A Comprehensive Investigation on the Fabrication Parameter Optimization for Natural Fibre Reinforced Laminate Sandwich Composite

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nt. J. Materials Engineering Innovation, Vol. 15, No. 3, 2024
Copyright © 2024 Inderscience Enterprises Ltd.
A comprehensive investigation on the fabrication
parameter optimisation for natural fibre reinforced
laminate sandwich composite
T. Ganapathy*
Department of Mechanical Engineering,
P.S.R. Engineering College,
Sivakasi, Tamil Nadu, India
Email: ganaskctmech@gmail.com
*Corresponding author
Milon Selvam Dennison
Department of Mechanical Engineering,
Kampala International University – Western Campus, Uganda
Email: milon.selvam@kiu.ac.ug
S. Arivazhagan
Department of Mechanical Engineering,
KPR Institute of Engineering and Technology,
Coimbatore, Tamil Nadu, India
Email: arivuazhagan001@gmail.com
M. Shirin Ayisha Maryam
Department of Computer Science and Engineering,
S. Veerasamy Chettiar College of Engineering and Technology,
Tenkasi, Tamil Nadu, India
Email: ayishamohammed1486@gmail.com
R. Radhakrishnan
Department of Electronics and Communication Engineering,
United Institute of Technology,
Coimbatore, Tamil Nadu, India
Email: rlgs14466@gmail.com
M. Thirukumaran and P. Sivasamy
Department of Mechanical Engineering,
P.S.R. Engineering College,
Sivakasi, Tamil Nadu, India
Email: mkthirukumaran@gmail.com
Email: siva31samy@gmail.com

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Abstract: This research investigates the fabrication of natural fibre-reinforced
laminate sandwich composites, emphasising the synergy between fibre type,
polymer laminate, and fibre treatment. The grey relational and Taguchi
techniques were employed to analyse the combinations of three natural fibres
(snake grass, banyan, pineapple), three polymers (high-density polyethylene,
high-impact polystyrene, polycarbonate), and chemical treatments (alkali,
potassium permanganate, benzoyl peroxide). The compression moulding was
adapted to produce the polymer sandwich composites with natural fibre
reinforcements. The mechanical properties of the fabricated composites were
measured using tensile and flexural tests. The contribution of the parameters to
the outcomes was estimated using ANOVA. The comparison analysis suggests
that the chemical treatment is the most influential fabrication parameter for
controlling multiple response characteristics. The most critical process
parameters for achieving the desired qualities (with values of 0.687, 0.663, and
0.655) are chemical treatments, polymer laminate, and fibre categories.
Thereby, the three important fabrication parameters contribute to the
advancement of sustainable composite materials.
Keywords: natural fibre; polymer laminate; chemical treatment; compression
moulding; sandwich composite; grey relation; Taguchi technique.
Reference to this paper should be made as follows: Ganapathy, T.,
Dennison, M.S., Arivazhagan, S., Maryam, M.S.A., Radhakrishnan, R.,
Thirukumaran, M. and Sivasamy, P. (2024) ‘A comprehensive investigation on
the fabrication parameter optimisation for natural fibre reinforced laminate
sandwich composite’, Int. J. Materials Engineering Innovation, Vol. 15, No. 3,
pp.264–284.
Biographical notes: T. Ganapathy is a dedicated academician in the field of
mechanical engineering, currently serving as an Associate Professor at the
P.S.R. Engineering College. He obtained his PhD full-time research at the
Anna University Chennai. His research specialises in polymer matrix
composites and bio-films. He holds a guideship in PhD from the Anna
University Chennai, with his research focused on polymer matrix composites,
optimisation, and friction stir welding. His academic contributions are
significant, with numerous publications in international journals and
presentations at conferences. His research interests are diverse, encompassing
natural fibre composites, 3D printing, and friction stir welding, among others.
Milon Selvam Dennison is a Senior Lecturer in the Department of Mechanical
Engineering at the School of Engineering and Applied Sciences, Kampala
International University, Western Campus, holds Bachelor’s, Master’s, and
PhD in Mechanical Engineering from India. With nine years of teaching
experience in India and three years in Uganda, he has supervised numerous
master’s and PhD students in his research area. He has conducted training
sessions aimed at enhancing students’ research, writing, and presentation skills.
His research interest is aligned with sustainable manufacturing, green
manufacturing, and sustainable machining. He has contributed to reputed
journals, authored book chapters for standard publishers, and collaborated on
research papers with colleagues. Additionally, his involvement in curriculum
development underscores his dedication to advancing education in mechanical
engineering.
S. Arivazhagan received his BE in Mechanical Engineering from the Tamil
Nadu College of Engineering, India in 2010. He received his ME (CAD/CAM)
from the Sri Krishna College of Technology, India in 2013, and his PhD
(Doctor of Philosophy) from the Anna University, India in 2021. Prime Star

