2. J. Inst. Eng. India Ser. D
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generate briquettes with a 1200 kg/m3
density. Compared
to raw materials, their higher density gives them a more
considerable calorific value and reduces the burning rate [1,
39–44]. Because of their increased combustion rate, they are
an excellent replacement for boiler applications. These bri-
quettes have the potential to alleviate the present fuel crisis
and serve as a cost-effective alternative fuel. Briquettes can
benefit small-scale industries such as tobacco curing, tea
drying, etc. Briquettes can be used to improve traditional
ceramics and clay ware processes because of their high calo-
rific value; they can even power boilers to generate steam
and electricity [45–50].
Much research is being done to increase the efficiency
of briquettes made from agricultural residuals to make
them more affordable. The most prominent advantages of
fabricating are that the raw materials necessary are readily
available worldwide, especially in less developed nations,
and high-efficiency briquettes may be manufactured with
low-cost machinery. Briquettes can also help reduce ocular
and respiratory illnesses in women and children due to their
compressed form [17, 51–55]. Briquettes can also be used
to safeguard the environment because agricultural leftovers
are briquetted rather than burned in the open air. They also
help to reduce deforestation by replacing wood as the most
used fuel.
Methodology
Experimental Design
The experiments are carried out as per the experimental
design obtained from Design of Experiments. It helps in car-
rying out the experiments in a systematic approach and also
provides valid data for statistical Analysis. Using Minitab
software a design layout (L24) has been obtained as shown
in Table 1. The binder is the influential factor in measuring
the responses hence binders are varied from 30 to 60 wt.%
in an increment of 10. The binders adopted are Cow dung,
Maida and Gaur Gum.
The agricultural waste such as rice husk, sugarcane husk,
groundnut shell husk have been considered as the other input
factors. The performance of briquettes has been found by
measuring parameter such as Gross Calorific value (GCV),
Ash Content, Moisture Content.
Preparation of Briquettes
The main constituents of briquettes are Rice husk, Ground-
nut shell powder, and Sugar cane husk, as shown in Fig. 1.
Cow dung, Gaur gum, and Maida have been selected as the
binders, which are represented in Fig. 2. Maida is substituted
for the edible wheat flour since it is less expensive. Rice
Husk, Groundnut shell powder, and Sugarcane husk were
obtained from nearby villages, while Cow dung, Maida,
and Gaur gum were obtained from a local grocery store. All
these materials are then sieved to remove undesirable waste
matter using a sieve size of 1700 µm. All the basic compo-
nents and binders are thoroughly combined by hand before
being compacted into 50×50 mm blocks using a Hand jolt-
ing machine. Using universal testing equipment, a pressure
of 1.6 MPa was applied to compress them to make the cor-
rect shape. Thus, obtained briquettes with 30wt.% of the
binder with Sugarcane and Rice husk are shown in Fig. 3.
Testing Methodology
To analyze the briquette performance, a Calorific value test,
Ash content test, and Carbon content test are employed. All
the tests are carried out as per the IS 1350 test method.
Calorific Value Testing
The briquette’s Gross Calorific value (GCV) is measured
through a calorific bomb in an isothermal water jacket.
The sample is buried in a known heat-capacity bomb calo-
rimeter. The main observation is a temperature rise, which
Table 1 Briquette experimental design
SI. No Binder (wt.%) Composition 1 Composition 2
Maida 30 Sugarcane husk Rice husk
Maida 40 Sugarcane husk Rice husk
Maida 50 Sugarcane husk Rice husk
Maida 60 Sugarcane husk Rice husk
Maida 30 Ground nut husk Rice husk
Maida 40 Ground nut husk Rice husk
Maida 50 Ground nut husk Rice husk
Maida 60 Ground nut husk Rice husk
Cowdung 30 Sugarcane husk Rice husk
Cowdung 40 Sugarcane husk Rice husk
Cowdung 50 Sugarcane husk Rice husk
Cowdung 60 Sugarcane husk Rice husk
Cowdung 30 Ground nut husk Rice husk
Cowdung 40 Ground nut husk Rice husk
Cowdung 50 Ground nut husk Rice husk
Cowdung 60 Ground nut husk Rice husk
Gaur gum 30 Sugarcane husk Rice husk
Gaur gum 40 Sugarcane husk Rice husk
Gaur gum 50 Sugarcane husk Rice husk
Gaur gum 60 Sugarcane husk Rice husk
Gaur gum 30 Ground nut husk Rice husk
Gaur gum 40 Ground nut husk Rice husk
Gaur gum 50 Ground nut husk Rice husk
Gaur gum 60 Ground nut husk Rice husk
3. J. Inst. Eng. India Ser. D
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yields the heat release when corrected for thermometer
errors and multiplied by the adequate heat capacity at the
mean temperature of the primary period. Additional pro-
vision is required for cooling losses, heat obtained due to
heat released by the ignition system, and heat of sulfuric
and nitric acid production from sulfur dioxide and nitrogen
in the chambers.
