Investigations on Dielectric Constant of Coir Powder-Reinforced PVC Composites

ABSTRACT

In recent times, there is an intensive growth toward investigation and creation of the green fiber composites due to its abundance and cost-effective, renewable, and environmentally-safe features. Natural fiber-based composites are rapidly replacing synthetic fiber-based composites in electrical engineering applications but being limited due to poor electrical insulation properties. Hence, an attempt is made in this study to improve the electrical insulation properties of coir fiber (powder form)/polyvinylchloride composite by optimizing the variables viz. fiber content (wt.%), particle size (in μm), and chemical treatments using Box–Behnken design. Thus, the results are optimized using the analysis of variance to achieve the low dielectric constant (2.256) for the combination of chemical treatments (triethoxy(ethyl)silane), fiber content (2 wt.%), and particle size (179.5 μm), which are suitable for the electrical insulation products. Additionally, a conformity test is executed and error was found to be 2.54%.

Graphical abstract

摘要

近年来，由于其丰富、成本效益高、可再生和环境安全的特点，绿色纤维复合材料的研究和开发得到了大力发展. 天然纤维基复合材料本质上是环保的，在电气工程应用中正在迅速取代合成纤维基复合物，但由于电绝缘性能差而受到限制. 因此，本研究试图通过使用Box-Behnken设计优化纤维含量（wt.%）、粒径（μm）和化学处理等变量来改善椰壳纤维（粉末形式）/聚氯乙烯复合材料的电绝缘性能. 因此，使用方差分析对结果进行了优化，以实现适用于电绝缘产品的化学处理（三乙氧基（乙基）硅烷）、纤维含量（2 wt.%）和粒度（179.5 μm）组合的低介电常数（2.256）. 此外，进行了一致性测试，发现误差为2.54%.pf介电常数.

KEYWORDS:

• Cocos nucifera powder
• chemical treatments
• Box–Behnken design
• P-polyvinylchloride
• hydraulic-injection molding
• resonance method

关键词:

• 椰子粉
• 化学处理
• Box-Behnken设计
• P-对聚氯乙烯
• 液压注塑

Introduction

India is the largest raw material supplier of natural fibers as a wide range of it is available through agricultural land and forests (Saravana Bavan and Mohan Kumar 2010). Natural fiber composites, also known as green composites (Mantia and Morreale 2011; Mochane et al. 2021), are widely used in a variety of applications like geo textiles, electric packaging materials (Pan et al. 2017), molded products, sorbents, filters (Zahidul Islam et al. 2022), construction materials, furniture, military (Faruk et al. 2012, Kumar et al. 2019), automotive parts (Sathishkumar et al. 2013a), aerospace industry (Sun et al. 2023, Ahmad, Choi, and Park 2014), structural beams, panels (Keya et al. 2019, Shekar Patil and Kalagi 2015), cable, wire insulation, and switch boards (Jayamani et al. 2014, Kuram and Kuram 2022). Natural fiber is biodegradable, less health hazardous, and process-friendly, has low CO₂ footprint, is recyclable (Ilyas et al. 2022; Kerni et al. 2020; Lotfi et al. 2021), and has low cost, low density, and high toughness (Kannan and Thangaraju 2022; Sathishkumar, Naveen, and Satheeshkumar 2014). Consequently, it is a preferable alternative to synthetic fibers (Maithil, Chandravanshi, and Chandravanshi 2023). Among natural fibers, coir fiber exhibits various properties such as high availability, high lignin content (Elanchezhian et al. 2018; Sathishkumar et al. 2013ba), low density, high elongation at break, and low elastic modulus (George Adeniyi et al. 2019; Kumar Saw, Sarkhel, and Choudhury 2012; Bongarde and Shinde 2014; Verma et al. 2013). The utilization of natural fiber in polymer composite is well known owing to the electrical insulating properties. An exceptional cable insulator possesses good electrical insulation and physical and mechanical properties. An insulator’s performance is improved by lowering its dielectric constant (DC; Nayak et al. 2017).

