tool wear prediction in drilling of gfrp laminates using neuro fuzzy

International Journal of Pure and Applied Mathematics
Volume 119 No. 7 2018, 2037-2055
ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version)
url: http://www.ijpam.eu
Special Issue
TOOL WEAR PREDICTION IN DRILLING OF GFRP LAMINATES
USING NEURO FUZZY MODELLING
Dr.P.Sengottuvel1, Dr.J.Hameed Hussain 2
1,2
Professor, 1Department of Mechatronics, 2Department of Mechanical
Email Id - dr.p.Sengottuvel@gmail.com, Deanengg@bharathuniv.ac.in,
BIST, BIHER, Bharath University, Chennai-73
Abstract
Recently the use of GFRP materials in engineering application has increased due to their
omni potential properties such as high strength to weight ratio and high specific stiffness. As
structural materials, fastening of GFRP structures cannot be avoided. The fastening efficiency
is largely dependent on the quality of machined holes. Due to the anisotropic and nonhomogenous structure of GFRP, there exist an extensive tool wear to the drill bit .The
excessive tool wear make the drilling process very expensive as only limited number of holes
can be drilled with one particular drill bit. High temperature, vibration and noise generated
during drilling were some of the factors responsible for tool wear during drilling various
GFRP laminates. Hence it is necessary to find out the optimized drilling condition which
minimizes the drill temperature, vibration and noise to minimize drill wear during drilling
GFRP laminates.
Mechanical properties of unidirectional laminates are very different from those random
laminates .Hence the study of directionality of the reinforcement has a significant effect
during drilling. The work presented here focuses on finding suitable drilling condition which
minimizes temperature, vibration and noise on GFRP laminates such as uni directional, bi
directional, woven and woven cross. Based on taguchi L16 Orthogonal Array, drilling
experiments were conducted on a CNC drilling machine for different type of GFRP
laminates. Input parameter used in the experiments for various drilling conditions were
spindle speed, feed and point angle.
A modelling algorithm, Adaptive Neuro Fuzzy Inference System (ANFIS) is used to find
flank wear in drilling process.
Keywords: Adaptive Neuro Fuzzy Inference System, Drill temperature, GFRP laminates,
Noise, Vibration.
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1 Introduction
GFRP’s are a very important engineering material. For composite matrix and reinforcement
systems, the reinforcement type and orientation will in most instances be the dominant
contributor to properties. Reinforcement forms for the various matrix systems are classified
as uni directional, bi directional, woven and woven cross.(1-8) In uni directional ,fiber
orientation in which all of the major fibres run in one direction whereas for bi-directional the
fiber run in two or more direction. Whereas woven fabrics are formed by interlacing two sets
of threads, the warp and the wept interlaced at right angles to create a single layer. The
fabrics integrity is maintained by the mechanical interlocking of fibers. woven reinforcement
are particularly useful for constructing shapes with double curvature since they can readily be
draped over quite complex formers, unlike uni directional prepegs which may wrinkle
because of their anisotropy. Woven cross fiber creates a little criss-cross pattern when all
those tiny fibers are actually woven together. (9-16)
Given the growing importance of GFRP’s in industry and manufacturing
much research has been conducted to understand the negative side effects of drilling GFRP’s
laminates. But this work has been done in a very fragmented manner, concentrating on
temperature, vibration and Noise during drilling process. Machining of laminate composite
depends on the direction of fiber and matrix and their effects on machining process.
Important requirement for thermoplastic matrices which are to be used in high performance
composite is thermal stability. Chemical decomposition brought on by elevated temperature
affect the mechanical and all other properties of the polymer matrix. Weinert et al. [1] studied
the effects of temperature on tool life during drilling FRPs in dry machining and wet
machining condition and found that tool temperature increases with increase in both cutting
