# A research on the effect of cutting parameters on cutting force in flat grinding using segmented grinding wheel

The article refers to the study of the influence of some process parameters including the
number of segment, depth of cut and feed rate to the cutting force when grinding the SKD11
steel by Taguchi methods and analysis of variance (ANOVA).
High accuracy and reliability (95 %) of the results of research using the Taguchi method
and analysis of variance with three parameters, three levels of impact, three trials

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Vietnam Journal of Science and Technology 55 (6) (2017) 793-802
DOI: 10.15625/2525-2518/55/6/8961
A RESEARCH ON THE EFFECT OF CUTTING PARAMETERS
ON CUTTING FORCE IN FLAT GRINDING USING SEGMENTED
GRINDING WHEEL
Nguyen Thi Phuong1, *, Nguyen Thi Phuong Giang2, Nguyen Tien Dong3
1General Department of Logistics – Ministry of Public Security, No 80 Tran Quoc Hoan Str.,
Cau Giay dist, Ha Noi
2, 3School of Mechanical Engineering, Hanoi University of science and Technology,
No 1 Dai Co Viet Str., Hai Ba Trung Dist., Ha Noi
*Email: phuongphucbao@gmail.com
Received: 5 December 2016; Accepted for publication: 25 August 2017
Abstract. This article represents the result of a research on the impact of cutting parameters
including the number of segments, cutting depth and feed rate on cutting force P in grinding
hardened steel SKD11 using segmented grinding wheel by Taguchi method and analysis of
variance (ANOVA). The result released the information of the relationship between the number
of segments, cutting depth and feed rate and its interactions with cutting force. Local optimal
value of cutting force can also be determined with minimal cutting force and low surface
roughness when machining the SKD11 harden steel using segmented grinding wheel.
Keywords: cutting force, Taguchi method, ANOVA, cutting depth, surface grinding.
1. INTRODUTION
Grinding force caused the elastic deformation of the technology system, vibration and
thermal in cutting areas. It is also used to determine the mode of grinding wheel wear. When
shear stress increases, the grinding wheel’s life reduces, reduced machining accuracy and
surface roughness increases. In particular, the immediate change of the shear is the main reason
causing the vibration of the wheel and other types of errors [1,2]. Julie Z. Zhang [3] and
Taranveer Singh [4] and colleagues used the Taguchi method to find the optimal process
parameters. Some authors in Vietnam, [5] and [6], studied the influence of some process
parameters, but using traditional methods, therefore it was a large number of experiments too.
There is no research of the influence of cutting parameters to cutting force in machining SKD11
harden steel using segmented grinding wheel. This paper presents the results of studying the
effects of grinding wheel segmented, depth of cut and feed rate to cutting force by Taguchi
methods and the analysis of variance (ANOVA) in order to minimize cutting forces.
2. OBJECT AND RESEARCH METHODOLOGY
2.1. Taguchi method [7]
Nguyen Thi Phuong, Nguyen Thi Phuong Giang, Nguyen Tien Dong
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Taguchi method is to determine the influence of some process parameters to the mean and
variance of the process performance characteristics and to figure out how well this process
works using the orthogonal matrix.
There are 3 input parameters with 3 levels, L9 matrix with 4 columns for 4 parameters (P1 -
P4). Therefore, the right column can be ignored. From that L9 orthogonal matrix is used to form
3 parameters and 3 levels as shown in Table 1.
The affecting level of cutting force is I = 3; the affecting parameters of cutting force is J =
3; the number of trials is K = 3; and the number of interation is L = 3.
Table 1. Orthogonal matrix according Taguchi L9 of 3 parameters and 3 levels.
Experiment P1 P2 P3 P4
1 1 1 1 1
2 1 2 2 2
3 1 3 3 3
4 2 1 2 3
5 2 2 3 1
6 2 3 1 2
7 3 1 3 2
8 3 2 1 3
9 3 3 2 1
where: P1 is feed rate, P2 - cutting depth, P3 - the number of segment;1, 2 and 3 - the low,
medium and high level of machine parameters, respectively.