Determination of Ash
The sample is heated in the air for 30 min to 500 degrees,
then to 815 degrees for another 30–60 min until the con-
stant mass is maintained. Mix the air-dried material (desired
compound) thoroughly for 1 min. Weigh a clean, dry, empty
dish, add 2–3 g of material, and place it in a muffin furnace.
Fig. 1 a Rice husk, b sugarcane husk, c groundnut shell powder
Fig. 2 a Guar gam, b maida
Fig. 3 Briquettes made of sugarcane husk, and Rice husk with a cow dung, b guar gum, c maida
4. J. Inst. Eng. India Ser. D
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After the temperature treatment, cover the dish with a lid
and set it aside to cool. Weigh it and record the results, then
re-heat it to the same temperature until the mass difference
is less than 0.01 g. The differences between the two masses
provide the ash content.
Determination of Carbon
A known mass of material is heated in a glass tube by dry
nitrogen current. After passing the gas through weighed
moisture absorption tubes, the moisture percentage is com-
puted, followed by the proportion of volatile matter in the
sample. The carbon percentage is computed through Eq. 1,
where M, A, and V are moisture percent, ash percent, and
volatile matter percent, respectively.
Gray Relational Analysis to Find the Optimal Biofuel
Gray relational analysis (GRA) helps to solve a complex
problem with multi responses by converting it into a simple
single-response optimization with the help of Gray Rela-
tional Grade. Firstly, the numerical data from the experi-
ment results (GCV, ASH%, Moisture content) are normal-
ized within the limits of 0–1. Within the context of this
research, the actual values of GCV (kcal/kg) are normalized
as greater-the-better is calculated from the formula given in
Eq. 2.ASH and Moisture contents are normalized as lesser-
the-better based on Eq. 3 [15–17].
Here xk(b) is normalized value, min yk(b) is the least value
of yk(b) for the both response and, max yk(b) is the highest
value of yk(b) for both response.
Results and Discussion
The experimental results for calorific value, ash content,
and moisture content of the briquette are given in Table 2.
The highest Gross calorific value (GCV) is 4059 kcal/kg
obtained for Groundnut and Rice husk with Cow dung
(40 wt.%) as a binder. However, Sugarcane and rice husk
with Maida (30 wt.%) have obtained the lowest GCV of
3054.75 kcal/kg. As the expérimental results it is observed
that the composition gaurgum (60% wt.) as binder with
composition of sugarcane husk and rice husk, the value
(1)
F = 100 − (M + A + V)
(2)
xk(b) =
yk(b) − minyk(b)
maxyk(b) − minyk(b)
(3)
xk(b) =
max yk(b) − yk(b)
max yk(b) − min yk(b)
of ash content is low this is because of the less bulk den-
sity of gaurgum. For 60% wt. of gaurgum as binder with
composition of sugarcane husk and rice husk, the value of
moisture content is low this is because of the less % of in
the sugarcane bagasse [56–60].
A calorific value test has been conducted, and the graphs
have been plotted for different compositions. The interaction
graph between Sugarcane and Ground nut husk with binder
is shown in Fig. 4. It clearly shows their interaction.