speed and feed and tool wear is distinctively more in dry machining than in wet machining.(16-18)
According to Maninder Singh et al. [2] FRP composites have low thermal conductivity and
heat capacity. This affects the energy balance between the tool and workpiece ensuing in high
temperatures at the flank area of the drill bit. These thermal loads affect the machined
surface, cutting forces and tool life. (19-21)
Wilson et al. [3] have experimentally measured the temperature for uni directional and cross
ply laminates of carbon fiber reinforced plastic and analysed the properties in both
longitudinal and transverse direction. The behaviour of glass fiber and polyester in
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compression and also mechanical properties of CFRP uni directional laminates at low
temperature were studied by Dutia and schutz et al. [24,25] respectively. Both of them found
that the Strength and modulus of the composites increases with decreasing temperature.
Palanikumar et al. [26] studies on machining characteristics of glass fiber reinforced polymer
composites and found that increase in feed rate increased the heat generation and hence tool
wear, which resulted in the higher tool wear. The increase in feed rate also increase the
chatter and it produces incomplete machining at a faster traverse, which leads to more tool
wear and hence low feed rates are selected and is between 0.10 and 0.50 mm/rev.
According to Komanduri et al. [27] the high abrasiveness of GFRP fibres result in loss of
sharpness of cutting edges of the tool. This loss of sharpness affects the integrity of the holes
drilled, increases production costs, power consumption and the productivity of the drilling
tool. Blunt edges not only reduce the life of the tool but results in excessive chatter and poor
surface finishes including overheating of the tool and a requirement for more power and
thrust whilst drilling.
Amit Kumar Tanwer et al. [28] stated that in tensile as well as compression test unidirectional
oriented glass fiber composites have large value of all the properties such as Ultimate force,
yield force, compressive strength, tensile strength, elongation than bidirectional.
Vibration and Noise are found to be primarily dependent on fibre orientation and operating
conditions and tool geometry have less influence. Ramkumar et al. [29] stated that in
conventional drilling of GFRP, force fluctuation has been observed during drilling, since the
drill encounters two different materials, whereas in case of superimposed vibration, no such
severe fluctuation in force is observed. The severe force fluctuation observed in the case of
conventional drilling may be the cause for damage around the drilled holes. This damage
increases progressively with the increase in thrust force.
Ramulu et al. [30] stated that the cutting forces produced in the machining of
fiber
reinforced plastic are influenced by the orientation of the fiber. The tool which generates the
smaller force is expected to be more effective in cutting. The measured vibration signal was
related to the drilling parameters and the state of the tool. It has been reported by lee that only
force and acceleration signals in the feed direction are significant, signals in the other
directions not revealing any useful information. Arul et al. [31] stated that, the defects in the
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drilling of composites are due to thrust forces experienced by the work material. The
parametric influence on cutting force was experimentally evaluated.
Langella et al. [32] presented a mechanistic model for predicting thrust force and torque
when drilling composite materials which allows a focused approach to the description of the
most appropriate drill geometry and cutting parameters.
Rajpal singh et al. [33] predicted the effective thermal conductivity (ETC) using the volume
fraction and thermal conductivities of different fillers filled in polymer matrices.
Lim et al. [34] stated that vibratory system formed due to the effect of machining operation.
Vibrations are often unfavourable to the work piece, cutting tool and machine tool. Increase
in cutting forces often results in flank wear to the drill bit and work piece will be degraded.
