What is Coordinate Measuring Machine? CMM Types, Features, Functions
Optimization of Abrasive Water Jet of Drilling
1. Sadhana
Optimization of AWJM drilling process parameters on onyx composite followed by
Additive Manufacturing
--Manuscript Draft--
Manuscript Number: SADH-D-22-00122R2
Full Title: Optimization of AWJM drilling process parameters on onyx composite followed by
Additive Manufacturing
Article Type: Original Articles
Keywords: Onyx composite; Abrasive water jet machining; delamination; Taguchi analysis;
surface roughness
Corresponding Author: Sachin Salunkhe
Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology
INDIA
Corresponding Author Secondary
Information:
Corresponding Author's Institution: Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology
Corresponding Author's Secondary
Institution:
First Author: Sachin Salunkhe
First Author Secondary Information:
Order of Authors: Sachin Salunkhe
G Dharmalingam
Deepak Panghal
Arun Prasad M
M. Sivakumar
N. Yuvaraj
Order of Authors Secondary Information:
Funding Information:
Abstract: Fiber-reinforced additive manufacturing components have been used in various
industrial applications in recent years, including aerospace, automobile, and
biomedical components. Compared to conventional manufacturing methods, additive
manufacturing methods result in lighter parts with superior mechanical properties,
lower setup costs and the ability to design more complex parts. The present article
focuses on delamination studies of onyx composites during composites machining
(drilling). However, the fabrication of onyx composites using the conventional method
resulted in delamination which is a significant issue during composites machining. The
fabrication of onyx composites via additive manufacturing with the Mark forged 3D-
composite printer was considered to address these shortcomings. Machinability tests
were conducted using abrasive water jet machining (AWJM) with various drilling
diameters, traverse speeds and abrasive mass flow rates. These parameters were
optimized using Taguchi analysis and then validated using the Genetic algorithm (GA)
and the Moth Flame Optimization algorithm (MFO). The surface morphology (Dmax)
and roughness of drilled holes were determined using a vision measuring machine with
2D software and a contact-type surface roughness tester. Confirmation testing
demonstrates that the predicted values are nearly identical to experimental standards.
It indicates, during the drilling of onyx polymer composite, regression models, genetic
algorithms and Moth-Flame Optimization algorithm were used to estimate the response
surface of delamination damage and surface roughness.
Response to Reviewers: Greetings,
The authors would like to thank the Editor for accepting this manuscript with minor
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2. modification based on the reviewer’s comments. Manuscript Ref.: Ms. No. SADH-D-
22-00122R1 and Titled “Optimization of AWJM drilling process parameters on onyx
composite followed by Additive Manufacturing”.
Based on the comments received from Editor, we have addressed the reviewer’s
comments with the appropriate heading. The revised manuscript is also attached for
your kind perusal.
Appendix 1 – Reviewer #2 comments with response
Appendix 2 – Reviewer #3 comments with response
Similarly the corrected section was highlighted in red colour within the revised
manuscript.
Thanking You
Yours Sincerely
(Dr. Sachin Salunkhe)
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3. Optimization of AWJM drilling process parameters on onyx composite followed by
Additive Manufacturing
Dharmalingam G1, Sachin Salunkhe1*, Deepak Panghal2, Arun Prasad M1, M. Sivakumar1,
N. Yuvaraj1
1
Department of Mechanical Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D
Institute of Science and Technology, Avadi, Chennai-600 062, Tamil Nadu, India;
2
National Institute of Fashion Technology, New Delhi-11016.
1*
Corresponding author email id: drsalunkhesachin@veltech.edu.in
Abstract: Fiber-reinforced additive manufacturing components have been used in
various industrial applications in recent years, including aerospace, automobile, and biomedical
components. Compared to conventional manufacturing methods, additive manufacturing
methods result in lighter parts with superior mechanical properties, lower setup costs and the
ability to design more complex parts. The present article focuses on delamination studies of onyx
composites during composites machining (drilling). However, the fabrication of onyx composites
using the conventional method resulted in delamination which is a significant issue during
composites machining. The fabrication of onyx composites via additive manufacturing with the
Mark forged 3D-composite printer was considered to address these shortcomings. Machinability
tests were conducted using abrasive water jet machining (AWJM) with various drilling
diameters, traverse speeds and abrasive mass flow rates. These parameters were optimized using
Taguchi analysis and then validated using the Genetic algorithm (GA) and the Moth Flame
Optimization algorithm (MFO). The surface morphology (Dmax) and roughness of drilled holes
were determined using a vision measuring machine with 2D software and a contact-type surface
roughness tester. Confirmation testing demonstrates that the predicted values are nearly identical
to experimental standards. It indicates, during the drilling of onyx polymer composite, regression
models, genetic algorithms and Moth-Flame Optimization algorithm were used to estimate the
response surface of delamination damage and surface roughness.
Keywords: Onyx composite, Abrasive water jet machining, delamination, Taguchi analysis,
surface roughness.
Click here to access/download;Manuscript;Revised manuscript
sadhana_AM [dharmalingam et al]_Revised 1.doc
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4. 1. Introduction
Composites reinforced with onyx have a high degree of strength, stiffness, fatigue strength,
corrosion resistance, wear resistance and lightweight. Onyx reinforced polymer composites have
many industrial structural applications, including aerospace, valves and fittings; robot grippers,
tools, battery cell holders, cargo and passenger doors; Jigs and fixtures; wind turbine blades,
automotive, prototype parts and civil structures reported by Fernandes et al., and He, Q et al. [1,
2]. Compared to other manufacturing methods, additive manufacturing enables the 3D printing
of complex structure that is lightweight, cost-effective, reduction in fuel consumption due to
improved geometrical structures, has short lead times, and minimizes material waste. Fused
deposition modeling which is one of the kinds of 3D printing technique was used to fabricate the
composite material using Mark forged – Mark Two Desktop 3D printer. The Markforged 3D
printers achieves greater stiffness, durability, reliability, consistent results, and unique strength
reported by Sanei et al. and Caminero, M., et al. [3-5]. Figure 1 illustrates the various
manufacturing processes used to create 3D printers.
Figure 1. The manufacturing process of 3D printed fiber-reinforced polymer composite [3] .