In order to minimal cutting force we need to calculate the signal to noise ratio η S/N
−== ∑
=
u
i
iii y
n
NS
1
21log10/η (3)
where: n is the number of interation; and yi is cutting force value by each experiment.
2.2. Analysis of variance ANOVA [7]
Table 2. Parameters of Analysis of Variation.
Variation F Sum of squares
Calculation (SS)
Mean squares
(MS)
C%
(Test) Between Colums (C) J-1 SSc SC
Between Rows (R) K-1 SSR MSR
Between Layers (L) L-1 SSL MSL
Interaction C × R (J-1)(I-1) SSCR MSCR
Interaction C × L (J-1)(K-1) SSCL MSCL
Interaction R × L (I-1)(K-1) SSRL MSRL
Interaction
C × R × L
(J-1)(I-1)(k-1) SSCRL MSCRL
Sum of squares N-1 SST
A research on the effect of cutting parameters on cutting force in flat grinding using
795
Analysis of Variance is a statistical technique used to compare the average value of three or
more groups. The variance of a two-component observed is variance between groups and
groupitself variance.
To analyze the variance we should define some parameters as in Table 2.
3. EXPERIMENTAL SET UP AND RESULTS
3.1 Research Problem
The concerned problem was to minimize cutting forces by Taguchi method with cutting
parameters: number of segment slot Z, feed rate s and depth of cut t when machining SKD11
steel using flat surface grinding machine KENT. Experimental data were calculated following
ANOVA.
3.2. Selecting the value of technological parameters
3.2.1. Experimental conditions
The used grinding machine was KENT flat grinding machine, made in TAIWAN. The
wheel rotation was 1450 rpm.
Figure 1. KENT flat grinding machine.
Table 3. Specifications of the KENT flat grinding machine.
Parameter Length (mm) Width (mm) Height (mm)
1. Machine dimension 4,280 1,850 2,900
2. Pallet dimension 700 300
3. Journey of desk work 850 450 400
4. Capacity of main spindle motor: 4.5 kW
Grinding wheel: In this experiment three grinding wheels were used: 1 conventional and 2
inclined segmented grinding wheels with different the number of segmented. Properties of
Nguyen Thi Phuong, Nguyen Thi Phuong Giang, Nguyen Tien Dong
796
grinding wheels are shown in Table 4. All of wheels were made by Hai Duong grinding wheel
company.
Table 4. General parameter of grinding wheel.
Segmented slot’s width w: 10 (mm)
Segmented slot’s depth b: 15 (mm)
Segmented slot’s angle β: 15 (0C)
Grinding wheel
Number of tracks
Z
Angle between two slotted
continually α (0C)
Segment rate
η (%)
Grinding wheel 1 20 18 18.19
Grinding wheel 2 24 15 21.83
Grinding wheel 3 0 0 0
Figure 2. Geometry parameters of segmented grinding wheel.
The measurement was performed using Futek with 3 axis load cell. The accuracy was
, A/D converter and DasyLab software for signal processing were used to obtain the
data.
Figure 3a. Card A / D data acquisition. Figure 3b. Futek 3 axis load cell.
A research on the effect of cutting parameters on cutting force in flat grinding using
797
Figure 3c. Program shear 3D focre measurement.
Workpiece Material was SKD11 harden steel with hardness of 58-60 HRC. Workpiece has
same size of 70 × 30 × 25 mm. The properties of material are shown in Table 5.
Table 5. Composition of chemical elements in SKD11 steel.
Element C Mn Si Cr Va Mo Ni
Content, % 1.5 0.3 0.25 11.5 0.25 0.3 0.35
Figure 4. Screenshot of the workpiece used in the experiment.
3.2.2. Experiment
The experiment setup is shown in Fig. 5.
Nguyen Thi Phuong, Nguyen Thi Phuong Giang, Nguyen Tien Dong
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Figure 5a. Experiment set – up.
Figure 5b. Experiment when flat grinding.
The process parameters are selected depending on the equipment, cutting tools, machining
materials (Table 6).