Vikrant Gupta et al. [35] developed a modelling algorithm using ANFIS to predict the
effective thermal conductivity of different fibers in the polymer matrix.. Anastasios P et al.
[16] studied Adaptive neuro-fuzzy inference system in modelling fatigue life of
multidirectional composite laminates. Xu Lei et al. [36] used the dynamic mechanical
analysis and vibration test to reveal the dynamic behaviours of specimen. The effect of
woven structure was discussed and the resultant analysis was done.
It is eminent fact that high temperatures, vibration and noise formed during drilling laminates
are the cause of unsatisfactory cutting tool life. Therefore, the most suitable drilling
parameters have to be selected to minimize wear during drilling laminates. Studies about
various laminates are not discussed so far. So this study will be useful to find the influence of
temperature, vibration and noise on various laminates and to predict the optimized cutting
condition during drilling various laminates.
Drilling Temperature was measured with PFA Teflon-coated K type thermocouples with a
diameter of 115µm, vibration signal measured with accelerometer and noise measured with
microphone were the output parameter used for the investigation. Experiments were carried
out using 10mm diameter drill bit with various point angles 90° 120° 130° 140° to find out
the effect of flank wear of the drill bit on drilling various laminates.
The effect of tool wear on the various parameters has been analyzed by ANFIS. From the
observed results it was found that the predicted output tool wear is almost very close to the
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actual output obtained in the experimental work. ANFIS model is validated with minimum
error, less than 5% which is experimentally reasonable. ANFIS improves the system accuracy
and eliminates the limitation in statistical modelling. This research would have served its
purpose if it aids in minimizing drill wear and damages caused to various GFRP’s laminates
whilst drilling.
2 Experimental setup
The drilling test were carried out on Hass CNCMILL USA model CNC milling
machine
with maximum torque 104 Nm@12000 rpm, maximum power rating 20 HP.
Figure 1 represents the experimental setup.
Figure 1 CNC milling machine and measurement setup
2.1 Cutting tools
Four uncoated carbide drill bits with a diameter of 10mm were utilized in drilling
GFRP laminates. The dimensional properties of the drilling tool are as follows: tool overhang
47mm,point angle 90° 120° 130° 140°130˚ and Shank type is cylindrical. A total of 4
uncoated carbide drills were used and the performance of each drill bit was examined and
monitored for sixteen condition of various feed rate, spindle speed and point angle.
2.2 Specimen preparation
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In these experiments, the various GFRP laminates such are woven roving,
unidirectional, bidirectional and woven cross matrix specimen with dimensions 90 x 200 x 8
mm prepared through hand moulding technique and used as work piece. High strength EGlass Mat was used as reinforcement in epoxy resin with araldite as hardener and processed
to a room temperature for approx 3hrs to fabricate GFRP. The prepared laminates are an Eglass/epoxy with a fiber volume fraction of 50%with a young’s modulus of 35Gpa and a
tensile strength of 60Mpa. The various laminates used in this study for investigation was
shown in figure 2.
Uni directional
Bi directional
Woven
Woven cross
Figure 2 Different arrangement of GFRP orientation
2.3 Drilling test
An experiment was conducted on Hass CNC MILL USA Model computer numerical control
(CNC) milling machine (presented in figure 1) with a maximum torque of 104Nm at 1200
rpm,a maximum power rating of 20Hp,drill trials were conducted under four different cutting
conditions. The range of cutting condition for GFRP drilling was recommended by the ASM
machining data. They are listed in table 1. The orthogonal array selected was L16 (4 4). A
total of 16 experiments were carried out considering speed, feed, point angle and laminates
for drilling. Each experiment has been repeated for four times and the temperature, vibration,
noise were recorded for each experiment.
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Table 1 Four Levels of Testing the Experiment
