVA, the parameter having the
greatest effect on the surface roughness was the feed
rate (57%), followed by the cutting tool (28.5%).
.The surface roughness values obtained with the
CT2 tool were 211.9% and 39.7% better than
those of the UT and CT1 tools, respectively.
.The hardness values of CT1 and CT2 samples
increased 3.7% and 15.3%, respectively, compared
to the UT sample.
.According to the cubic regression model, a high
correlation was found between the experimental
results and the predicted values.
.All these findings indicate that the Taguchi method
is a reliable technique for optimization of machin-
ing nickel-based super alloys. In the future, this
method can be applied in similar studies and in
the industrial sector.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with
respect to the research, authorship, and/or publication of
this article.
Funding
The author(s) disclosed receipt of the following financial
support for the research, authorship, and/or publication
of this article: This study was supported by the Scientific
Research Project Unit of Karabu
¨k University (KBU
¨-BAP-
13/2-DR-013).
ORCID iD
SıtkıAkinciog
˘lu https://orcid.org/0000-0003-4073-4837
Meltem A Karatas¸ https://orcid.org/0000-0002-1628-1316
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