All the natural fibers are hydrophilic in nature (Dugvekar and Dixit 2022). In order to enhance the electrical insulation properties of composite materials, the interfacial adhesion strength between matrix and natural fiber has to be improved using chemical treatment methods (Nassif 2010; Nigrawa and Chand 2012; Siddika et al. 2015). Therefore, chemical treatments using sodium hydroxide (NaOH; Karthikeyan and Kalpana 2022; Sathishkumar et al. 2013) and silane (Siakeng et al. 2018) and also acetylation (Zaman and Khan 2021) are carried out with coir fiber to remove fiber surface impurities (Sudhakara et al. 2013). Chemical treatments also result in reduced water absorption capacity (Sai Priya, Raju, and Naveen 2014).

The effect of dielectric behavior in the natural fiber-reinforced polymer composites depends upon volume percentages of fiber and resin (Bongarde and Shinde 2014), characteristics of their constituent materials (Verma et al. 2013), polarizability of the material (Khouaja, Koubaa, and B 2021), cellulose in fabric (Mustata and Mustata 2014), and filler content (Nigrawa and Chand 2012). Thermoplastic polymer matrix is reinforced with natural fibers because of its biodegradability, recyclability (Huda, Huda, and Widiastuti 2021), specific strength, corrosion resistance, cost-efficiency, design versatility (Awais et al. 2020), and good electrical insulation (Nayak et al. 2017). Epoxy resin, natural rubber, and polypropylene reinforced with palm sugar (30%) and sisal and coconut fibers (25%), respectively, exhibit low DC (Ngurah Nitya Santhiarsa, Pratikto, and Marsyahyo 2014; Peng et al. 2010; V et al. 2023). The combination of 3 wt.% of boron nitride, 2 wt.% of banana fiber, and a particle size of 3 µm results in a composite material with a DC of 1.14 (Salunke and Gopalan 2022). The DC of nonpolar polymer lies between 1.8 and 2.6 and similarly for plasticized-polyvinylchloride (PVC), it lies between 3 and 5 (Nayak et al. 2017). To improve electrical properties of composites, injection molding process is incorporated to initiate the dispersion of fiber in the resin (Saba et al. 2015, Qaiss, Bouhfid, and Essabir 2015, Sapuan and Yusoff 2015.

The response surface method is a tool that implements a statistical approach to optimize natural fibers content in composite fabrication for better properties (Pravitha et al. 2021). Central composite design (Pandiselvam et al. 2022; Penjumras et al. 2015) and Box–Behnken design (BBD; Mohamad Zaki Hassan et al. 2019, Mat Kandar and Akil 2016] are well-known response surface methods. Among response surface methodology, BBD is better because it does not have axial points, has fewer design points, is less expensive to run with the same number of factors, and efficiently estimates the first- and second-order coefficients (Preetha et al. 2023; Sudha et al. 2023).

An experimental plan and further statistical analysis of data with regression model, fitting for each response, were carried out using Expert Design software version 10 (Sathishkumar et al. 2017; Srikanth et al. 2020). Analysis of variance (ANOVA) and regression equation were used in explaining the level of influence for different parameters in composite materials (Ahmad et al. 2023; Aydar et al. 2022; Venkatachalam et al. 2018; Yaghoobi and Fereidoon 2019).

From the literature, it is determined that no investigation has been carried out to analyze the electrical insulation of composite material using PVC and coir fiber in powder form. As a result, a novel study attempt is carried out in this paper to reduce the DC of coir fiber powder/PVC by optimizing the variables like fiber content (wt. %), particle size (in μm) and chemical treatments using BBD. Variables affecting the DC are also investigated.

Materials and methods

Materials

Coir fiber (Cocos nucifera) is used as reinforcing material because of its easy availability, low cost, insulating characteristics, and eco-friendly behavior. The coir fiber is supplied from Go Green Products, Chennai, India.