Symbo
Factors
Level 1
Level 2
Level 3
Level 4
F
Feed(mm/min)
25
30
35
40
S
Speed(rpm)
250
500
750
1000
θ
Point angle(θ)
90
120
130
140
L
laminates
WC1
WOVEN2
BD3
UD4
l
2.4 Temperature Measurement
In this study, drill temperature was measured with PFA Teflon-coated K type thermocouples
with a diameter of 115 μm. The range of thermocouple is 0–500 °C, and its response time is
10 μs. OMB-PDQ 30 analog input expansion module with a sampling rate of 2MHZ is
connected with thermocouple output and interfaced with computer for investigation. The
thermocouple was fixed and positioned above the workpiece as shown in Figure 1.The
drilling temperature values are stored in laptop for further analyses.
2.5 Vibration measurement and Noise absorption
Vibration and noise during drilling the composite material were measured using Kistler
8636C50 piezo electric accelerometer and microphone. The accelerometer amplitude range
500g peak and frequency range 1 to 2000Hz and the microphone frequency range is
100~10000Hz, and minimum sensitivity to noise ratio 58dB. The data acquired from the
accelerometer mounted on the fixture are stored in laptop for further analyses using
DEWESOFT.
2.6 Flank wear measurement
Maximizing the tool life by drilling through optimum drilling condition was the ultimate
objective of the present work. Flank wear was produced by the friction between the GFRP
laminates and the end flanks of the tool. This wear type was measured by using profile
projector.
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3 Results and Discussion
The Experimental results of Temperature, Vibration and Noise of each sample are
shown in table 2.
Table 2 Temperature, Vibration and Noise absorption values for each Experiment
EX.
SPINDLE
FEED
POINT
LAMINAT
TEMPERA
VIBRATI NOISE
TOOL
NO
SPEED
RATE
ANGLE
ES
TURE (ºc)
ON
WEAR
(rpm)
(mm/
(degree)
(dBL)
(g)
(mm)
min)
1
250
25
90
WC
62.956
29.101
88.78
0.0592
2
250
30
120
WOVEN
57.098
35.977
83.31
0.0540
3
250
35
130
BD
63.773
29.671
80.97
0.0330
4
250
40
140
UD
48.205
25.642
78.92
0.0526
5
500
25
120
BD
52.541
25.739
76.13
0.0281
6
500
30
90
UD
55.442
27.729
80.69
0.0329
7
500
35
140
WC
51.995
27.125
85.17
0.033
8
500
40
130
WOVEN
49.032
29.698
80.38
0.0369
9
750
25
130
UD
44.139
23.155
70.52
0.0154
10
750
30
140
BD
52.463
25.451
72.44
0.0183
11
750
35
90
WOVEN
47.609
28.219
76.58
0.0330
12
750
40
120
WC
61.682
28.99
87.77
0.0366
13
1000
25
140
WOVEN
46.789
23.955
71.79
0.0214
14
1000
30
130
WC
51.531
25.132
78.12
0.0230
15
1000
35
120
UD
46.76
24.517
76.52
0.0370
16
1000
40
90
BD
55.75
26.138
78.16
0.0369
3.1 Experimental observation
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The experimental results of temperature, vibration and noise obtained during drilling various
GFRP laminates at different cutting condition are shown in table 2.
From the experiment we found that the minimum temperature for unidirectional composite
was 44.139°C where as for bi directional, woven and woven cross the minimum temperature
obtained was 52.463°C, 46.789°C and 51.531°C respectively. In the same way minimum
vibration for unidirectional composite was 23.155g whereas for bi directional, woven and
woven cross minimum vibration was 25.451g, 23.955g 25.132g respectively. Similarly
minimum noise obtained during drilling
uni directional GFRP laminates was 0.52dbl
whereas for bi directional, woven and woven cross the minimum noise obtained 72.44dbl,
71.79dbl and 78.12dbl. This shows that during drilling various laminates minimum
temperature, vibration and noise was obtained in uni directional laminates compared to other
laminates.
The influence of temperature on unidirectional composite was 79% whereas for bidirectional,
woven and woven cross was more than 80%.This shows the % influence of temperature was
less in unidirectional laminates compared to bidirectional, woven and woven cross. Similar
observation was found in vibration and noise.
The percentage of wear occurs in unidirectional composite is 29% whereas for bidirectional,
woven and woven cross was 49%, 39% and 33% respectively. This implies that wear
obtained during drilling unidirectional composite was less compared with other three
laminates (bidirectional, woven, woven cross).
Optimum cutting condition for minimizing Drill Temperature and vibration