The main effects from Fig. 5 plot show that Gaur gum
60 has the highest mean GCV of 3853.35 kcal/kg in bind-
ers, and groundnut husk has the highest mean GCV of
3709.22 kcal/kg. The highest average GCV is given by Gaur
gum 60, and groundnut husk is 3870.1 kcal/kg.
From the interaction plots (Fig. 6), Gaur gum (50 wt.%)
with groundnut husk obtained an ash content of 2.34%.
However, Gaur gum (60 wt.%) with groundnut husk attained
an ash content of 2.41%. The interaction plot from Fig. 6
shows that Gaur gum (50 wt.%) with groundnut husk gives
2.34% ash, and Gaur gum (60 wt.%) with groundnut husk
gives 2.41% ash. Gaur gum (60 wt.%) shows 2.3% ash with
sugar cane husk. The ideal mixture is Gaur gum60 and sugar
cane husk for less ash content [61–65].
Table 2 Experimental results of the briquette
S. nc GCV (kcal/kg) ASH (%) Moisture
content (%)
3054.75 3.9 10.01
3373.336 3.84 9.76
3698.23 3.77 9.61
3895.06 2.77 9.33
3876.7 4.4 9.83
3711.1 3.34 9.82
3681.77 3.65 9.54
3776 3.16 10.04
4059.7 12.64 9.44
3741.6 11.38 9.63
3920.2 11.2 9.83
3828.6 10.72 9.62
3633.8 11.28 8.88
3611 11.17 8.79
3553.4 9.8 8.87
3663.5 9.71 8.84
3653.9 3.06 9.96
3636.8 2.93 10.2
3533.3 2.5 9.9
3836.6 2.3 10.2
3788.9 3.52 9.6
3629.7 2.74 10.01
3714.7 2.34 10.59
3870.1 2.41 9.78
5. J. Inst. Eng. India Ser. D
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Fig. 4 Interaction plot for GCV
Fig. 5 Main effects plot for GCV
6. J. Inst. Eng. India Ser. D
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Fig. 6 Interaction plot for ash
Fig. 7 Main effects plot for ASH
7. J. Inst. Eng. India Ser. D
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Fig. 8 Interaction plot for moisture content
Fig. 9 Main effects plot for moisture
8. J. Inst. Eng. India Ser. D
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The main effects plot from Fig. 7 shows the mean ash
content in Gaur gum (60 wt.%) and Ground nut husk are
2.355 and 5.62%,respectively. The lowest average ash con-
tent of 2.41%is given by Gaur gum (60 wt.%) and ground
nut husk [66–70].
The interaction plot from Fig. 8 shows that Cow dung
(40 wt.%) with ground nut husk has a moisture content of
8.79%. However, Maida (60 wt.%) and sugar cane husk
have a moisture content of 9.33%. Low moisture content
is observed for the briquette made of Cow dung (40 wt.%)
with Ground nut and Rice husk. From the interaction
plots Fig. 4 it can be concluded that for 30 wt.% maida the
GCV for groundnut shell husk is high and for sugarcane
husk it is low, As the binder wt.% is increased to 60 wt.
% high GCV is shown for sugarcane husk. Similar trends
were observed for gaurgum. The Cow dung (30 wt.%)
has obtained a high and low GCV for sugarcane husk and
groundnut husk respectively, however at 60 wt.% a high
value is observed for groundnut and low value for sugar-
cane husk [71–75].
The main effects plot from Fig. 9 shows that Cow dung
30 has the lowest average moisture content of 9.16%, while
Ground nut husk has the lowest average moisture content of
9.54%. Thus, Cow dung 30 and ground nut husk are the ideal
mixtures for the least moisture content.
The normalized values of the GCV, Ash, and Moisture
Content are given in Table 3.
If the value of xk(b) is one or approximately equal
to one, then that result is the best response. Hence the
best sequence is xk
�
(b) for b = (1,2,3,4,…….,24) is
(1,1,………,1).The deviation sequence of the data is cal-
culated from the Eq. 3. The Gray relational coefficient
expresses how close the values are to the optimal solution.
It is calculated with the help of Eq. 4.
where =Δk|xk�(b) − xk(b)| = différence between absolute
value and actual value of each response.