266 T. Ganapathy et al.
Industries (Quality Supervisor) 5 May 2010–10 May 2011, Sri Krishna College
of Technology (Assistant Professor) 6 June 2013–31 October 2019 and KPR
Institute of Engineering and Technology (Associate Professor/Innovation
Officer) 21 June 2021–till date.
M. Shirin Ayisha Maryam received her BE in Computer Science and
Engineering from the National College of Engineering, Anna University, India
in 2011. She received her ME in Computer Science and Engineering from the
Anna University, India in 2013, and her PhD in Computer Science and
Engineering from the Anna University, India. She has been working as an
Assistant Professor in the Department of Computer Science and Engineering,
S. Veerasamy Chettiar College of Engineering and Technology, Tamil Nadu,
India. Her field of interests includes machine learning, deep learning and
network security.
R. Radhakrishnan received his BE in Electronics and Communication
Engineering from the Bharathidasan University, India in 1990. He received his
ME in Applied Electronics from the Bharathiar University, P.S.G. College of
Technology, India in 1997, and his PhD in Information and Communication
Engineering from the Anna University, Government College of Technology,
India in 2008. His career starts from 1991, he has vast experience of 33 years
working in various position at various colleges around Tamil Nadu. His field of
interests includes microprocessors, microcontrollers and its applications. Under
his guidance 18 students completed his/her doctorate degree.
M. Thirukumaran is working as an Associate Professor in the Department of
Mechanical Engineering at P.S.R. Engineering College, Sivakasi, Tamil Nadu,
India. He graduated with a degree in Mechanical Engineering from
Kalasalingam University in 2013. He received his Master’s in Manufacturing
Engineering from the Anna University, Chennai, Tamil Nadu, India, in 2015
and his PhD in the Department of Mechanical Engineering from Kalasalingam
Academy of Research and Education, Krishnan Koil, Tamil Nadu, India, in
2020. He has six years of teaching and nine years of research experience. He
published two patents and five book chapters. His research area is hybrid
laminate structure, polymer composites, material characterisation, tribology,
and welding.
P. Sivasamy received his BTech in Mechanical Engineering from the
Kalasalingam University, India in 2014. He received his ME in Engineering
Design from the Anna University, India in 2016, and his PhD in Mechanical
Engineering from the Anna University, India in 2021. Since 2022, he has been
working as an Associate Professor in the Department of Mechanical
Engineering, P.S.R. Engineering College, Tamil Nadu, India. His field of
interests includes composite materials, material science and phase change
material.
1 Introduction
In the modern era, natural fibre-reinforced sandwich composites play a vital role in the
manufacturing industry, replacing conventional and synthetic materials due to their
lightweight and high-strength properties (Thyavihalli Girijappa et al., 2019; Riccio et al.,
2018; Khan et al., 2022). The fibre extracted from naturally available plants and certain
matrix creates the natural fibre-reinforced sandwich composites for real-time

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applications. The natural fibre can be extracted from famous plants such as banana, coir,
sisal, abaca, hemp, jute, pineapple, and flax, exhibiting good strength, low density and
corrosion resistance properties. Reinforcements made from natural fibres in a polymer
matrix have several benefits, including lighter composites, lower cost, and greater
adaptability during preparation (Tran et al., 2019). In recent years, the global emphasis on
sustainable and eco-friendly materials has intensified across various industries. This
paradigm shift is driven by an escalating awareness of environmental concerns and the
imperative to reduce the ecological footprint associated with conventional manufacturing
processes. Within this context, natural fibre composites have emerged as a compelling
and increasingly important area of research and application. The unique combination of
lightweight characteristics and desirable mechanical properties positions natural fibre
composites as a viable substitute for conventional materials in numerous sectors. As
industries seek innovative and environmentally responsible alternatives, the research and
development of natural fibre composites have gained momentum, making them an
integral part of the global shift toward sustainable practices. Moreover, the versatile
nature of natural fibres allows for a broad range of applications, spanning from
automotive and construction to packaging and consumer goods (Thyavihalli Girijappa
et al., 2019; Riccio et al., 2018; Khan et al., 2022).
The high-strength pineapple leaf fibre (PALF) has the potential to replace more
expensive and non-renewable synthetic fibre while also providing a source of unifying
composite material for the manufacturing sectors (Motaleb et al., 2018). Interfacial
interaction is crucial for natural composite properties as it directly impacts mechanical
strength, thermal conductivity, dimensional stability, and resistance to environmental
factors. A strong interface enhances load transfer, reinforcing the composite structure and
improving overall performance (Motaleb et al., 2018; Zin et al., 2018) However, the
interfacial interaction between fibres and reinforced matrix compatibility of composite
has only been the subject of a few investigations (Zin et al., 2018). The development of
PALF fibres for industrial applications is abundant, renewable, and readily accessible.
PALF has proven to be an adequate substitute for man-made fibres due to its minimum
cost and easy renewability.
PALF’s outstanding mechanical qualities result from its high alpha-cellulose content
and low microfibril angles. PALF can be used as a composite matrix reinforcement
because of its exceptional qualities. In terms of physical and mechanical properties, all-
natural fibres differ depending on factors like their adhesion to the matrix, volume
fraction, aspect ratio, and stress resistance. PALF-based polymer composites have more
stiffness and strength than cellulose-based composites. PALF/PP composite exhibited an
increase of 210% tensile strength (TS), 412% tensile modulus, 155% bending strength,
265% bending modulus, and 140% impact strength compared to polypropylene (PP)
matrix (Motaleb et al., 2018).
The banyan tree (Ficus Benghalensis) is widespread in numerous biosphere regions,
including India, Guinea, Australia, the USA, and New Caledonia. It can grow well in
both tropical and subtropical climates on any soil. A typical banyan tree grows to a height
of 30m with aerial roots, and the fibre extracted from the aerial root is well-suited for
producing unidirectional and bidirectional composites (Ganapathy et al., 2019a). The
primary issue in fibre-matrix interfacial contact is the conflict between fibre
hydrophilicity and matrix hydrophobicity. The importance of adapting these uncertainties
to the essential needs of composites for real practical applications was emphasised.
Increasing matrix adherence by roughening the fibre surface can produce a high-strength