The optimum cutting condition which minimizes the drill temperature and vibration
during drilling uni directional GFRP laminates is speed 750rpm, feed 25mm/min and
point angle 130°.

The optimum cutting condition for bi directional GFRP laminates is 750rpm, feed
30mm/min and point angle 140°.

Woven GFRP laminates the optimum cutting condition is 1000rpm,feed 25mm/min
and point angle 140°

Spindle speed 1000rpm, feed 30mm/min and point angle 130° was the optimum
cutting condition for woven cross GFRP laminates.
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Optimum cutting condition for minimizing noise

From the experiment we found that the optimum cutting condition which minimizes
the noise during drilling Uni directional GFRP laminates is spindle speed 250rpm,
feed 40mm/min and point angle 140°.

Similarly for bi directional GFRP laminates the optimum cutting condition was
spindle speed 250rpm, feed 35mm/min and point angle 130°.

The optimum cutting condition for woven GFRP laminates is spindle speed 250rpm,
feed 30mm/min and point angle 120°

For woven cross GFRP laminates the optimum cutting condition 250rpm, feed
25mm/min and point angle 90°.
3.2 Discussion
From above table 2 it was found that the minimum temperature, vibration and noise for
unidirectional composite was less when compared for woven, bidirectional and woven cross
This is due to the orientation of composite in one direction. Whereas for woven, bidirectional
and woven cross the orientations of fibers are in longitudinal and transverse direction. During
drilling this laminates, the interactions between the tool and fibers will be more. This
increases the temperature in woven, bidirectional and woven cross composites. The
temperature increase in woven cross is more when compared to woven due to the orientation
fibers at different angle.
Similarly it was found that vibration was more in woven, bidirectional and woven cross
composites compared to unidirectional composite .This is due to the twisting of the laminates
by the perpendicular arrangement of the warp and weft threads. From the literature we found
that the strength, stiffness &damping co-efficient of unidirectional composites was more
compared to other laminates. In general fibers in a one dimensional form are characterised by
flexibility, fineness and high ratio of length to thickness due to orientation of composite in
one direction. Continuous fibers have long aspect ratio and normally have preferred
orientation.
4 ANFIS modelling on tool wear
Adaptive Neuro-fuzzy inference system is a fuzzy inference system implemented in the
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framework of an adaptive neural network.
ANFIS is more powerful than the simple fuzzy logic algorithm and neural
networks. Since it provides a method for fuzzy modelling to learn information about the data
set, in order to compute the membership function parameters that best allow the associated
fuzzy inference system to track the given input/output data. The architecture of ANFIS for
flank wear is shown in Figure 3.
Figure 3
ANFIS Architecture
The seven inputs with one output and their final fuzzy membership functions are shown in
this figure 3. A total of 84 network nodes and 12 fuzzy rules were used to build the fuzzy
inference system.
A triangular – shaped membership functions were used to train ANFIS because it achieved
the lowest training error as shown in the training curve of Figure 4.Seven triangular-shaped