The fabricated polymer composite materials require sequentially machining operations to
accomplish dimensional tolerances and assembly. During the machining of the composite
materials, inner layers are exposed to damages related to delamination. Occurrence of
delamination is based on the machining process parameters and the drilling geometry. The
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5. machining of polymer matrix composites is the most significant and challenging drilling of
composites in the current scenario. The failure modes were observed in the polymer composite
materials, such as intralaminar matrix cracking, fiber fracture, fiber-matrix debonding, fiber pull
in and out; delamination and longitudinal matrix splitting during the machining process because
of localized impact loads. Abrao et al. Benardos et al. and Rubio et al.[6-8] stated that severe
delamination and higher surface roughness values were observed during the drilling of the fiber-
reinforced composite plastics and it affected them significantly. Tan et al. [9] stated that
significant contribution of machining process parameters was optimized through statistical
analysis followed by the Taguchi method for controlling the delamination damage and surface
roughness.
The conventional machining process such as sawing, milling, and drilling is used to make holes,
profiles and trim the polymer matrix composite materials as well as metal matrix composites
reported by Masoud et al.[10]. In the conventional machining of the polymer matrix composite
materials, one of the significant disadvantages observed were poor surface quality because of
diversification of the composite materials. During the conventional machining process, the
cutting tool produces the shear force because delamination occurs when drilling composite
materials such as carbon and glass fibers as reported by Abdullah et al. and Solati et al. [11, 12].
Hejjaji et al. [13]; Rao et al. [14] stated that the laser drilling as an alternate to conventional
drilling methods due to the absence of tool wear, vibrations and thrust force. Since the process of
drilling hole using laser results in ablation of composite due to thermal effects. Therefore,
optimization of process parameter is an important aspect which determines the quality of a
drilled hole.
Yallew et al. [15] reported the surface quality based on the cutting tool geometry during the
machining of the fiber-based composite materials. Celik et al.[16] concluded that the
conventional machining process parameters significantly affect the fiber-reinforced polymer
composite materials through surface damage and delamination factor. Making a hole in 3D
printed parts is possible using 3D printing machine. But near net shaped 3D printed parts which
process good quality hole considering a good surface roughness is difficult task and moreover to
obtain accurate dimensions of hole is a daunting task. Osama et al.[17] and Akhilesh et al.[18]
reported that 3D printed parts have poor surface roughness, dimensional inaccuracy and warping.
Because of that the present study is focused primarily on AWJM.
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6. Jesthi et al. [19]AWJM (Abrasive water jet machining) is a flexible process for achieving high
productivity for higher material removal rates. Compared to conventional machining, the AWJM
process produces low cutting forces and generates a low-temperature range. Because of this
AWJM process shows great interest during machining, reducing the probability of defects or
deterioration in the polymer matrix composite materials. Banon et al. [20] stated that AWJM
process has no involvement of physical tools and significantly more minor wear on auxiliary
components were noticed with reduced process cost. Ramesha and Akhtar [21] stated that these
machining issues can be resolved through AWJM method, which is ten times more rapid than
conventional machining route. Prabu et al. [22] concluded that AWJM drilling process is
completely free from cutting tool, chip generation, plastic delamination and thrust force (TF).
Ming et al.[23] investigated the surface quality of glass fiber and carbon fiber reinforced with
epoxy matrix machined through the AWJM process. It was concluded that based on the ANOVA
(analysis of variance) statistical analysis indicates, abrasive mass flow rate, higher hydraulic
pressure and low transverse speed is major influencing factor for determining the surface quality
of hybrid polymer composite materials. Jagadeesh et al. [24]. Seyedali et al. [25, 26] have
studied; the statistical results were benchmarked based on algorithms such as GA and MFO to
provide very much optimized competitive results. James et al. [27] identified the optimum
machining parameters for metals and composites via the DOE (design of experiments) followed
by ANOVA.
Based on the available literature review, it was found that the AWJ machining of onyx polymer
composite has not been reported. It is challenging to minimize the delamination defects and
lower surface roughness in the fiber-reinforced polymer composite materials followed by the
conventional machining process. In order to overcome these drawbacks, the unconventional
machining process AWJM was used to minimize these defects. In the present work, selecting the
appropriate machining process parameters for onyx polymer composite such as traverse speed
rate (mm/min), drilling diameter (mm) and abrasive mass flow rate (g/min) through Taguchi
analysis and optimization algorithms (GA &MFO) was performed to minimize the delamination
and lower surface roughness of the present study.
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7. 2.0 Materials and methods
The current study is to optimize the AWJM process parameters on the probability of process
quality such as delamination and surface roughness, on onyx polymer composite. The onyx,
which is a mixture of nylon with continuous carbon fibre and plastic filament is fabricated using
Markforged (USA) Mark Two Desktop composite 3D printers, as shown in Figures 2(a) and (b),
and is printed through fusion deposition modeling technique. The onyx is modeled using
computer-aided design (CAD) solid works software version 18.0, as illustrated in Figure 2. (c).
The onyx printing parameters were set to 100 layers with solid fill pattern, were each layer
thickness of 0.1mm is maintained and the infill density is set to 100 percent. The dimensions of
printed onyx as shown in Figure 2 (d) are 100mm x100mm x10mm. The hardness of the onyx
was measured using a durometer shore D hardness as per ASTM D 2240 standard. The hardness
value of 68 shore D was obtained.
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8. Figure 2. Printing of Onyx fiber Markforged Mark Two Desktop composite 3D printers -
Experimental setup (a) Front view (b) Top view (c) onyx CAD model (d) printed
onyx.
Machinability (drilling) of onyx polymer composite using AWJM is shown in Figure 3. The
AWJM has a travel capacity of 3500mm on the X-axis and 1500mm on the Y-axis. Table 1
shows the constant condition parameters used during the AWJ machining experiments Yuvaraj et
al.& Dhakal et al.[28, 29].
Table 1: Constant parameters used for AWJM process
S.No Parameters Conditions Units
1 Abrasive Water jet pressure 380 MPa
2 Standoff distance 2 mm
3 Abrasive material GARNET -
4 Abrasive particle size 80 mesh size
5 Impact angle 90 Degree (°)
6 Nozzle diameter 1 mm
7 Material & thickness Onyx & 10 mm
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9. Figure 3. Experimental setup of AWJM for drilling of onyx composite
2.1 Design of experiments (DOE) and Optimization Techniques
The Taguchi analysis was used to minimize production time, cost savings, materials and several
experiments. In the research experimentation, the Taguchi methodology was combined with
experimental design theory and the quality loss function. Taguchi's design of experiments (DOE)
followed by the L9 orthogonal array were reported by Sesharao et al., Chohan et al., Sakthi et al.