The chemical treatments such as NaOH, triethoxy(ethyl)silane, and potassium hydroxide (KOH) are used to improve the bonding between the polymer and coir fiber and those chemicals are purchased from Sigma-Aldrich Chemicals Private Limited, Bangalore, India.

PVC, a thermoplastic polymer, is used as matrix material because of its multipurpose properties such as low cost, durability, being lightweight, and easy processability. The physical properties of coir and PVC are analyzed and the details are given in Table 1 (Kumar Saw et al. 2012; Jammoukh et al. 2018; Rehab and Ghania 2016). Figure 1 shows the different steps of research work processes.

Figure 1. Work flowchart.

Table 1. Physical properties of coir and PVC.

PROPERTY	Coir fiber	PVC
Density (g/cm3)	1–2	1.3–1.7
Modulus (GPa)	4–6	.001–1.8
Tensile strength (MPa)	175	7–25
Elongation to failure (%)	30	100–400
Moisture absorption (%)	130–180	.2–1

Design of experiment – Box–Behnken design

The design of experiment/optimization study is carried out based on BBD tool of response surface methodology using Minitab version 16 software. It includes three levels (−1, 0, +1) for the independent variables such as fiber content (wt. %), particle size (in μm), and different types of chemical treatments. The output response is DC. In addition, fiber content [A], particle size [B], and chemical treatments [C] are elucidated in a range of 2–6 wt.%, 75–225 μm, and treatments (silane, NaOH, and KOH) as tabulated in Table 2. Table 3 presents the BBD layout for 15 runs. Twelve face edge points and three replicates of origin can be seen in Figure 2.

Figure 2. BBD for three factors.

Table 2. Parameters for experimental strategy.

Factor	Parameters	Coded levels of parameters
		−1	0	+1
A	Fiber content (wt.%)	2	4	6
B	Particle size (in μm)	75	150	225
C	Chemical treatments	1	2	3

Table 3. The arrangement of the BBD.

Sample no.	Input parameters
	Fiber content (wt.%)		Particle size (μm)		Chemical treatments
	Coded values	Physical values	Coded values	Physical values	Coded values	Physical values
1	1(+)	6	0	150	1(+)	3
2	1(-)	2	0	150	1(-)	1
3	0	4	0	150	0	2
4	1(-)	2	1(-)	75	0	2
5	1(+)	6	1(+)	225	0	2
6	0	4	1(+)	225	1(-)	1
7	0	4	1(+)	225	1(+)	3
8	0	4	0	150	0	2
9	0	4	1(-)	75	1(-)	1
10	0	4	1(-)	75	1(+)	3
11	1(-)	2	0	150	1(+)	3
12	1(+)	6	0	150	1(-)	1
13	0	4	0	150	0	2
14	1(+)	6	1(-)	75	0	2
15	1(-)	2	1(+)	225	0	2

Preparation of composites

Coir fiber is cut into small pieces (approximately 1–2 cm) using scissors. Coir fiber is heated for 1 h at 105°C in a hot air oven and then using Pulverizes Mill, the fiber is converted into powder form. Finally, coir fiber powder is sieved into three categories namely 75, 150, and 225 (μm) using a sieving machine as shown in Figure 3. These values refer to average size with a range of ±20 microns.

Figure 3. Grinding of coir fiber.

The coir fiber powder contents (2 wt.%, 4 wt.%, and 6 wt.%) in combination with size of particles (75 μm, 150 μm, and 225 μm) are chemically treated using BBD as shown in Figure 4. The following lines explain the chemical treatment procedure.

Figure 4. Chemical treatment procedure.

• For triethoxy(ethyl)silane treatment, coir fiber powder is immersed in distilled water with 2 wt.% silane for 3 h. After treatment, the coir fiber powder is thoroughly washed and then dried using hot oven at 80°C for 48 h (Asim et al. 2016).