(4)
𝛾
(
xk
)
=
Δmin + 𝜉Δmax
Δk + 𝜉Δmax
(5)
Δmin = min{Δk, b = 1, 2, … 24}
Δmax = max{Δk, b = 1, 2, … 24}
Table 3 Normalized and
deviation values of the
responses
Normalized values Déviation values
SI. no GCV ASH (%) Moisture content
(%)
GCV ASH (%) Moisture
content
(%)
0 0.845 0.322 1 0.155 0.678
0.317 0.851 0.461 0.683 0.149 0.539
0.640 0.858 0.544 0.360 0.142 0.456
0.836 0.955 0.7 0.164 0.045 0.3
0.818 0.797 0.422 0.182 0.203 0.578
0.653 0.899 0.428 0.347 0.101 0.572
0.624 0.869 0.583 0.376 0.131 0.417
0.718 0.917 0.306 0.282 0.083 0.694
1 0 0.639 0 1 0.361
0.683 0.122 0.533 0.317 0.878 0.467
0.861 0.139 0.422 0.139 0.861 0.578
0.770 0.186 0.539 0.230 0.814 0.461
0.576 0.132 0.95 0.424 0.868 0.05
0.554 0.142 1 0.446 0.858 0
0.496 0.275 0.956 0.504 0.725 0.044
0.606 0.283 0.972 0.394 0.717 0.028
0.596 0.926 0.35 0.404 0.074 0.65
0.579 0.939 0.217 0.421 0.061 0.783
0.476 0.981 0.383 0.524 0.019 0.617
0.778 1 0.217 0.222 0 0.783
0.731 0.882 0.55 0.269 0.118 0.45
0.572 0.957 0.322 0.428 0.043 0.678
0.657 0.996 0 0.343 0.004 1
0.811 0.989 0.45 0.189 0.011 0.55
9. J. Inst. Eng. India Ser. D
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Within this study the value of 𝜉 is assumed as 0.5 as per
the literature [18, 19].Gray relational coefficient values are
shown in Table 4. The Gray relational grade is calculated
by taking the average of the Gray relational coefficients as
given in Eq. 6.
Here, n is the number of responses for each trial.
Using Gray Taguchi optimization technique, the feasible
parameters at which high Gross calorific value, with low ash
content and Moisture content, is obtained for the briquette
made up of Ground nut, Rice husk with Maida (60 wt.%).
Conclusions
Briquettes are prepared from powders of Rice husk, Sugar-
cane husk and Groundnut husk, which possess good energy
that can be regained upon combustion. These briquettes are
far less expensive than traditional briquettes since they are
made from remains of Argo Industrial waste. According to
(6)
𝛾i =
1
n
n
∑
k=1
𝛾
(
xk
)
the Gray Taguchi study, maida (60 wt.%), rice husk, and
sugarcane husk briquette composition have the low moisture
content, low ash content, and high GCV. It can be said that
after increasing the quantity of Maida, the GCV is increased
with decrease in ASH% and Moisture%. This implies that
the fuel efficiency is increased while reducing the pollution
factor so this can be one of the best alternatives for the pres-
ently used fuels.
The highest calorific value of 4059 kcal/kg is registered
for Sugarcane husk, rice husk with Gaur gum (60 wt.%).
Less amount of Ash content of 2.3% is noticed for Sugar-
cane husk, Rice husk with guar gum (60 wt.%). On the other
hand, briquettes composed of rice husk and Ground nut husk
with cow dung (40 wt.%) were found to have reduced mois-
ture content of 8.79%. Hence, the briquettes made from the
Agro Residues can become a major source of energy on a
large scale.
Funding Not applicable.
Availability of Data and Materials Not applicable.
Declarations
Conflict of interests The authors declare that they have no conflict
of interest.
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37. N. Praveen , U. S. Mallik, A. G. Shivasiddaramaih, R. Suresh , C
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45. M. Muralidhar Singh, M. Ajit, M. Hebbale, C. Durga Prasad,
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46. P. Mohan, H Hanumanthappa, C. Durga Prasad, H. Madhusoodan
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