Kus et al. [30-33] is carried in the current machinability study of onyx, where the controllable
parameters were drilling diameter, traverse speed rate, and abrasive mass flow rate. Table 2
shows each of these controllable factors and their levels. The experimental results, such as the
delamination factor at hole entry and exit and the surface roughness were examined using the
S/N ratio (signal to noise ratio), with the smaller being better. The 'Signal' term denotes preferred
responses, while the 'Noise' term denotes undesirable values resulting from uncontrollable
factors. The signal to noise ratio as per equation (1) is used to calculate the smaller is better and
is shown below [34, 35]. In equation (1), 'n' represents the replication number and 'y' represents
the observed response value.
= - 10 2
) ----------------------------------------- (1)
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10. The optimum quality drilling process parameters were determined in this study using the S/N
ratio through graph data and response table. Furthermore, the ANOVA yielded an estimate of the
response parameter's contribution percentage (PC). The regression model was developed to
ascertain the relationship between process parameters and output (response) parameters. Figures
4 and 5 show the response parameters regarding delamination of peeling up at hole entry and
pushing out at hole exit. Surface roughness measured with a vision measuring machine (VMM)
2D software (MITUTOYO), a contact-type surface roughness tester. Persuasion damage about
the delamination factor was measured during onyx composite (Fd) drilling. The delamination
damage has been pragmatic on both sides of the onyx composite, which is at jet entry and exit.
The delamination factor was calculated using the standard formulae (Fd = Dmax/Do) as reported
by Vigneshwaran et al.[36]. Where Dmax is maximum diameter of the delaminated area and the
Do is nominal diameter or actual diameter of the drilled hole. The Dmax is calculated for Peel up
at hole entry and Push out at hole exit using vision measuring machine (VMM) followed by 2D
software (MITUTOYO) three point method. Each reading was repeated ten times and finally
noted the average value [37]. In the current study, Minitab '17' software was used to analyze
process parameters such as traverse speed rate (mm/min), drilling diameter (mm) and abrasive
mass flow rate (g/min). Each experimental value was taken ten times in the current study, and the
mean value was recorded. To analyze the best possible solutions for the machining process
parameters of the onyx composite, optimization techniques such as the Moth-Flame
Optimization algorithm (MFO) and genetic algorithm (GA) were used. The algorithms used a list
of parameters, as shown in Table 3. These input parameters were selected based on the literature
survey, for the GA and MFO algorithm, Geetha et al.[38] , Lenin et al. [39], Yang et al. [40],
Chohan et al.[31] , Antil et al. [26], Nadimi et al. [41], Shehab et al.[42] , Mirjalili et al.[25] , and
Buch et al.[43].
Table 2: Design of control factors and levels for Taguchi Analysis
Level Factors
Drilling diameter (mm) Traverse speed rate (mm/min) Abrasive mass flow rate
(g/min)
I 8 30 250
II 10 40 350
III 12 50 450
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12. Table 3: List of Parameters involved in Algorithms
Algorithms Parameters Values
GA
Population size 100
Stopping criteria – Maximum number of
iterations
100
Selection for reproduction Roulette wheel selection
Cross over probability 0.45
Cross over method Single point
Mutation probability 0.02
MFO
Maximum number of moth 100
Stopping criteria – Maximum number of
iterations
100
Adaptive number of flames round((mf-(itr*(mf-
1)/max_itr)))
Adaptive convergence constant (r) -1 to -2
Next position of moth close to flame (t) r to 1
3.0 Results and discussion
3.1 Delamination factor on onyx composite
Machinability studies (drilling) of the onyx composite were carried out using AWJM to assess
the impact of machining process parameters on workpiece damage. Figure 6 shows the
maximum damage drilled hole diameter (Dmax) measured with profile projector vision measuring
machine through 2D software. Table 4 shows the effect of machining process parameters on the
delamination factor for peel up at hole entry and push out at hole way out. It can be seen that as
the abrasive mass flow rate increases, the delamination factor value decreases for both the peel
up at the hole entry and the push out at hole exit. The study found that the lower the traverse
speed rate, the lower will be the delamination factor value.
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13. Table 4: Design of L9 orthogonal array used for Taguchi Analysis and measured values for
delamination peel up at hole entry and push out at hole way out
Figure 6. Measurement of maximum damage drilled hole diameter (Dmax)
No of experimental
drilling hole ID Delamination factor
Machining Process parameters
Peel up at
hole entry
Push out at
hole exit
Drilling diameter (mm) Traverse
speed rate
(mm/min)
Abrasive
mass
flow rate
(g/min)
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1.28100
1.34430
1.36077
0.96840
1.05180
1.43780
0.69600
1.07190
1.15530
0.9976
0.9402
0.9128
0.7816
0.7542
1.1120
0.6856
0.9434
0.9160
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14. Figure 7. Response graph of S/N for delamination peel up at hole entry
As shown in Table 4, the delamination aspect ranged from 0.69600 to 1.43780 for peel up at hole
entry delamination and from 0.6856 to 1.1120 for push out at hole exit delamination. These
delamination factor values are lower than those reported by several other researchers in previous
studies of conventional drilling of GFRP and CFRP composites [9, 24, 37, 44]. The Taguchi
statistical analysis was performed using the Signal to Noise Ratios (S/N) when Smaller is better
based on equation (1) characteristics for the observed response value, as shown in Tables 5 and 6
delamination’s peel up and push out. The delta values when varying the machining process
parameters from level 1, level 2 and level 3 were defined by the rank columns. The greater the
delta value, the greater the influence on delamination damage from levels 1 to 3. Based on the
grade result shown in Table 5, it is clear that the drilling diameter significantly influences the
delamination damage (peel up) approximately the hole diameter, followed by the traverse speed
rate and the abrasive mass flow rate. The abrasive mass flow rate appears to be the most
influential factor in delamination, as evidenced by the rank results shown in Table 6 from level 1
to level 3, followed by the traverse speed rate and the drilling diameter. In addition, the response
graphs for the delamination factor are shown in Figures 7 and 8 (peel up and push out). The
drilling diameter (12mm), traverse speed rate (30mm/min), and abrasive mass flow rate (450
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15. g/min) were found to be the most desirable drilling process parameters for minimizing
delamination factor peel up and push out. This study concluded that the suggested machining
process parameters of a higher level of drilling diameter, a lower level of traverse speed rate, and
a higher level of abrasive mass flow rate were obtained for drilling onyx composite to produce
high-quality holes. Whereas lower level of a drilling diameter, a higher level of traverse speed,
and a lower level of abrasive mass flow rate were obtained for drilling onyx composite to
produce poor-quality holes (higher delamination factor). In the onyx composite, during AWJM
the drilling diameter is major influencing factor to obtain the minimum delamination factor and
the lower surface roughness. It was observed that the drilling diameter increases (8mm to
12mm), the minimum delamination factor (peel up and push out) and the lower surface
roughness is noted as shown in Tables 4 and 7. Whereas the lower drilling diameter of 8mm and
10mm, the higher delamination factor, surface roughness is observed than the drilling diameter
of 12 mm.