268 T. Ganapathy et al.
composite, chemically treated fibre surfaces before composite production can solve these
problems (Ganapathy et al., 2023).
The alkali treatment was the primary treatment, followed by potassium permanganate,
stearic acid, and benzoyl peroxide (BP). The maximum mechanical properties were
achieved by treating fibre composites with permanganate (Motaleb et al., 2018; Aravindh
et al., 2022). The best mechanical performance was also reported for composites
containing Agava sisalana treated with potassium permanganate (KMnO4). The maximal
tensile characteristics of polyester composites made from alkali-treated elephant grass
fibre were superior to those made from permanganate-treated fibre (Aravindh et al., 2022;
Prabhu et al., 2020). In an experiment, different amounts of sodium hydroxide (NaOH)
were used on the coconut coir fibre with PP (C3H6)n composites. An amount of 6% of
NaOH-treated natural fibre generated the highest level of mechanical performance
(Mehra et al., 2021). The fibre made from banana and kenaf polyester hybrid composites
treated with sodium lauryl sulphate instead of the NaOH chemical fibre had the best
mechanical properties (Thiruchitrambalam et al., 2009). The randomly oriented Agava
Sisalana fibre tensile characteristics on PP matrix composites. The Agava sisalana fibre
treated with NaOH was superior to those treated with permanganate and maleic
anhydride (Vijay et al., 2021). The maximum mechanical properties of Agave sisalana
fibre on PP composites were attained in 3% alkalised Agave sisalana fibre, as opposed to
10% NaOH-treated Agave sisalana fibre (Khan et al., 2019). To convalesce the
mechanical properties of PP-flax fibre composites, the Flax fibre was treated with 5%
sodium hydroxide (NaOH). The effects of 2% alkali treated on Agave sisalana/glass, 1%
alkalised on bambusoideae/glass, and 2% alkali on pure silk/Agave sisalana fibre
polyester-based hybrid composites. They investigated the outcome of these treatment
reactions on the composites by chemical resistance and mechanical properties (Subash
et al., 2022). Specifically, the mechanical characteristics of composites made from
banana-woven fibre polyester determined that the best mechanical properties were
achieved after treatment with 1% NaOH. The tensile characteristics of Agave sisalana
fibre polyester composites treated with 5% of alkali (NaOH), benzoyl chloride reagent,
permanganate (KMnO4), and silane (SiH4) (Aravindh et al., 2022). Composites with
NaOH and SiH4 fibres had the highest TS.
Comparatively, polymer matrix composites have the highest enriched properties than
ceramic matrix, metal matrix, and carbon matrix composites. Due to its low mass and
high strength properties, the polymer matrix composite is the most desirable composite. It
can be made with either a thermosetting or a thermoplastic matrix. Thermoplastic
materials are PP, polyethene, and polyvinyl chloride, while thermosets include epoxy,
phenolics, and polyesters. The manufacturing process and the constituent materials
determine the mechanical properties of the sandwich composite (Cao et al., 2022; Zheng
et al., 2022).
The optimisation benefits of Taguchi’s method include little expenditures of time and
money on investigations. The glass/PP composite laminate formations were optimised to
maximise flexural strength. The results indicate that hybrid configurations are more
advantageous than conventionally reinforced laminates, determined by the Taguchi
technique and grey relational analysis (Praveena et al., 2022). The optimal manufacturing
factor for Agave Sisalana fibre and thermosetting resin composites, the Analysis of
Variance, was used to identify the critical factor (ANOVA) (Sundara Bharathi et al.,
2019; Ravi Kumar et al., 2017). Results suggest that fibre content is the most influential
factor in determining the critical mechanical properties of matrix composites.