membership functions were used for inputs of spindle speed, feed rate, point angle, laminates,
temperature, vibration, noise. The input values are normalized by the mark signal and
submitted for ANFIS training.
4.1 ANFIS training error curve
ANFIS predictions of tool wear starts by obtaining the data set (input-output data pairs) for
training. The data set is used to find the initial premise parameters for the fuzzy membership
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functions by equally spacing each membership function. The values of the premise
parameters are fixed, so the overall predicted tool wear, can be expressed as a linear
combination of consequent parameters. Then, the output of ANFIS in Figure 4 shows the
predicted tool wear.
Figure 4 Trained output data for ANFIS
4.2 Validation of Neuro Fuzzy Model of Flank Wear
The wear testing on a new carbide drill bit with same specification is conducted. The flank
wear in every stages are noted. Then the obtained parameters are submitted for validation in
ANFIS as shown in table 3.Figure 5 shows the FIS model of ANFIS.
Each validation data point (spindle speed, feed rate, point angle, laminates,
temperature, vibration and noise) was fed into the system, and then the predicted tool wear
values were plotted with the actual experimental values of tool wear as shown in Figure 6.
This figure 6 shows that the predicted values are a close match to the actual ones.
No of Inputs : 7 (Exclude Machining time)
FIS : Mandani Sub clustering
Algorithm : Hybrid
Total number of Input Membership Functions: 84 (7 inputs X 12 each)
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Total number of Output Membership Functions: 12
Membership Function: Gaussian Membership Function
Figure 5 FIS MODEL
Figure 6 ANFIS Validation diagram
Table 3 Validation of results
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EX.N
SPINDLE
FEED RATE POINT
LAMINAT
TEMPERAT
VIBRATION
NOISE
Tool
O
SPEED
(mm/min)
ES
URE (ºc)
(g)
(dBL)
wear
(rpm)
ANGLE
(degree)
(mm)
1
250
40
140
4
48.205
23.955
70.52
0.0214
2
500
25
120
3
52.463
25.739
76.13
0.0281
3
750
40
120
1
61.682
28.99
87.77
0.043
4
1000
40
90
3
63.773
29.671
80.97
0.0369
Actual values measured from the Profilometer and the output of FIS is shown in Table 3.
To validate the experimental values, tool wear values was measured for arbitrary cutting
condition and validated with ANFIS modelling. It was found from the figure 6 percentage of
error within 5% for tool wear. Since the % error was very less ANFIS was best suitable for
modelling the evaluation of tool wear. The instrument errors in measurement system and
uncertainty of machining parameters produce uneven rate of change in tool wear. This may
be the reason for the error, which is experimentally reasonable.
5 Conclusions
Tool abrasion reduces their work life considerably. Blunted tools results in excessive power
consumption, increase in production costs, excessive noise whilst drilling and a compromise
in the integrity of the composite materials. In the present work a comparison of tool wear
characteristics on drilling various laminates were studied. Drilling experiment was conducted
by changing the spindle speed (rpm), feed rate (mm/min) and point angle (degree). The
ANFIS model developed for the validation of flank wear model is carried out with 5% error
which is experimentally reasonable, because of its complex nomenclature.
Based on the experimental results the following conclusion can be drawn from drilling of
various GFRP laminates.