Table 5: Delamination peel up - response table for S/N Ratios when Smaller is better
Level
Drilling diameter (mm)
Traverse speed rate
(mm/min)
Abrasive mass
flow rate (g/min)
1
-2.46553 0.42525 -1.96935
2
-1.10458 -1.20389 -1.18164
3
0.43028 -2.36119 0.01115
Delta
2.89581 2.78643 1.98050
Rank 1 2 3
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17. 3.2 Surface roughness on onyx composite fiber
Table 7 shows the effect of machining process parameters on surface roughness values, similar
to the effect of delamination factor peel up and push out. It can be seen that as the abrasive mass
flow rate increased, so that the lower surface roughness values were noted. The higher the
traverse speed rate, the higher the surface roughness values observed in the study. Whereas lower
drilling diameter, a higher traverse speed, and a lower abrasive mass flow rate were obtained for
drilling onyx composite to produce higher surface roughness values. The surface roughness
response for each factor and level was summarised using the S/N ratio, as shown in Figure 9 and
Table 8. The rank columns defined the delta values when the drilling process parameters were
varied from level 1, level 2, and level 3. As shown in Table 8, the greater delta value, the better
determination aspect of surface roughness from level 1 to level 3.
Table 7: Design of L9 orthogonal array used for Taguchi analysis and measured values for
surface roughness
Based on the grade result shown in Table 8, it is clear that the abrasive mass flow rate
significantly influences the surface roughness, followed by the traverse speed rate and the
drilling diameter. The preferred drilling process parameters for minimizing surface roughness
No of
experimental
drilling hole ID
Machining Process parameters Surface
roughness
(µm)
Drilling diameter (mm) Traverse speed
rate (mm/min)
Abrasive
mass
flow rate
(g/min)
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30
40
50
250
350
450
350
450
250
450
250
350
3.7705
3.5335
3.2965
3.0675
2.6305
3.8025
2.3445
3.3365
3.0995
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19. 3.3 Investigation of multiple linear regression model and ANOVA
In the current study, the correlation regression analysis of multiple linear regression analysis was
used to determine the response of the onyx composite delamination factor peel-up, push-out and
surface roughness. The R2
(99.1 percent) of the regression coefficient's delamination factor peel-
up standards is in good qualitative agreement with the adjusted R2
(96.4 percent) value obtained.
Similarly, in the study, the delamination factor push out standards of the regression coefficient
R2
(99.6 percent) are in high-quality conformity with the adjusted R2
(98.5 percent), and the
corresponding surface roughness standards of the regression coefficient, R2
(99.6 percent), are in
high-quality conformity with the adjusted R2
(98.3 percent). The regression equation for the
delamination factor peel-up was created.
Delamination peel up = 1.7632 - 0.08857 Drilling diameter (mm)
+ 0.016808 Traverse speed (mm/min) - 0.001137 Abrasive mass flow rate (g/min)
-------------------------------------------------------------------------------------------------------- (2)
The regression equation was generated for the delamination factor push out
Delamination push out = 1.2396 - 0.02547 Drilling diameter (mm)
+ 0.00793 Traverse speed (mm/min) - 0.001167 Abrasive mass flow rate (g/min)
-------------------------------------------------------------------------------------------------------------- (3)
The regression equation was generated for the surface roughness
Surface roughness = 5.587 - 0.1517 Drilling diameter (mm)
+ 0.01693 Traverse speed (mm/min) - 0.004397 Abrasive mass flow rate (g/min) ----------- (4)
According to equations (2), (3), and (4), the drilling diameter (12 mm), traverse speed rate (30
mm/min), and abrasive mass flow rate (450 g/min) all play a significant role in the response of
the onyx composite delamination factor (peel up, push out) and surface roughness. The drilling
process parameters of the drilling diameter (12 mm), traverse speed rate (30 mm/min), and
abrasive mass flow rate (450 g/min) were optimized based on the response graph of the S/N ratio
shown in Figures 7, 8, and 9 and the response Tables of 5, 6, and 8. The statistical Analysis of
variance and Pseudocode of Optimization Algorithms were performed using MINITAB 17.0 and
MATLAB 18.0 to accurately verify the desired drilling process parameters and the
corresponding importance of each factor concerning the delamination and the surface roughness.
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20. Based on the ANOVA, the p-value is less than 0.05, as shown in Tables 9 &10. At a 95
percent confidence level, it was determined that the drilling operation parameter has a clear
impact. Tables 9 & 10 show the PC (percentage of contribution) in the last column, which shows
the directing of each process factor on the response values of the delamination factor (peel up,
push out) and the surface roughness. According to ANOVA Table 9, the drilling diameter (12
mm) and traverse speed rate (30 mm/min) was the most significant contributing factors to the
delamination peel-up at hole entry. Whereas the delamination pushes out at the hole exit, the
abrasive mass flow rate (450 g/min) and traverse speed rate (30 mm/min) were the most
important contributing factors. Similarly, the most important contributing factors to surface
roughness are the abrasive mass flow rate (450g/min) and the traverse speed rate (30mm/min), as
shown in Table 10. The S/N ratio and the ANOVA results were significantly closer to each other.