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In this research work, three categorial fabrication parameters have been chosen, such
as natural fibre type (f), polymer laminate (l), and fibre chemical treatment (c) that
influence the mechanical properties of the sandwich composite. These were selected due
to their significant influence on the mechanical properties of the composite. The natural
fibres include snake grass, banyan, and pineapple, while the polymer laminates are high-
density polyethylene (HDPE), high-impact polystyrene, and polycarbonate (PC). The
chemical treatments involve alkali, potassium permanganate, and BP. The research aims
to understand how these parameters affect the composite’s tensile and flexural strength,
optimising them using grey relational and Taguchi techniques. The relevance of each
parameter is demonstrated through their impact on the composite’s performance,
highlighting the importance of careful selection and treatment of materials in developing
efficient and sustainable composite materials.
2 Experimental strategies
2.1 Research materials
In this current research,
a snake grass
b banyan
c pineapple fibre were used as reinforcement materials illustrated in Figure 1.
Among many treatments available for natural fibres, the NaOH treatment has
traditionally been the most used. Most of the initial fibre treatment employed in
composite preparation involved a NaOH concentration of 5%. After the first treatment,
different chemicals were used to make composites. These included benzoyl chloride
reagent, stearic (octadecanoic) acid, permanganate (KMnO4), silane (SiH4), and sodium
lauryl sulphate. SiH4 and KMnO4 have been proven next superior to other fibre treatment
chemicals (Aravindh et al., 2022; Suganya et al., 2022). The three different untreated
natural fibres were soaked in three different chemicals, alkali (NaOH), potassium
permanganate (KmnO4), and BP, to remove the chemical over the surface of the fibre for
60 minutes.
Bio-composites comprise natural fibres and matrices of man-made non-ecological
polymers that partially bio-degrade over time. In addition, the eco-friendly material has
comparable technical qualities and processability to resins derived from fossil fuels.
Therefore, producing eco-friendly plastic does not require additional alterations to the
underlying technology. High mechanical properties are an advantage of biodegradable
plastics (high-impact polystyrene, PC, and HDPE). However, thermoplastic is a
significantly non-polluting material that decomposes into typical substances and is used
in the automotive, construction engineering materials, and fibre optics industries
(Suganya et al., 2019).
In this research work, perforated plastic HDPE, high impact polystyrene (HIPS), and
PC polymer reinforcement are used in the preparation of sandwich composite. The
physical properties of Polymer laminates are listed in Table 1.
The polymer sheets were purchased from Royal Hardware Mart, Nagarathpete,
Bengaluru, India, after the sheets were drilled with a hole size of 8 mm diameter by a

270 T. Ganapathy et al.
CNC machine in Coimbatore, India. Epoxy resins and hardeners were used as matrix
material, and triethylenetetramine (TETA) was used as the hardener. Epoxy matrix has
unique mechanical characteristics. The matrix and fibre bonding property determines the
composite’s final qualities. Aypols Polymers Private Limited, India, supplied both the
epoxy resin (density: 1.2 g/cm3) and the TETA (density: 0.98 g/cm3). The matrix was
created by combining epoxy resin and hardener ratio at 10:1. We identified a gap in the
existing literature regarding the comprehensive optimisation of natural fibre-reinforced
laminate sandwich composites. Our novel approach combines the study of various natural
fibres, polymer laminates, and chemical treatments in a singular framework to understand
their combined impact on mechanical properties. This integrated analysis is
unprecedented in the field, offering a more holistic understanding of material
performance and sustainability in composite manufacturing. We believe these additions
will greatly enhance the reader’s comprehension of the study’s significance and
originality.
Table 1 The physical properties of Polymer laminate sheets
Physical properties HDPE HIPS PC
Density (g/cm3) 0.96 1.09 1.20
Tensile properties (MPa) 30.5–32 32 66
Tensile modulus (GPa) 0.86 1.9 2.4
Elongation at break (%) 150 40 110
Glass transaction temperature 130 100 150
Poisson’s ratio 0.46 0.41 0.36
Flexural modulus (GPa) 1.25 1.8 2.4
Mould shrinkage (%) 3 0.5 0.5–0.8
Melting temperature (°C) 120–150 210–270 310–330
Figure 1 Visual representation of (a) snake grass (b) banyan (c) pineapple fibre used as
reinforcement materials (see online version for colours)
2.2 Method of FRL preparation
Compression moulding was used to produce sandwich composites reinforced with natural
fibres illustrated in Figure 2. Polymer laminate has been used as the mid-layer of the fibre
mat, and it has a hole diameter of 8 mm at equal intervals. The first, second, and third