• For NaOH treatment, coir powder is soaked in 5 wt.% NaOH solution for a period of 72 h at room temperature. Furthermore, the coir fiber powder is removed from the solution and then washed several times using fresh water. Subsequently, the coir fiber powder is washed with demineralized water. Finally, the coir fiber powder is air-dried for more than 2 days (Krishnaraj Chandrasekaran et al. 2013).

• For KOH treatment, Powdered coir fiber is treated with a solution of KOH (10 wt.%). It is kept in the alkaline solution for 36 h at 30°C. Fiber is completely washed in faucet water and it is neutralized with acetic acid solution (2%). It is again thoroughly washed in water to eradicate the acid sticking. Finally for about 48 h, it is left to dry at room temperature (Srinivasa and Bharath 2013).

• Hydraulic injection molding machine is used for fabricating all the samples. The powdered coir fiber and PVC are injected into hopper heated barrel that enhances the heating process together with the shearing action of the screw. The parameters used for manufacturing the natural fiber powder-reinforced polymer matrix composites are injection pressure of 130 MPa, injection temperature at 190°C, injection rate of 20 cm³/s, and holding pressure of 190 MPa. The cast of each composite is cured at molding temperature of 35°C, cooling time of 15 s, and holding time 10 s (Fu et al. 2011). Thus, the specimens are fabricated in the shape of rectangular blocks, sized 115 mm × 95 mm × 3 mm.

Dielectric constant measurement

DC is determined by measuring variable capacitance of standard specimen and test specimen at resonance condition with the aid of DC equipment. Originally, variable capacitor of the test sample is measured. Subsequently, standard capacitor values with and without dielectric material are noted. Similarly, the same technique is followed for other samples. Then, the average value of DC is calculated using equation (1)(1) $k=\frac{C1-C2}{C1-C3}$(1) . DC K is measured at the frequency of 5 MHz in room temperature (Tereshchenko, Buesink, and Leferink 2011) as shown in Figure 5. Rectangular samples of length 115 mm, breadth 95 mm, and thickness 3 mm are used for the study.

Figure 5. Dielectric constant (resonance method).

(1) $k=\frac{C1-C2}{C1-C3}$(1)

K= DC.

C1= Conventional variable capacitor’s capacity at resonance (maximum deflection).

C2= Conventional variable capacitor’s capacity at resonance (maximum deflection) including test capacitor with dielectric in it.

C3= The conventional variable capacitor’s capacity at resonance (maximum deflection) including test capacitor without dielectric in it.

Results and discussion

Dielectric constant by experimentation

The experimental DC values for all 15 samples are tabulated in Table 4. DC of composites ranges from 2.254 to 3.283. The highest DC value is 3.283 for the variables having fiber content (4 wt.%) and particle size (75 μm) and undergoing KOH treatment. The lowest DC value is 2.254 under the conditions which include fiber content (2 wt.%), 225 μm of particle size, and NaOH treatment. Interfacial polarization of a composite depends on coir fiber content (Jayamani et al. 2014). Increase in coir powder above 2 wt.% increases moisture absorption capability leading to increase in DC. Particle size (225 μm) in coir fiber leads to good fiber dispersion with p-PVC. Because of chemical treatment, low DCs are obtained due to less interfacial polarization (Jayamani et al. 2021).

Table 4. Experimental DC.

Sample no.	Fiber content (wt.%)	Particle size (μm)	Chemical treatments	Dielectric constant
1	6	150	3	2.299
2	2	150	1	2.481
3	4	150	2	2.754
4	2	75	2	2.720
5	6	225	2	2.381
6	4	225	1	2.592
7	4	225	3	2.963
8	4	150	2	2.754
9	4	75	1	2.652
10	4	75	3	3.283
11	2	150	3	2.598
12	6	150	1	2.353
13	4	150	2	2.754
14	6	75	2	2.889
15	2	225	2	2.254

The statistical comparative study on DC is carried out using response surface methodology, and responses with respect to the effects of the independent variables (Al-Sharify et al. 2022) are discussed in the upcoming section.