For delamination peel-up at hole entry, the PC results of the drilling diameter (41.163 percent)
and traverse speed rate (38.430 percent) have far more influencing factors than the abrasive mass
flow rate (19.498 percent). Whereas for the delamination push out at hole exit, the abrasive mass
flow rate (58.116 percent) and the traverse speed rate (28.301 percent) were found to be far more
influential factors than the drilling diameter (13.212 percent) in the drilling onyx composite
materials. In the analysis of variance technique, the abrasive mass flow rate (59.69088 percent)
had the most influencing factor on surface roughness than the drilling diameter (28.89676
percent) and the traverse speed rate (10.66138 percent), as shown in Table 10.
Table 9: ANOVA analysis for Delamination peel up at hole entry and push out at hole exit
Drilling parameters Delamination peel up at hole entry Delamination push out at hole exit
Factors DF SS MS
F-
Value
P-
Value
PC%
SS MS
F-
Value
P-
Value
PC%
Drilling
diameter (mm)
2
12.5937 6.2969 45.38 0.022 41.163 1.8197 0.90986 35.79 0.027 13.212
Traverse speed
rate (mm/min)
2
11.7576 5.8788 42.36 0.023 38.430 3.8978 1.94892 76.65 0.013 28.301
Abrasive mass
flow rate
(g/min)
2
5.9656 2.9828 21.49 0.044 19.498 8.0042 4.00209 157.40 0.006 58.116
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21. Error 2 0.2775 0.1388 - - 0.907 0.0509 0.02543 - - 0.3695
Total 8
30.5945
- - -
100 13.7726
- - -
100
Note: SS-Sum of squared deviation, DF-Degree of freedom, F- Fisher’s F ratio, PC-Percentage
of contribution, MS-Mean squared deviation, P-Probability of significance at 5%.
Table 10: ANOVA analysis for surface roughness
Drilling parameters Surface roughness
Factors DF SS MS F-VALUE P-VALUE PC%
Drilling diameter (mm) 2
4.5020 2.25102 38.48 0.025 28.89676
Traverse speed rate
(mm/min)
2
1.6610 0.83048 22.20 0.046 10.66138
Abrasive mass
flow rate (g/min)
2
9.2996 4.64978 79.48 0.012 59.69088
Error 2
0.1170 0.05850
- -
0.750982
Total 8
15.5796
- - -
100
3.4 Interaction plot for the delamination factor and the surface roughness
The interaction plot, as shown in Figures 10, 11, and 12, revealed an increasing trend of the
abrasive mass flow rate, a decreasing trend of the traverse speed rate, and an increasing trend of
the geometry of the hole, indicating a lower value of the delamination factor (peel up, push out)
and surface roughness. The maximum delamination factor peel-up (1.43780) was observed due
to the higher traverse speed rate (50 mm/min), lower drilling diameter (8 mm & 10mm) and
lower abrasive mass flow rate (250 g/min) because of insufficient kinetic energy. In addition, the
chipping effect was observed as a result of fiber interfacial debonding, as shown in Figure 13.
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22. Similarly, the chipping effect was observed due to the pull-out mechanism for the delamination
factor push-out, as shown in Figure 16. Because of better fibre interfacial bonding, the
delamination factor pushes out (1.1120) obtained a lower value than the delamination factor
peels up. Whereas the abrasive mass flow rate (350 g/min) increased the delamination factor peel
up, the push-out value decreased (Figures 10&11), when compared to the abrasive mass flow
rate (250 g/min). However, chipping was observed in both cases (Figures 14&17) due to a faster
traverse speed rate of 50 mm/min, lower abrasive mass flow rate and lower drilling diameter (8
mm & 10mm), which leads to insufficient kinetic energy over the target material. Similarly, as
shown in Figure 12, the maximum surface roughness (3.8025μm) was observed due to a higher
traverse speed rate (50 mm/min), lower drilling diameter (8 mm) and a lower abrasive mass flow
rate (250 g/min). Compared to the abrasive mass flow rate of 250 g/min, traverse speed rate of
50 mm/min, and the drilling diameter of 8 mm, the increasing trend of abrasive mass flow rate
(350 g/min, 450 g/min), drilling diameter (10mm, 12mm), and the decreasing trend of traverse
speed rate (30 mm/min), the lower surface roughness value (Figure 12 and Table 7) were
observed in the study. According to the interaction plot, the optimized machining (drilling)
process parameters of drilling diameter (12mm), traverse speed rate (30 mm/min), and abrasive
mass flow rate (450 g/min) resulted in the lowest delamination factor and surface roughness
when compared to other drilling process parameters. Furthermore, the chipping effect was not
observed with the optimized drilling process parameters of higher abrasive mass flow rate (450
g/min), also higher drilling diameter (12mm) and lower traverse speed rate (30 mm/min) due to
higher kinetic energy over the target material (good fibre interfacial bonding) (Figures 15&18).
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27. Figure 18. Delamination push out drilled hole surface at drilling diameter (12 mm),
traverse speed rate (30 mm/min), and the abrasive mass flow rate (450 g/min)
3.4.1 Comparative study of UCM process over other methods
The material removal occurs in the unconventional machining process (UCM) is based on
minimal cutting force, high pressure, high frequency vibration, and high temperature through
special equipment; it is completely different from the conventional material removing
techniques[45]. The wire electro discharge machining (WEDM) has restrictions to perform the
machining operations as only conductive materials can be used Unde et al. [46]. Even though
there are different types of unconventional machining process in practice such as laser
machining, water jet machining, Electrochemical Machining, and ultrasonic machining, etc[36].
Compared to other UCM process, the AWJM process, the machining accomplishment is based
on machining process parameters and also material properties. Table 11, shows the Delamination
damage and surface roughness in the AWJM process compared to other methods. The
conventional machining techniques are having poor surface finish, fiber pullout, harshly
damages to subsurface and high matrix removal, which causes uneven surface roughness due
to higher thrust force and torque reported by (Vinod et al.[47], Azmi et al.[48], Debnath et al.[49],
and Dvivedi et al.[50]).
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8
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28. Table 11. Delamination damage and surface roughness in the AWJM process compared to
other methods.
S.