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sandwich composite sample the compositions of snake grass fibre mat with HDPE, HIPS,
PC polymer laminate, and the concerned fibre with specific treatment of Alkali,
Potassium permanganate, and BP. The fourth, fifth, and sixth sandwich composite sample
has the compositions of a banyan fibre mat with HDPE, HIPS, and PC polymer laminate,
and the fibre undergoes distinct chemical treatment of Potassium permanganate, BP, and
alkali. The seventh, eighth, and ninth composite sample has the composition of pine apple
fibre mat with HDPE, HIPS, and PC polymer laminate with the specific treatment of BP,
alkali, and potassium permanganate. Similar sandwich composite combinations were
prepared using epoxy resin with hardener. Tensile and flexural test specimens were cut
from the fabrications in accordance with ASTM D638 and ASTM D790. A schematic
representation diagram of the fibre-reinforced polymer laminate composite sandwich is
shown in Figure 3, and Figure 4 demonstrates the process by which the reinforced
polymer laminate sandwich composite was created.
Figure 2 A compression moulding machine aids to fabricate the composite (see online version
for colours)
2.3 Mechanical evaluation
2.3.1 Tensile test
To perform the tensile test, it was necessary to prepare fabricated specimens according to
the guidelines outlined in ASTM D638. The precision tensile test was conducted and
executed by a computer-supported universal testing machine. The test involved the
examination of multiple samples of natural fibre-reinforced sandwich composites, with
four replicates of each type being analysed. The resulting data was then used to calculate
the average values. When measuring tensile stress, the stress value is considered
concerning the strain rate.
2.3.2 Flexural test
The flexural test specimens were prepared following the guidelines outlined in ASTM
D790. The use of a universal testing machine managed by a computer to execute the
three-point flexural test per the requirements of standard ASTM D790-2003. The

272 T. Ganapathy et al.
specimen in this experiment was loaded in the middle and supported at both ends by the
flexural fixture. Both the stress and strain due to bending were determined.
Figure 3 Schematic of sandwich composites (see online version for colours)
Figure 4 Fabrication of FRL (see online version for colours)

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2.4 Taguchi method
Taguchi was used with excellent efficacy across many manufacturing domains, which
benefited from its application to optimise the multi-response characteristic of complicated
situations based on grey relational analysis (Navaneethakrishnan and Athijayamani,
2017; Rajan et al., 2019). The Taguchi method is appropriate for single-response
optimisation. However, in nature, engineering applications need multi-response
optimisation. Therefore, Taguchi with grey relational analysis, effectively converts
multiple responses to their corresponding single response. An S/N ratio is computed from
the experimental data. The verified data statistics are regarded as experiment responses.
higher is better (HB), nominal is best (NB), and lower the better (LB) are the three-tier
categories for analysing performance attributes using the S/N ratio (Ravi Kumar et al.,
2017).
10 2
1
1
1
10 log n
HB ii
SN y
n

 

 (1)
10
1
10log
NB e
SN V
n

 
 (2)
2
10 1
1
10log n
LB i
i
SN y
n

 

 (3)
In which n signifies the total number of samples, yi is the detected response, and Ve is
variance.
Within zero to one, responses (tensile and flexural strength) are normalised in grey
relational analysis. The term ‘grey relational generation’ describes this method. HB, NB,
and LB are normalised (Pawar et al., 2020; Rajan and Kumar, 2018). These equations are
utilised to calculate the normalised values for HB, NB, and LB.
() ()
*
(,) ()
(,) min (,)
() max ( ) min ( )
oo
ii
ioo
ii
xk xk
Xk
x
kxk

 (4)
() ()
*
() ()
max ( ) ( )
() max ( ) min ( )
oo
ii
ioo
ii
xkxk
Xk
x
kxk

 (5)
() ()
*
() ()
()
() 1 max ( )
oo
i
ioo
i
xkx
Xk
x
kx

  (6)
where *(,)
i
X
k is the value next to the normalisation; ()
max . ( )
o
i
x
k is the significant value
of ()
()
o
i
x
k for the kth responses and ()
min . ( )
o
i
x
k is the lowest value of ()
()
o
i
x
k for the k
responses.
After normalisation, the following formula is used to determine the grey relational
coefficient.
min max
0max
:() ()
i
i
ζ
ξkkζ


(7)

274 T. Ganapathy et al.
where **
00
|| () ()||
ii
x
kxk  express the variance between the absolute values *
0()
x
k and
*(),
i
x
k ζ is the distinguished coefficient, **
min 0
min min || ( ) ( ) ||
i
ji k
x
kxk
 
  is the smallest
value of ∆0i and max 0
maxmax|| () ()||
j
ji k
x
kxk
 
  is the most significant value of ∆0i.
The grey relational grade was derived from the premeditated grey relational
coefficient as
1
1()
n
ii
k
γξk
n
 (8)
where n represents the number of process responses. When the grey relationship grade is
high, it indicates that the associated fabrication process parameters are among the best
possible rankings. A high relational grade designates a strong relationship between the
reference and comparability sequences. The main objective of deciding the fabrication
process parameters is maximising mechanical properties. In this study, our investigation
was carried out with three different control parameters; fibre type (f), fibre chemical
treatment (c), and Polymer laminate (l) individually, at three diverse levels. For precise
analysis, an L9 orthogonal array was used.
3 Results and discussion
Table 2 cites the control parameters for the process and their corresponding values. Since
this study aims to maximise the characteristics range of tensile and flexural properties, it
was determined that the greater the process responses, the better they would be for data
pre-processing. The experimental layout employs the L9 orthogonal array and displays
the output responses in Table 3.
Table 2 Parameters and levels for fabrication
Sl.
no. Parameters Notation Levels
1 2 3
1 Fibre type f Snake grass Banyan Pineapple
2 Polymer laminate l HDPE HIPS PC
3 Fibre chemical
treatment
c NaOH Potassium permanganate
(KMnO4)
Benzoyl
peroxide (BP)
Table 3 The experimental layout employing the L9 orthogonal array
Sl.
no.
Parameters Output responses
Fibre type (f) Polymer
laminate (l)
Fibre chemical
treatment(c)
Tensile
strength (MPa)
Flexural
strength (MPa)
1 1 1 1 73.3 121.7
2 1 2 2 72.0 103.3
3 1 3 3 92.0 74.2
4 2 1 2 87.3 105.4
5 2 2 3 89.3 82.6