Model fitting and ANOVA for dielectric constant

Using Minitab software, the recorded data are examined. ANOVA is used to analyze the responses for model fitting and to evaluate the significance of the coefficient terms (Pragasam and Mallikarjuna Reddy 2020).

The ANOVA for quadratic model on the DC is presented in Table 5 The P-value of fiber content (wt.%) is 0.05 and the F-value of fiber content is 6.07. Hence it is statically significant. Additionally, P-values of other parameters such as (fiber content (wt.%) * fiber content (wt.%)) is fewer than 0.05. The R² value (79.63%) shows that the model is a good fit and the relationship between the dependent and the independent variables is significantly stronger. Hence the model is fit to analyze.

Table 5. ANOVA outcomes for DC.

Source	DF	Adj SS	Adj MS	F-Value	P-Value
Model	9	0.84734	0.094149	2.17	.203
Linear	3	0.39309	0.131030	3.02	.132
Fiber content (wt.%)	1	0.28408	0.284078	6.55	.051
Particle size (μm)	1	0.04037	0.040372	0.93	.379
Chemical treatments	1	0.02047	0.020473	0.47	.522
Square	3	0.45250	0.150834	3.48	.106
Fiber content (wt.%) * Fiber content (wt.%)	1	0.37221	0.372208	8.59	.033
Particle size (μm) * Particle size (μm)	1	0.05518	0.055182	1.27	.310
Chemical treatments * Chemical treatments	1	0.00005	0.000052	0.00	.974
2-Way interaction	3	0.02448	0.008161	0.19	.900
Fiber content (wt.%) * Particle size (μm)	1	0.00027	0.000272	0.01	.940
Fiber content (wt.%) * Chemical treatments	1	0.00731	0.007310	0.17	.698
Particle size (μm) * Chemical treatments	1	0.01690	0.016900	0.39	.560
Error	5	0.21672	0.043344
Lack-of-fit	3	0.21672	0.072239	*	*
Pure error	2	0.00000	0.000000
Total	14	1.06406

By executing simple regression analysis on the responses, the quadratic model for the DC of the three chosen factors is shown in Equation. (2)(2) $\begin{array}{c}\mathrm{R}\mathrm{e}\mathrm{g}\mathrm{r}\mathrm{e}\mathrm{s}\mathrm{s}\mathrm{i}\mathrm{o}\mathrm{n}\mathrm{e}\mathrm{q}\mathrm{u}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}=1.60+0.677\mathrm{A}-0.00681\mathrm{B}+0.364\mathrm{C}-0.0794{\mathrm{A}}^2+0.000022{\mathrm{B}}^2\\ -0.004{\mathrm{C}}^2-0.000055\mathrm{A}\ast \mathrm{B}-0.0214\mathrm{A}\ast \mathrm{C}-0.00087\mathrm{B}\ast \mathrm{C},\end{array}$(2)

(2) $\begin{array}{c}\mathrm{R}\mathrm{e}\mathrm{g}\mathrm{r}\mathrm{e}\mathrm{s}\mathrm{s}\mathrm{i}\mathrm{o}\mathrm{n}\mathrm{e}\mathrm{q}\mathrm{u}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}=1.60+0.677\mathrm{A}-0.00681\mathrm{B}+0.364\mathrm{C}-0.0794{\mathrm{A}}^2+0.000022{\mathrm{B}}^2\\ -0.004{\mathrm{C}}^2-0.000055\mathrm{A}\ast \mathrm{B}-0.0214\mathrm{A}\ast \mathrm{C}-0.00087\mathrm{B}\ast \mathrm{C},\end{array}$(2)

Where

A is a fiber content (wt.%),

B is a particle size (μm),

C is a chemical treatment.