No
Machining methods Materials used Delamination
factor value
Surface
roughness
(µm)
References
1 Computer numerical control vertical
drilling machine
Glass fiber
reinforced
plastics(GFRP)
- 3.50
Vinod et
al.[47]
2 Vertical drilling machine Carbon fiber
reinforced
polymers
(CFRP)
1.55 -
Korlos et
al.[51]
3 Electro Discharge Machining CFRP
1.60 -
Korlos et
al.[51]
4 Vertical drilling machine CFRP 1.30 - Feito et
al.[52]
5 Laser machining GFRP 1.30 7 Hejjaji et
al.[13]
6 Electrochemical Discharge
Machining
CFRP 1.42 - Mukund et
al.[53]
7 Laser drilling kenaf/high-
density
polyethylene
composites
- 3.83 Renu et
al.[54]
8 Electrical Discharge
Machining(EDM)
CFRP 1.30 6 Guu et
al.[55]
9 AWJ drilling -
Abrasive mass flow rate (3g/min),
Traverse speed rate (20 mm/min),
Drilling diameter (10mm),Abrasive
Water jet pressure (300MPa)
CFRP 1.92 2.38 Hom et
al.[29]
10 AWJM - Abrasive mass flow rate
(450g/min), Traverse speed rate
(30mm/min),Drilling diameter (12
mm),Abrasive Water jet pressure
(380 MPa)
3D Printed
Onyx composite
0.69 2.34 Present
work
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29. The AWJM is the most suitable machining method for fiber-reinforced composites because of
minimal cutting force and the absence of the heat-affected zone (HAZ). Due to the absence of
cutting tool during machining, delamination damages are reduced drastically and thermal
distortion effects is eliminated when compared to other machining techniques. Moreover
controlled process variables of AWJM such as lower traverse speed rate, and higher abrasive
mass flow rate, higher water jet pressure leads to reduced delamination of onyx composites. The
higher abrasive mass flow rate, higher water jet pressure leads to high kinetic energy for the
abrasive particles impacting on the work piece surface, so that enhancing drilling of the material
with better surface roughness, high jet penetration and minimization of delamination factor. At
lower traverse speed rate there is a possibility of rising the number of abrasive particles, which
has an influence on the work piece per unit time and hence an improved surface roughness,
minimization of delamination factor and penetration depth were obtained (Momber et al.[56],
&Karakurt et al.[57]). The other input process parameters and interaction parameters were found
to be less significant due to failure of the statistical test. Compared to other methods, AWJM is a
low cost production technique, time saving process, and is more environmentally eco-friendly. It
can able to do machining of metals, non-metals, synthetic and natural fiber composite materials.
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30. 3.5 Probability plot for the delamination factor and the surface roughness
Figures 19, 20 and 21 shows the normal probability plot function plotted between the response
values (delamination peel up, delamination push out, and surface roughness) in the X-axis and
the percent in the Y-axis. According to the probability plot function, the response values such as
delamination peel up, delamination push out, and surface roughness points were fitted within the
central line, as indicated by the central limit theorem. The goodness of fit is also shown for the
data response values. As a result of the probability plot function, it was determined that the
response (delamination factor - peel up, push out, and surface roughness) data are typically
distributed closer to the central line, as shown in Figures 19, 20, and 21. Similar kind analysis
were reported by Vankanti,et al.[47]. This work will be useful for industries for the selection of
process parameters in drilling the onyx composite materials which improves the quality of the
drilled holes by reducing the delamination.
Figure 19. Probability plot of delamination factor peel up
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32. 3.6 Pseudocode of Optimization Algorithms
The optimum drilling process parameters were identified and validated using Pseudocode of
Optimization Algorithms such as the Month Flame Optimization Algorithm (MFO) and the
genetic algorithm (GA), as shown in Figures 22,23 and 24, and tabulated in 12.
i) Moth-Flame Optimization Algorithm
Read the lower and upper bounds of each parameters along with the number of Flames (mf)
Initialize Moth position Pij randomly (i=1,2,3…mf and j=1,2,3…np)
For each i=1:mf
Compute the response values Rik (i=1,2,3…mf and k=1,2,3…nr)
End
While (itr ≤ max_itr)
Update the position of Pij
Calculate the no. of flames (nf) = round((mf-(itr*(mf-1)/max_itr)))
Evaluate the fitness function Rik
If (itr==1) then
F = sort (Pij)
OF = sort (Rik)
Else
F = sort (Pt-1, Pt)
OF = sort (Pt-1, Pt)
End
For each i=1:mf do
For each j=1:np do
Update the values of r = -1+(itr*(-2-1)/max_itr) and t = randbetween(r,1)
Calculate the value of D as abs(Fj. – Pi.)
Update Pij w.r.t. corresponding Flame
End
End
End
Using Deng’s Method, compute the best parameters and its response values
ii) Genetic Algorithm (GA)
Initialize population of chromosomes (Pij)
While (itr<=max_itr)
Compute Response values Rik
Select pareto optimal solutions
Select N chromosomes for reproduction
Crossover (new chromosome created by cross over operator from N)
Mutation (new chromosome created from both reproduction and cross over
chromosomes)
End
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33. Using Deng’s method select the best chromosomes and its fitness values from pareto optimal
front solutions.
mf – maximum number of moth flames
np- number of parameters
nr- number of responses
nf –number of flames
Pij – ith
moth’s jth
parameter value
Rik – kth
response value of ith
moth flame
Flj – lth
flame’s jth
parameter value
0 10 20 30 40 50 60 70 80 90 100
0.692
0.694
0.696
0.698
0.7
0.702
0.704
0.706
0.708
Iteration No.
Peel
Up
GA
MFO
Figure 22. Convergence plot for peel up of delamination value
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34. 0 10 20 30 40 50 60 70 80 90 100
0.646
0.647
0.648
0.649
0.65
0.651
0.652
0.653
0.654
Iteration No.
Peel
Out
GA
MFO
Figure 23. Convergence plot for push out of delamination value
0 10 20 30 40 50 60 70 80 90 100
2.296
2.298
2.3
2.302
2.304
2.306
2.308
2.31
Iteration No.