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ation 275
Table 3 The experimental layout employing the L9 orthogonal array (continued)
Sl.
no.
Parameters Output responses
Fibre type (f) Polymer
laminate (l)
Fibre chemical
treatment(c)
Tensile
strength (MPa)
Flexural
strength (MPa)
6 2 3 1 104.9 81.5
7 3 1 3 109.6 83.4
8 3 2 1 108.2 101
9 3 3 2 98.2 88
3.1 Development of regression model
The obtained TS and FS results of the fabricated sandwich composites are fed into
Minitab Software (Version 21.3) for estimating its significance on the conducted
experiments. A coded linear with interaction regression model was created to fit the
results, equation (9) for TS and equation (10) for FS.
Tensile strength (TS) 42.8 34.15 28.76 28.6 15.47 6.13 4.7
f
l c fl fc lc      (9)
Flexural strength (FS) 165 13.2 34.9 0.4 9.17 4.43 1.6
f
l c fl fc lc      (10)
The outcomes from the variance analysis (ANOVA) for the created models are given in
Tables 4 and 5. These tables include the contents such as degrees of freedom (DF), the
sum of squares (SS), mean square (MS), P and F values. The ANOVA tables imply that
the fitted models are significant with p < 0.5 and have a confidence level of 95%. The
ANOVA of TS (Table 4) implies that the fabrication factor fibre type and the interaction
of fibre type with polymer laminate influence more on the output response. At the same
time, the case of FS (Table 5) implies that the fabrication factor of polymer laminate and
the chemical treatment influence more on the output response more. The R2 of the fitted
models are 0.96 and 0.95 for TS and FS, respectively. In terms of statistics, the value of
R2 implies the influence of the independent variables over the dependent variables. The
value of R2 nearing the unity determines the significance of this experiment.
Table 4 Results of ANOVA for TS
Source DF Seq SS Contribution Adj. SS Adj. MS F-value P-value
Model 6 1,493.85 96.32% 1,493.85 248.98 8.72 0.106
Linear 3 1,138.99 73.44% 609.82 203.27 7.12 0.126
f 1 1,032.28 66.56% 437.39 437.39 15.31 0.040
l 1 103.34 6.66% 310.11 310.11 10.86 0.081
c 1 3.37 0.22% 58.20 58.20 2.04 0.290
2-way interaction 3 354.86 22.88% 354.86 118.29 4.14 0.201
f*l 1 310.25 20.00% 279.26 279.26 9.78 0.089
f*c 1 18.84 1.21% 43.82 43.82 1.53 0.341
l*c 1 25.77 1.66% 25.77 25.77 0.90 0.442
Error 2 57.13 3.68% 57.13 28.56
Total 8 1,550.98 100.00%

276 T. Ganapathy et al.
Table 5 Results of ANOVA for flexural strength
Source DF Seq SS Contribution Adj. SS Adj. MS F-value P-value
Model 6 1,774.09 95.55% 1,774.09 295.681 7.16 0.128
Linear 3 1,546.08 83.27% 470.46 156.821 3.80 0.215
f 1 119.71 6.45% 64.87 64.869 1.57 0.337
l 1 743.71 40.06% 456.50 456.504 11.05 0.080
c 1 682.67 36.77% 0.01 0.013 0.00 0.988
2-way interaction 3 228.01 12.28% 228.01 76.002 1.84 0.371
f*l 1 161.60 8.70% 98.13 98.134 2.38 0.263
f*c 1 63.42 3.42% 22.88 22.881 0.55 0.534
l*c 1 2.99 0.16% 2.99 2.987 0.07 0.813
Error 2 82.60 4.45% 82.60 41.298
Total 8 1,856.68 100.00%
3.2 Optimisation of the conditions for TS and FS
Table 6 displays the S/N ratio and normalised S/N ratio values for TS and flexural
strength (FS). The value of the distinguishing coefficient ζ is assumed to be 0.5 (Javed
et al., 2018; Almetwally, 2020). The grey relational coefficient and grade values for each
experiment were calculated using equations (7) and (8). Based on Table 7, the experiment
design determined that the test number 8 fabrication parameter setting has the highest
grey relational grade. The eighth experimental test yielded the highest values for TS and
FS. Next, the average grey relational grade for each level of fabrication parameters must
be determined. The grey relational grades were used for this and were sorted by
parameter and level for ease of use.
Table 6 Normalised S/N ratios and S/N ratios for both TS and FS
Test
no.
Response I (TS) Response II (FS)
S/N ratio Normalised S/N ratios S/N ratio Normalised S/N ratios
1 37.30030 0.38257 41.70581 1.00000
2 37.14786 0.35745 40.28201 0.66871
3 39.27812 0.70857 37.40808 0.00000
4 38.82426 0.63377 40.45681 0.70938
5 39.01703 0.66554 38.33960 0.21675
6 40.41427 0.89584 38.22315 0.18965
7 40.79938 0.95932 38.42332 0.23623
8 40.68254 0.94006 40.08643 0.62320
9 39.83781 0.80083 38.88965 0.34473
3.2.1 Determination of parameter ranking
The grey relational grade values for maximum TS and flexural strength are shown in
Figure 5. The response graph is plotted using average grey relational grade for several