The spindle speed should be in the range of 62% from the rated speed in order to
obtained minimum wear during drilling various GFRP laminates.
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The feed rate set should be in the range of 25-30mm/min and point angle must be in
the range of 130-140° to obtained less wear during drilling GFRP laminates.

The influence of temperature, vibration and noise in unidirectional composite was
very less compared to other laminates.

The percentage influence of temperature in unidirectional composite was 79%
whereas the percentage influence of vibration and noise was 86% and 87%
respectively. This shows the influence of vibration and noise was more in drill wear
when compared to temperature. Similar observation was found in bidirectional,
woven and woven cross.

The percentage of wear obtained during drilling unidirectional laminates was very
less compared to other laminates. This shows the significance of unidirectional
laminates over other laminates.

The investigation of drilling process has shown that unidirectional laminates was the
best suited laminates.

The statistical or analytical methods have certain limitations for non linear systems,
and for online application. The ANFIS solves the stated problems. The model
developed by neuro fuzzy system shows that the presented system can be used in real
time with minimum error.
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Reference
1. Hameed Hussain J., Anbazhgan G., Improve of the cop of vapour compression refrigeration
system by using thermoelectric cooler, International Journal of Pure and Applied
Mathematics, V-116, I-14 Special Issue, PP-585-589, 2017
2. Nakkeeran S., Hussain J.H., Innovative technique for running a petrol engine with diesel as a
fuel, International Journal of Pure and Applied Mathematics, V-116, I-18 Special Issue, PP-4144, 2017
3. Naveenchandran P., Vijayaragavan S.P., A sensor less control of SPM using fuzzy and ANFIS
technique, International Journal of Pure and Applied Mathematics, V-116, I-13 Special Issue,
PP-43-50, 2017
4. Hameed Hussain J., Nakkeeran S., Design and development of pepper plucking equipment,
International Journal of Pure and Applied Mathematics, V-116, I-14 Special Issue, PP-573576, 2017
5. Naveenchandran P., Vijayaragavan S.P., A high performance inverter fed energy efficient
cum compact microcontroller based power conditioned distributed photo voltaic system,
International Journal of Pure and Applied Mathematics, V-116, I-13 Special Issue, PP-165169, 2017
6. Golden Renjith Nimal R.J., Hussain J.H., Stress analysis of gear tooth using metal,
International Journal of Pure and Applied Mathematics, V-116, I-17 Special Issue, PP-317322, 2017
7. Hameed Hussain J., Hariharan R., Development of temperature-time and pressure-time
diagrams for diffusion bonding ti-aa7075 dissimilar materials, International Journal of Pure
and Applied Mathematics, V-116, I-14 Special Issue, PP-493-499, 2017
8. Udayakumar R., Khanaa V., Saravanan T., Saritha G., Cross layer optimization for wireless
network (WIMAX), Middle - East Journal of Scientific Research, V-16, I-12, PP-1786-1789,
2013
9. Khanaa V., Thooyamani K.P., Udayakumar R., Cognitive radio based network for ISM band
real time embedded system, Middle - East Journal of Scientific Research, V-16, I-12, PP-17981800, 2013
10. Khanaa V., Mohanta K., Saravanan T., Comparative study of uwb communications over fiber
using direct and external modulations, Indian Journal of Science and Technology, V-6, ISUPPL.6, PP-4845-4847, 2013
11. Kumarave A., Udayakumar R., Web portal visits patterns predicted by intuitionistic fuzzy
approach, Indian Journal of Science and Technology, V-6, I-SUPPL5, PP-4549-4553, 2013
12. Thooyamani K.P., Khanaa V., Udayakumar R., An integrated agent system for e-mail
coordination using jade, Indian Journal of Science and Technology, V-6, I-SUPPL.6, PP-47584761, 2013
13. Sengottuvel P., Satishkumar S., Dinakaran D., Optimization of multiple characteristics of EDM
parameters based on desirability approach and fuzzy modeling, Procedia Engineering, V-64,
PP-1069-1078, 2013
14. Udayakumar R., Khanaa V., Saravanan T., Synthesis and structural characterization of thin
films of sno2 prepared by spray pyrolysis technique, Indian Journal of Science and
Technology, V-6, I-SUPPL.6, PP-4754-4757, 2013
15. Udayakumar R., Kumarave A., Rangarajan K., Introducing an efficient programming paradigm
for object-oriented distributed systems, Indian Journal of Science and Technology, V-6, ISUPPL5, PP-4596-4603, 2013
2052
International Journal of Pure and Applied Mathematics
Special Issue
16. Kerana Hanirex D., Kaliyamurthie K.P., Multi-classification approach for detecting thyroid
attacks, International Journal of Pharma and Bio Sciences, V-4, I-3, PP-B1246-B1251, 2013
17. Udayakumar R., Khanaa V., Kaliyamurthie K.P., Performance analysis of resilient ftth
architecture with protection mechanism, Indian Journal of Science and Technology, V-6, ISUPPL.6, PP-4737-4741, 2013
18. Udayakumar R., Khanaa V., Kaliyamurthie K.P., Optical ring architecture performance
evaluation using ordinary receiver, Indian Journal of Science and Technology, V-6, I-SUPPL.6,
PP-4742-4747, 2013
19. Udayakumar R., Khanaa V., Saravanan T., Chromatic dispersion compensation in optical fiber
communication system and its simulation, Indian Journal of Science and Technology, V-6, ISUPPL.6, PP-4762-4766, 2013
20. Sundarraj M., Study of compact ventilator, Middle - East Journal of Scientific Research, V-16,
I-12, PP-1741-1743, 2013
21. Udayakumar R., Khanaa V., Saravanan T., Analysis of polarization mode dispersion in fibers
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