Surface
Roughness
GA
MFO
Figure 24. Convergence plot for surface roughness value
3.7 Confirmation test of the drilling process parameters on onyx composite
The confirmation was carried out using optimized drilling process parameters such as drilling
diameter (12mm), traverse speed rate (30mm/min), and abrasive mass flow rate (450 g/min)
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35. to obtain the results of delamination peel up (PU) and push out (PO) and surface roughness, as
shown in Table 12. Based on the experimental results and the predicted results of the regression
model equation, Moth-Flame Optimization algorithm (MFO) and genetic algorithm (GA), both
results were obtained almost identically with a margin of error of less than 6%. It was discovered
that the experimental and predicted values are both good occurrences obtained through Taguchi
analysis and Pseudocode of Optimization Algorithms (Figures 22, 23 & 24). It was stated that
the proposed model is suitable for the selected range of drilling process parameters of onyx
composite, followed by the AWJM.
Table 12: Best Parameters results of confirmation test for delamination peel up (PU) and push
out (PO), & the surface roughness (SR)
Optimized machining
process parameters
Experimental values
Algorithms
&
Regression
model
Predicted values of
delamination factor and
surface roughness
DD
(mm)
TS
(mm/
min)
AMF
(g/
min)
PU PO SR
(µm)
PU PO SR
(µm)
12 30 450 0.696 0.685 2.344
GA
0.705 0.651 2.318
Error (%)
1.29 4.96 1.12
MFO 0.693 0.646 2.296
Error (%) 0.43 5.69 2.09
Regression
model
equation
0.692 0.646 2.295
Error (%) 0.57 5.69 2.09
Note: Drilling diameter (DD), Traverse speed (TS), Abrasive mass flow rate (AMF)
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36. 4. Conclusions
The machinability (drilling) of the onyx polymer composite was evaluated using AWJM,
followed by Taguchi statistical analysis, ANOVA, and these results were validated using a GA
and MFO.
The concluding remarks for the present study are as follows,
An optimum combination of AWJ drilling parameters and their levels was identified
which achieves lower delamination factor peel up, push out, and surface roughness
compared to other machining process parameters based on the Taguchi analysis, S/N
ratio, ANOVA, GA and MFO.
The optimum level of input process parameters combinations was identified conforming
to the response of closeness coefficients: abrasive mass flow rate (450 g/min), traverse
speed rate (30 mm/min), and drilling diameter (12 mm).
Analysis of variance was performed to investigate the significant parameters for the
multi performance characteristics of AWJM. Based on the ANOVA analysis, P value was
found to be the most significant factor, followed by abrasive mass flow rate, traverse
speed rate, and drilling diameter. The delamination factor and surface roughness can be
reduced by reducing the traverse speed rate and increasing the abrasive mass flow rate,
drilling diameter at constant higher abrasive water jet pressure (380 MPa). Further
increasing in the traverse speed rate, and reducing the abrasive mass flow rate, drilling
diameter will increase the delamination factor due to the involvement of insufficient
kinetic energy over the target material.
The Regression model, Genetic algorithm and Moth-Flame Optimization algorithms,
were used to model the variation of the machining operation parameters mathematically.
The confirmation test confirms that the experimental results were closer to the predicted
values of delamination factor - peel up, push out, and surface roughness. The
experimental results were found to agree with the predicted results. It was found that the
proposed combination of Taguchi analysis, ANOVA, GA and MFO algorithms was more
effective in solving AWJM multi response problems.
Finally, it was discovered that the AWJM process is superior to conventional methods for
machining onyx composite material. Directly, it can be used in various industrial
applications such as aerospace, automobiles, and construction, among others.
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37. The mechanism of interlaminar deformation of onyx composites during the drilling process can
be further analyzed with the help of the finite element method, and the delamination can be
monitored via the internet of things (IoT). The variation of abrasive water jet pressure will be
considered as future work.
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41. Response to Reviewer Comments
From
Dr. Sachin Salunkhe,
Department of Mechanical Engineering,
Vel Tech Rangarajan Dr.Sagunthala R & D Institute of Science and Technology,
Avadi, Chennai 600 062, India.
To
Soumitra Paul(Machining, Grinding,Tool Coating ),
Corresponding Editor,
Sadhana.
Sub:- Revision of manuscript – Reg.
Greetings,
The authors would like to thank the Editor for accepting this manuscript with minor modification based
on the reviewer’s comments. Manuscript Ref.: Ms. No. SADH-D-22-00122R1 and Titled “Optimization of
AWJM drilling process parameters on onyx composite followed by Additive Manufacturing”.
Based on the comments received from Editor, we have addressed the reviewer’s comments with
the appropriate heading. The revised manuscript is also attached for your kind perusal.
Appendix 1 – Reviewer #2 comments with response
Appendix 2 – Reviewer #3 comments with response
Similarly the corrected section was highlighted in red colour within the revised manuscript.
Thanking You
Yours Sincerely
(Dr. Sachin Salunkhe)
Click here to access/download;Authors' Response to Reviewers'
Comments;Responses to reviewer comments1 -
42. Appendix 1 – Reviewer #2 comments with response
We thank the reviewer for his constructive criticism and positive comments to improve the
quality of the manuscript. As per the suggestion of the reviewer's comment, the corrections have been
incorporated in the revised manuscript. The reviewer's comments were addressed below.
Manuscript Title: (Ref.: Ms. No. SADH-D-22-00122R1)
“Optimization of AWJM drilling process parameters on onyx composite followed by Additive
Manufacturing”
Reviewer comments #1:
Q1. The authors have stated that "The term '3D printing' refers to the process of fabricating the
composite materials through layer by layer succession of additive manufacturing, followed by
the Mark forged - Mark Two Desktop composite 3Dprinters, which print using fused deposition
modelling (FDM) technology". The authors should note that the term 3D Printing does not refer
to the process of fabricating composite materials. In addition to composites, the term is applicable
to polymers and metals. Thus, the corresponding sentence in the introduction has to be modified
or rephrased again.
Response
Thank you for your corrections. The above sentence has been re-modified and incorporated in the
revised manuscript (Pg No. 2 Introduction section 1).
Reviewer comments #2:
Q2. The AWJM is the most suitable machining method for fibre-reinforced composites because of the
absence of the heat-affected zone (HAZ) and exerts minimal cutting force; a cutting tool that is
responsible for thermal distortion and thrust force due to reduced delamination damage was
noted in the AWJM process compared to other methods'. The authors should check and rephrase
the sentence once again for more clarity. The authors may rewrite the same sentence into two
separate sentences.