Table 6. Value parameters in experiment technology.
Parameter Design parameters
Level
Low Medium High
Rate of feel s (m/min) P1 12 15 20
Depth of cut t (mm) P2 0.02 0.05 0.07
Segment grinding wheel P3 0 20 24
3.3. Experiment sampling using Taguchi method
3.3.1. Orthogonal matrix according to Taguchi
Experiment was set up as defined in Table 7.
Table 7. Orthogonal matrix according to Taguchi L9 of 3 parameters and 3 levels.
Experiment No. P1 (m/min) P2 (mm) P3 (Segment)
1 12 0.02 0
2 12 0.05 20
3 12 0.07 24
4 15 0.02 20
5 15 0.05 24
6 15 0.07 0
7 20 0.02 24
8 20 0.05 0
9 20 0.07 20
A research on the effect of cutting parameters on cutting force in flat grinding using
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3.3.2. Calculation results Taguchi experimental method
Table 8. Value of signal to noise ratio η = S/N.
Experiment P1 P2 P3 1P 2P 3P P iη
1 1 1 1 14.96 15.09 16.35 15.47 -23.79
2 1 2 2 19.26 18,15 17.25 18.22 -25.22
3 1 3 3 21.28 20.74 22.34 21.45 -26.63
4 2 1 2 10,09 9,2 8,98 9.42 -19.49
5 2 2 3 18.45 17.62 17.25 17.77 -24.99
6 2 3 1 22.14 21.59 21.06 21.60 -26.69
7 3 1 3 14.59 13.67 15.34 14.53 -23.26
8 3 2 1 19.86 18.62 17.98 18.82 -25.5
9 3 3 2 21.04 20.62 19.27 20.31 -26.16
From the above experiment we can calculate and have results in Table 9.
Table 9. ANOVA analysis of factors table for cutting power P (N).
Variation F SS MS C (%)
P1 2 68.04 34.02 23.04
P2 2 16.10 8.05 5.45
P3 2 62.28 31.14 21.09
P1 × P2 4 21.18 5.29 7.17
P1 × P3 4 60.64 15.16 20.53
P2 × P3 4 20.68 5.17 7
P1 × P2 × P3 8 46.35 43.23 15.72
Sum 80 295.27 - 100
3.4. ANOVA analysis
From the experimental results we calculated the variance and obtained the results as shown
in Table 9.
3.5. Results and Discussions
According to the results of signal to noise ratio η as shown in Table 8, we can see that in the
4th experiment the performance value of ratio η by the interference signal (S / N) is the smallest
then the impact of process parameters to cutting force is minimal.
Nguyen Thi Phuong, Nguyen Thi Phuong Giang, Nguyen Tien Dong
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From the mean value of process parameters (feed rate, cutting depth and the number of
segments) P1, P2, P3, we can see the cutting force P (obtained from the three components) and
performance "η" in Table 8. The Figures 6 a, b and c show the influence of the average value of
signal to noise ratio (S / N) under different feed rate, cutting depth and the number of segments
in machining SKD11steel.
From the graphs in Figs. 6a, 6b, 6c we can notice that the biggest impact on cutting force is
at level 1 when changing cutting depth, level 2 when changing feed rate and level 2 when
changing the number of segments. At these levels the value of cutting force is minimal and most
stable.
Figure 6a. The effect of signal to noise ratio to cutting force when changing the cutting depth by
SKD11 steel using inclined segmented grinding wheel.
Figure 6b. The effect of signal to noise ratio to cutting force when changing feed rate by S
KD11 steel using inclined segmented grinding wheel.