From the regression equation (2)(2) $\begin{array}{c}\mathrm{R}\mathrm{e}\mathrm{g}\mathrm{r}\mathrm{e}\mathrm{s}\mathrm{s}\mathrm{i}\mathrm{o}\mathrm{n}\mathrm{e}\mathrm{q}\mathrm{u}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}=1.60+0.677\mathrm{A}-0.00681\mathrm{B}+0.364\mathrm{C}-0.0794{\mathrm{A}}^2+0.000022{\mathrm{B}}^2\\ -0.004{\mathrm{C}}^2-0.000055\mathrm{A}\ast \mathrm{B}-0.0214\mathrm{A}\ast \mathrm{C}-0.00087\mathrm{B}\ast \mathrm{C},\end{array}$(2) , DC values for all 15 samples are calculated by substituting the corresponding fiber content (wt.%), particle size (μm), and chemical treatments as presented in Table 6.

Table 6. Dielectric constant (regression equation).

Sample no.	Fiber content (wt.%)	Particle size (μm)	Chemical treatments	Dielectric constant
1	6	150	3	2.506
2	2	150	1	2.440
3	4	150	2	2.897
4	2	75	2	2.897
5	6	225	2	2.494
6	4	225	1	2.788
7	4	225	3	2.921
8	4	150	2	2.897
9	4	75	1	2.983
10	4	75	3	3.377
11	2	150	3	2.789
12	6	150	1	2.448
13	4	150	2	2.897
14	6	75	2	2.836
15	2	225	2	2.588

Experimental and theoretical DCs are compared for all 15 samples. The error (%) is calculated and found to be in range −1.68% to 12.907%, which are tabulated in Table 7. Error is less than 10% except for two samples. Few samples’ errors are more than 5%. Samples below average exhibit errors more than 5%.

Table 7. Comparison between experiment and regression equation for DC.

Run no.	Dielectric constant (Experiment)	Dielectric constant (Regression equation)	Error %
1	2.299	2.506	8.26
2	2.481	2.440	−1.68
3	2.754	2.897	4.936
4	2.720	2.897	6.11
5	2.381	2.494	4.531
6	2.592	2.788	7.038
7	2.963	2.921	−1.419
8	2.754	2.897	4.966
9	2.652	2.983	11.104
10	3.283	3.377	2.799
11	2.598	2.789	6.865
12	2.353	2.448	3.908
13	2.754	2.897	4.966
14	2.889	2.836	−1.532
15	2.254	2.588	12.907

Effects of interactions on dielectric constant

Response surface 3D plot of interaction

Figure 6 demonstrates the surface 3D plot of interaction among input variables such as fiber content (%), particle size (μm), and different types of chemical treatments on DC behavior.

Figure 6a. Surface plot of DC vs. particle size (μm) and fiber content (%).

Figure 6b. Surface plot of DC vs. chemical treatment (%) and fiber content (%).

Figure 6c. Surface plot of DC vs. chemical treatment (%) and particle size (μm).

Figure 6a illustrates the surface 3D plot on DC vs. particle size (μm)/fiber content (wt.%). It is inferred that low DC is observed for two combinations: 1.2 wt.% of fiber content/160 μm of particle size and 2.6 wt.% of fiber content/160 μm of particle size.

Main effects for dielectric constant

Figure 7(a) shows that rise in the fiber content from 2 wt.% to 4 wt.% increases DC but also a decrease (2.82 to 2.44) is observed from 4 wt.% to 6 wt.% of fiber content. Figure 7b shows that DC decreases when particle size is increased from 75 μm to 225 μm. Figure 7c reveals that DC is low for triethoxy(ethyl)silane chemically treated FRP (Fiber Reinforced Polymer) composites. When a silanol molecule from the triethoxy(ethyl)silane interrelates with the cell wall of coir powder, silanation occurs. The hydroxyl groups (lignin, hemicellulose, and pectin) existing in the coir powder are reduced, thereby increasing cellulose content. As a result, good interfacial bond is created, which leads to decrease in the DC. Larger amounts of lignin, hemicellulose, and pectin are removed by triethoxy(ethyl)silane compared to other chemical treatments. Hence, the silane treatment leads to lower DC in comparison to other treatments (Asim et al. 2016; Sunthrasakaran et al. 2019).