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s
ation 277
factor levels, shown in Figure 6. In Table 8, the highlighted values indicate better
fabrication performance. Parameter C obtained the highest typical peak of grey relational
grade result in level 1. Simultaneously, parameters A and B received the highest average
peak of grey relational grade results in level 3 and level 1. The optimal value of the
process parameter setting was C1B1A3.
Table 7 Grey relational coefficient and grey relational grade values for responses
Test
no.
Grey relational coefficient Grey relational
grade Rank
Response I Response II
1 0.4475 1.0000 0.7237 2
2 0.4376 0.6015 0.5195 7
3 0.6318 0.3333 0.4826 9
4 0.5772 0.6324 0.6048 4
5 0.5992 0.3896 0.4944 8
6 0.8276 0.3816 0.6046 5
7 0.9248 0.3956 0.6602 3
8 0.8930 0.5703 0.7316 1
9 0.7151 0.4328 0.5740 6
Table 8 Response table for the mean grey relational grade
Parameter Level 1 Level 2 Level 3 Max – Min
Fibre type (f) 0.575 0.568 0.655 –0.007
Polymer laminate (l) 0.663 0.582 0.554 0.109
Fibre chemical treatment (c) 0.687 0.566 0.546 0.121
Error 0.597 0.595 0.606 0.003
Figure 5 The grey relational grade for maximum TS and FS (see online version for colours)

278 T. Ganapathy et al.
The optimal process parameters include HIPS polymer laminate type, NaOH fibre
chemical treatment, and pineapple fibre. The maximum and minimum values listed in
Table 8 for the mean grey relational grade are 0.687 for fibre chemical treatment, 0.663
for polymer laminate, and 0.655 for the fibre category. The maximum (maxi-min) value
obtained in this instance is 0.687. It indicates that the chemical treatment is the most
controllable fabrication parameter for multi-response characteristics. Chemical
treatments, polymer laminate, and fibre category are the most crucial suitable process
parameters for the multi-response characteristics (i.e., 0.687 > 0.663 > 0.655).
Figure 6 Response graph for average grey relational grade (see online version for colours)
3.3 Effect of fabrication factors on the output response
The fibre type affects the overall strength and stiffness of the composite material
(Ganapathy et al., 223). High-strength natural fibres can yield improved tensile and
flexural strength and also offer a balance between strength and sustainability (Ganapathy
et al., 2019b; Kumar et al., 2019). Figure 7 shows the effect of fibre types on the output
responses of TS and FS. When we compare the TS of the fibre types, it is evident that the
pineapple fibre gives the dominant followed by the banyan and snake grass and for FS it
is vice versa the snake grass fibre gives the foremost strength followed by pineapple and
banyan fibres. When we compare the performance of each fibre, pineapple fibre gives
better-combined strength than the other two fibres.
The choice of polymer laminate material can influence the adhesion between fibres,
leading to bonding (Sinha et al., 2017; Gokul et al., 2017). The properties of the polymer,
including its stiffness, ductility, and resistance to environmental factors, impact the
overall strength of the composite (Caminero et al., 2021). Proper selection of the polymer
laminate can enhance the load-bearing capacity of the composite (Rajan et al., 2019;
Amjad et al., 2022). Figure 8 shows the effect of polymer laminates on the output
responses. The ANOVA results (Table 4 and Table 5) of this research prove that the
polymer laminates and their interaction with the fibre type play a significant role in the
output responses. When we compare the TS of the various polymer laminates it is evident