-27
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-25
-24
-23
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-21
-20
0
5
10
15
20
25
Level 1 Level 2 Level 3
Sig
n
al
to
n
oise
ratio
S/N
Th
e
a
v
er
a
ge
v
a
lu
e
o
f t
he
fo
rc
e
P(
N
)
The average value of the
force
The influence of the
average signal power to
noise ratio S/N
-25.5
-25
-24.5
-24
-23.5
-23
-22.5
14.5
15
15.5
16
16.5
17
17.5
18
18.5
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Level 1 Level 2 Level 3
Sig
n
al
to
n
oise
ratio
S/N
Th
e
a
v
er
a
ge
v
a
lu
e
o
f t
he
fo
rc
e
P(
N
)
The average value of
the force
The influence of the
average signal power to
noise ratio S/N
A research on the effect of cutting parameters on cutting force in flat grinding using
801
Figure 6c. The effect of signal to noise ratio to cutting force when changing the number of segments
by SKD11 steel using inclined segmented grinding wheel.
Discussion
By calculating the signal to noise ratio, from Table 8 it shows that the 4th experiment with
process parameters including the number of segments Z = 20; depth of cut t = 0.02 (mm) and of
feed rate s = 15 (m/min) gave the biggest value, i.e. η = - 19.49, meaning that the impact of this
experiment to cutting force is most stable.
Table 9 shows that, in the order feed rate of 23.04 %, the number of segment of 21.09 %
affects most to cutting force.
Compared to conventional grinding wheel, inclined segmented grinding wheel has more
stable and smaller cutting force in surface grinding. It can be explained that when using
conventional grinding wheel, the cutting process occurs continuously in the grinding surface,
chips will move reversely with the wheel’s velocity direction. These chips tend to gather in a
group with increasing size and take the space in the porosity of grinding wheel. Then there will
be no cutting edge in this zone. If chips can not move out of the cutting zone (the self sharpen
ability of grinding wheel), grinding wheel will become dull and lose its cutting ability. Then
cutting edges will be only slide process without cutting. It causes the increase in the tangential
cutting force of grinding process along with the increase of friction and thermal. It is a
disadvantage of conventional grinding wheel. With segmented grinding wheel because of the
space created by the slot, chip is easier to move out from the cutting zone, then there will be no
“dull” or “stick” in grinding process, therefore, the cutting ability will increase and also decrease
cutting force.
4. CONCLUSION
The article refers to the study of the influence of some process parameters including the
number of segment, depth of cut and feed rate to the cutting force when grinding the SKD11
steel by Taguchi methods and analysis of variance (ANOVA).
High accuracy and reliability (95 %) of the results of research using the Taguchi method
and analysis of variance with three parameters, three levels of impact, three trials and three
-25.5
-25
-24.5
-24
-23.5
-23
-22.5
14.5
15
15.5
16
16.5
17
17.5
18
18.5
19
Level 1 Level 2 Level 3
Sig
n
al
to
n
oise
ratio
S/N
Th
e
a
v
er
a
ge
v
a
lu
e
o
f t
he
fo
rc
e
P(
N
)
The average value of
the force
The influence of the
average signal power to
noise ratio S/N
Nguyen Thi Phuong, Nguyen Thi Phuong Giang, Nguyen Tien Dong
802
iterations of set points design, show the scientifically quantifiable impact of process parameter
to cutting force when machining SKD11 steel on KENT flat grinding machine.
For minimizing shear forces within the selected parameters of technology systems, the
local optimal values are shown as follows: number of segments to be Z = 20 (groove); depth of
cut to be t = 0.02 (mm); and feed rate to be s = 15 (m/min).
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and Technology Publishing House, Ha Noi, 2013 (in Vietnamese).
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3. Julie Z. Zhang, Joseph C. Chen, E. Daniel Kirby - Surface roughness optimization in an
end-milling operation using the Taguchi design method, Journal of Materials Processing
Technology 184 (2007) 233–239.
4. Taranveer Singh, Khushdeep Goyal, Parlad Kumar - To Study the Effect of Process
Parameters for Minimum Surface Roughness of Cylindrical Grinded AISI 1045 Steel,
Manufacturing Science and Technology 2 (2014) 56-61.
5. Nguyen Thi Phuong Giang, Banh Tien Long, Tran The Luc - The influence of the cutting
parametres in cylindrical grinding using highspeed grinding wheel produced by Hai
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Industry, ISSN 1859-3585 57 (2006) 28-31 (in Vietnamese).
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(2016) 37-40 (in Vietnamese).

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