Figure 7. Main effects plot for DC.

Pareto charts of the standardized effects on dielectric constant

Figure 8 demonstrates the impact of various factors of the simple regression equation on the DC. The influence of fiber content and particle size shows significant effect on the DC.

Figure 8. Pareto chart of the standardized effects.

Verification and optimization of the model

In Figure 9, response optimization plot for DC is shown, with Y-axis displaying DC and X-axis displaying fiber constant (wt.%), particle size (μm), and different types of chemical treatments. It reveals that the set of triethoxy(ethyl)silane treatment, fiber content of 2 wt.%, and particle size of 179.54 (μm) offers low DC.

Figure 9. Response optimization plot.

To attain good electrical insulation properties, it is essential to recognize the maximum significant of each parameter by satisfying composite desirability (Salunke and Gopalan 2022). Thus, the optimized combination provides low DC as stated in Table 8.

Table 8. Criterion for optimization.

Solution	Fiber content (wt.%)	Particle size (μm)	Chemical treatments	DC fit	Composite desirability
1	2	179.54	1	2.25	1

Table 9 is a comparative analysis of our optimization process, which displays the error analysis for DC between optimization and experimentation values. Error is 2.54% only, which shows the authenticity of the optimization process.

Table 9. Optimized set of variables.

Trail no.	Fiber content (wt.%)	Particle size (μm)	Chemical treatments	DC	Error %
1	2	179.54	1	2.19 (By experimentation)	2.54
2	2	179.54	1	2.25 (By optimization)

Conclusion

This paper reports the influence of fiber content (wt.%), particle size (μm), and different types of chemical treatments on DC of coir fiber-reinforced PVC composite. Initially, coir fiber is powdered and then chemically treated (NaOH, KOH, and triethoxy(ethyl)silane) using BBD. Using hydraulic injection molding, chemically treated fiber powders are reinforced with PVC to manufacture the samples.

The manufactured samples are experimentally tested for DC using resonance method. Furthermore, ANOVA and regression analysis are performed using Minitab software to find the effect of fiber content (wt.%), particle size (μm), and different types of chemical treatments on output response. The response surface 3D and main effects plots are obtained to examine the effects of fiber content (wt.%), particle size (μm), and different types of chemical treatments on DC. Errors are calculated among experimental values and regression equation values to find the deviation.

Experimentally, low DC value of 2.19 is attained for the set of fiber content (2 wt.%), particle size (179.545 μm), and triethoxy(ethyl)silane. Coir fiber is added to the composite to improve its ability to degrade and be recycled. The composite’s green content is increased by its incorporation of coir fiber. It is concluded that with persistent and systematic research on fiber-reinforced thermoplastic polymer composites, there will be good opportunity and better future in electrical applications requiring insulation such as microchips, parts of transformers, terminal, connectors, switches, circuit boards, etc.

Highlights

• BBD approach is used for designing the experiments.

• Injection molding machine is used to fabricate the composites.

• ANOVA is used to identify the relevance of individual process variables.

• Silane and fiber content (2 wt.%) with size (179.545 μm) gives the lower DC.

• Lower DC functions as an insulator for electronic products.

Authors contribution

Aravindh: Software, Validation, Formal analysis, Investigation, Resources, Data Curation, Writing – Original Draft, Writing – Review and Editing, Visualization, and Project Administration. Gopalan Venkatachalam: Conceptualization, Methodology, Resources, and Supervision.

Acknowledgements

The authors wish to express their gratitude to Strength of Materials Laboratory, School of Mechanical of engineering, VIT, for their testing facility.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The author(s) reported that there is no funding associated with the work featured in this article.