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comprehensive investigation on the fabrication parameter optimi
s
ation 279
that PC gives the enhanced performance whereas for FS it is the HDPE that gives the
optimum result (Hao et al., 2020; Ayyanar et al., 2022). While we investigate the
combined performance, HDPE is recommended.
Figure 7 Effect of fibre type on the responses (see online version for colours)
79.10
93.83
105.33
99.73
89.83 90.80
0.00
20.00
40.00
60.00
80.00
100.00
120.00
Snake grass Banyan Pineapple
Average Response
Fibre Type
Tensile strength (MPa)
Flexural strength (MPa)
Figure 8 Effect of polymer laminate on the responses (see online version for colours)
90.07 89.83
98.37
103.50
95.63
81.23
0.00
20.00
40.00
60.00
80.00
100.00
120.00
HDPE HIPS PC
Average Response
Polymer Laminate
Tensile strength (MPa)
Flexural strength (MPa)
Chemical treatments of fibres can modify the surface properties and improve the
compatibility with the polymer matrix. The chemical treatment can also reduce the
moisture absorption of natural fibres, making the natural composite more resistant to
environmental degradation (Neto et al., 2022). Figure 9 shows the effect of fibre chemical
treatment on the output responses. When we compare the TS, the fibres treated with BP
and sodium hydroxide give an enhanced result followed by potassium permanganate
treatment. However, in the case of FS, it is sodium hydroxide and potassium
permanganate treatment give the optimum strength. As a combination of responses
sodium hydroxide fibre treatment is recommended for optimum conditions.

280 T. Ganapathy et al.
3.4 FESEM analysis of fractography specimens in tensile load
Using an EVO-18ZEISS Field Emission Scanning Electron Microscope, tensile
specimens were analysed by fractography (FESEM) of the second and seventh
specimens. The selected specimens are based on the minimum and maximum output
response tensile results.
Figure 9 Effect of fibre chemical treatment on the responses (see online version for colours)
95.47
85.83
96.97
101.40 98.90
80.07
0.00
20.00
40.00
60.00
80.00
100.00
120.00
Sodium
hydroxide
Potassium
permanganate
Benzoyl
peroxide
Average Response
Fibre Chemical Treatment
Tensile strength (MPa)
Flexural strength (MPa)
According to FESEM morphological analysis, the principal causes of failure in FRL
composites include fibre pull-out, fibre fracture, matrix cracking, hole size, delamination,
plastic sheet tear, and voids. Most failures were caused by the size of the holes and the
torn plastic materials. The failure mechanism is depicted in Figure 10(a). demonstrates
the epoxy matrix’s brittle nature and the HIPS polymer laminate’s pull-out. Due to the
extent of the hole’s diameter and short epoxy matrix fill over the composite, the samples
contain an expanded hollow. Some KMnO4. treated woven snake grass fibres separate
from the woven surface and escape through the perforations of the HIPS polymer
laminate. An incompatibility between the snake grass fibres and epoxy matrix causes
matrix fractures. There is no change in stiffness between layers due to the matrix crack;
nonetheless, the laminate is compromised due to the initiation of layer delamination.
Figure 10 (a), (b) FESEM image of the fractured tensile specimen (see online version for colours)

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As observed by the FRL composite fractography, of specimen seven, failure approaches
of the seventh specimen maximum tensile load FESEM samples are shown in
Figure 10(b). FRL pineapple fibre, BP, and HDPE laminate composite specimens
damaged by a tensile force showed damage at both the top and bottom layer zone,
although the HDPE polymer laminate interface layer shows damage first because of the
hole diameter. Since bending causes compressive stress, the delamination width is most
significant in the loading zone on the top surface. Some delamination occurs due to
bonding between the top fibre layer and the following perforated polymer layer.
4 Conclusions
This research work comprehensively investigated the three categorial fabrication
parameters such as natural fibre type (f), polymer laminate (l), and fibre chemical
treatment (c) that influence the mechanical properties of the sandwich composite. The
following observations were made;
 The addition of NaOH to pineapple fibre notably enhanced the composite qualities.
Experimental findings emphasised the collective influence of chemicals, laminate,
and mat fibre type on the improved abilities of the composites.
 Significantly, chemical treatment emerged as the paramount factor, surpassing fibre
and laminate contributions, in strengthening tensile and flexural responses.
 Employing Taguchi’s approach and grey relational analyses proved effective for
evaluating multi-response properties, while ANOVA identified crucial stages in the
fabrication process.
 The study emphasised the pivotal role of chemical treatment in multi-response
characteristics, with controllable parameters ranked in importance as chemical
treatment, polymer laminate, and fibre type.
 FESEM micrographs provided insights into the failure mechanism and bonding
impact between fibre, matrix, and polymer laminate.
 Notably, NaOH-treated pineapple fibre showcased positive improvement results.
However, challenges in composite performance were observed, with the HIPS
laminate’s effectiveness limited by various factors.
 Optimal values for process parameters were identified as HIPS laminate type, NaOH
chemical treatment, and pineapple fibre.
 Additionally, the study highlighted the ductile character of the composites through
the analysis of 8 mm perforated polymer pattern specimens.
 In conclusion, this research contributes valuable insights into optimising process
parameters and understanding the mechanical behaviour of FRL composites.

282 T. Ganapathy et al.
5 Future scope
The future investigation path will be the development of hybrid composites utilising the
potential of natural fibres. These materials can potentially replace man-made fibre
components in medical devices for both humans and animals and in consumer and
vehicular products.
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