Response
Thanks for the suggestions, the above mentioned sentence have made the necessary changes and
incorporated in the revised manuscript (Pg No. 27 Results and discussion section 3.4.1).
43. Reviewer comments #3:
Q3. Mention one or two distinct industrial applications of onyx composites in the introduction section
(preferably after the second sentence).
Response
Onyx polymer composite are used various industrial applications such as including aerospace,
valves and fittings; robot grippers, tools, battery cell holders, cargo and passenger doors; Jigs and
fixtures; wind turbine blades, automotive, prototype parts and civil structures. As per suggestion,
the applications has incorporated in the revised manuscript in the introduction section 1 (Pg No. 2).
Reviewer comments #4:
Q4. Please correct the grammatical errors visible at various sections in the manuscript.
Response
Throughout the manuscript the grammatical errors were checked and incorporated in the revised
manuscript.
We hope, the reviewer queries have been carefully addressed. So, as per the suggestions from the Editor,
the authors are herewith resubmitting the revised manuscript for further consideration.
44. Appendix 2 – Reviewer #3 comments with response
We thank the reviewer for his constructive criticism and positive comments to improve the quality of the
manuscript. As per the suggestion of the reviewer's comment, the corrections have been incorporated in
the revised manuscript. The reviewer's comments were addressed below.
Manuscript Title: (Ref.: Ms. No. SADH-D-22-00122R1)
“Optimization of AWJM drilling process parameters on onyx composite followed by Additive
Manufacturing”
Reviewer comments #1:
Q1. Still the literature review of the article is lengthy. It needs to be concise and focused towards the
objective of the work.
Response
The critical literature reviews regarding the objective of the current study were maintained throughout
the manuscript in the introduction section. Other literature reviews were removed from the manuscript
based on your valuable suggestions and incorporated in the in the revised manuscript.
Reviewer comments #2:
Q2. No new knowledge-base on 3D printing is added in this article, therefore, these part may be
removed and more information about machinability studies (drilling) of the onyx composite
using AWJM (abrasive water jet machining) would be provided.
Response
We would bring the notice to the reviewers that the making a hole in 3D printed parts is possible using
3D printing machine - Fused deposition modelling (FDM). As you aware, the near net shaped 3D printed
parts have a good quality in the final product but at that same time the smooth surface roughness not
maintained. Moreover, to obtain accurate dimensions of hole is a daunting task. Osama et al.[17] and
Akhilesh et al.[18] reported that 3D printed parts have poor surface roughness, dimensional inaccuracy
and warping. Because of that the present study is primarily focused on machinability studies on 3D
printed parts of onyx polymer composites using AWJM.
Based on the available literature review, it was found that the 3D printed part of onyx polymer
composites machinability studies has not been reported. Therefore, the new knowledge can be gained of
mark forged (FDM) 3D printed parts of onyx polymer composites machinability studies (drilling) were
performed through AWJM. This machinability (AWJ drilling) process parameters such as traverse speeds
and abrasive mass flow rates and onyx polymer composites drilling diameter were optimized through
Taguchi analysis and then validated using the Genetic algorithm (GA) and the Moth Flame Optimization
algorithm (MFO).
45. Reviewer comments #3:
Q3. Further, for optimization problem, more number of experiments and development of nonlinear
regression models are recommended.
Response
The regression coefficient's (R2) of each regression model for onyx composite was found to be 99.1%,
99.6% & 99.6% for delamination factor peel-up, push-out and surface roughness respectively. It is clear
that the value of R2 goodness of fit for the model, which indicates that the regression model can be
represented as experimental data is closer. In order to further understand the relationship between
experimental response and main parameters, the regression model equations were validated using
genetic algorithms and the Moth-Flame Optimization algorithm and also confirmed through
confirmation test (shown in Table 12). Because of materials, manufacturing and machinability cost the
experiments were limited to nine experiments. As per the suggestions from reviewer, a greater number of
experiments and nonlinear regression models will be done as future study.
Moreover, several researchers have done similar kind of analysis namely such as Chohan et al. [2022],
Antil et al. [2018], Moorthy et al. [2015], Sesharao et al. [2021], Kus et al. [2018], Sakthi et al. [2020],
Vankanti et al. [2014].
Chohan, J.S., Kumar, R., Yadav, A., Chauhan, P., Singh, S., Sharma, S., Li, C., Dwivedi, S.P. and
Rajkumar, S., 2022. Optimization of FDM Printing Process Parameters on Surface Finish,
Thickness, and Outer Dimension with ABS Polymer Specimens Using Taguchi Orthogonal Array
and Genetic Algorithms, Mathematical Problems in Engineering, 2022.
Antil, P., Singh, S. and Manna, A., 2018, Genetic algorithm based optimization of ECDM process
for polymer matrix composite, In Materials Science Forum (Vol. 928, pp. 144-149), Trans Tech
Publications Ltd.
Moorthy, S.S., Manonmani, K. and Elangovan, T., 2015, An optimization approach to the dry
sliding wear behavior of particulate filled glass fiber reinforced hybrid composites, Journal of
engineered fibers and fabrics, 10(2), p.155892501501000213.
Sesharao, Y., Sathish, T., Palani, K., Merneedi, A., De Poures, M.V. and Maridurai, T., 2021.
Optimization on operation parameters in reinforced metal matrix of AA6066 composite with HSS
and Cu, Advances in Materials Science and Engineering, 2021.
Kus, H., Basar, G. and Kahraman, F., 2018. Modeling and optimization for fly ash reinforced
bronze-based composite materials using multi objective Taguchi technique and regression
analysis. Industrial Lubrication and Tribology.
46. Sakthi Balan, G., Ravichandran, M. and Kumar, V.S., 2020, Study of ageing effect on mechanical
properties of Prosopis juliflora fibre reinforced palm seed powder filled polymer
composite, Australian Journal of Mechanical Engineering.
Vankanti, V.K. and Ganta, V., 2014, Optimization of process parameters in drilling of GFRP
composite using Taguchi method, Journal of Materials Research and Technology, 3(1), pp.35-41.
We hope, the reviewer queries have been carefully addressed. So, as per the suggestions from the Editor,
the authors are herewith resubmitting the revised manuscript for further consideration.
