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The objective of this paper is optimization mixing parameters in terms of mixing process

of polymer nanocomposites using Taguchi method. Considering the mixing parameters such as

rotational speed, mixing temperature and mixing time were performed to reveal the electrical

conductivity data. Taguchi method was used by electrical conductivity analyses based on three level

factorial designs. Orthogonal arrays of Taguchi, the signal-to-noise (S/N) ratio, and the analysis of

variance (ANOVA) were utilized to find the optimal levels and the effect of mixing parameters on

electrical conductivity. Confirmation analysis measurements with the optimal levels of mixing

parameters were carried out in order to show the optimum electrical conductivity of Taguchi

method. The result shows that Taguchi method is effective in solving the quality problem occurred

on the mixing parameters of the polymer nanocomposites.

The mixing parameters play important factor in modifying the desirable electrical conductivity of

the polymers nanocomposites. Currently, melt mixing compounding [1–4], in situ polymerization

[5-8] and coagulation [9, 10] are widely used to prepare the nanocomposites. The coagulation and

in-situ polymerization processes generally produce higher levels of nanoparticle dispersion, but the

melt mixing compounding to be familiar due to its compatibility with current industrial

compounding facilities and also kindly and economically on the environmental process for the

absence of solvents. Since the main problem of the polymer composite plate is low electrical

conductivity, combination of high concentration of graphite and additional conductive fillers on

these polymer composite plates is necessary to improve electrical conductivity [11-13]. The

reinforced fillers commonly used including carbon nanotube, carbon fibre, and carbon black which

have been incorporated into the composites to enhance overall performance of composite plates by

conventional polymer processing technique [13, 14]. Although significant improvement in electrical

conductivity and reduction in interfacial area specific resistance were realized, very high filler

loadings are still needed to meet electrical conductivity targets. Wolf et al. [15] developed a liquid

crystal polymer composite bipolar plate by compression molding while the conductive fillers were a

combination of carbon blacks and carbon fibres, and the loading concentration in the composite was

below 40 vol%. However, conductivity less than 6 S/cm was achieved although the bipolar plate

had excellent gas barrier properties and mechanical properties. Dweiri et al. [16] studied

PP/graphite/CB composite bipolar plates by compression molding process, and the electrical

conductivity obtained was only around 35 S/cm even at graphite loading as high as 80 wt%. Similar

work was also done by Yin et al. [17]. Very high loading of 85 wt% graphite powder was required

to reach 100 S/cm of the electrical conductivity.

Applied Mechanics and Materials Vols. 52-54 (2011) pp 31-36Online available since 2011/Mar/28 at www.scientific.net© (2011) Trans Tech Publications, Switzerlanddoi:10.4028/www.scientific.net/AMM.52-54.31

All rights reserved. No part of contents of this paper may be reproduced or transmitted in any form or by any means without the written permission of TTP,www.ttp.net. (ID: 152.2.176.242, University of North Carolina at Chapel Hill, Chapel Hill, USA-02/10/14,05:00:07)

In spite of the critical importance of processing parameters to produce the qualified polymer

nanocomposite, nevertheless less attention has been given to use optimization of mixing parameters,

especially for polymer nanocomposites. In this study optimization of mixing parameters on the

electrical conductivity of polymer nanocomposites based on the Taguchi method was investigated.

Polymer nanocomposites were prepared by melt compounding. Synthetic Graphite (G)

used in this study has electrical resistivity of 0.03 Ω-cm, surface ratio of 1.5 m2/g and an average

particle size of 74 µm. It was purchased from Asbury Carbons, New Jersey. Multi walled carbon

nanotubes (MWCNTs) NC 7000 type was purchased from Nanocyl, Belgium. The diameter is 9.5

nm, and length is 1.5 µm, with purity ≥90%, reported by manufacturer. The epoxy resin was a

bisphenol-A based epoxy resin (635), with viscosity 6 Poise was obtained from US Composites.

The curing agent, 4-Aminophenylsulphone was received from New Jersey, USA. The curing agent

was the diamine type (tetra functional) to facilitate rapid and dense cross-linking of epoxy resins. A

lower viscosity of epoxy matrix was selected for better wetting conditions with conductive fillers.

The epoxy and curing agent were mixed with ratio 3:1

in wt.%. The mixing of CNTs/G in epoxy was produced by three stages. In first stage, milling of

mixture CNTs and G with different (wt%) concentration was conducted using planetary ball mill to

get homogen mixer . The ball to powder ratio that had been used was 4:1 with stainless balls 10 mm

in diameter at rotating speed of 200 rpm for one hour. In the second stage, EP and curing agent was

mixed using the high speed mechanical mixer (RW 20-KIKA-WERK) at 1200 rpm for 40 s. Third

stage, CNTs/G further mixed using internal mixer with a Haake torque rheometer with various

rotational speed 20, 25, 30 rpm, mixing time 5, 10, 15 min, and mixing temperature 30, 35, 40 0C as

a control factor. The composite mixtures were poured into a steel mould at curing temperature 150

°C and curing pressure was maintained at 12 MPa for 1.5 hours. The electrical conductivity of the

nanocomposites were measured using a Jandel Multi Height Four-Point Probe combined with a

RM3 Test Unit. It has a constant-current source and digital voltmeter. This equipment is able to

measure sheet resistance in the range from 1mΩ/cm up to 5×108 Ω/cm and volume resistivity range

from 10-3

to 106 Ω-cm.

Three parameters used on this research were rotational speed,

mixing temperature, and mixing time. Research parameters as the control factors mainly affect the

output of the objective or the electrical conductivity value. Table 1 lists three control factors and

their levels, which are rotational speed A = 20, 25, 30 rpm, mixing time B = 5, 10, 15 min, and

mixing temperature C = 30, 35, 40 0C.

Table 1. Control factors and their levels for mixing parameters

Symbol Control Factors Units Level 1 Level 2 Level 3

A Rotational speed rpm 20 25 30

B Mixing time min 5 10 15

C Mixing temperature 0C 30 35 40

The least number of experiment trials can be achieve by orthogonal array

(OA), which the configuration is based on the total degree-of-freedom (DOF) of the objective

function. The DOF is given as eight since there are three control factors with three levels in this

study. To make the performance comparisons among different combinations of control factors, it is

necessary to select an OA having at least nine experimental trials (DOF + 1). Therefore, the

standard L9(33) OA as listed in Table 2 is selected for study.

32 Advances in Mechanical Engineering

Table 2. L9 (33) orthogonal array

Trial number L9 Control factor level

A B C

1 1 1 1

2 1 2 2

3 1 3 3

4 2 1 2

5 2 2 3

6 2 3 1

7 3 1 3

8 3 2 1

9 3 3 2

Since the objective of this study is to obtain the maximum values of the electrical

conductivity, then the larger the better is used to examine quality characteristic by The Taguchi

method, which is defined as:

η = -10 log (MSD) (1)

where MSD is the mean-square-deviation of the objective function, and is given as

MSD = 2 (2)

where n is the number of repeated experiments for each combination of control factors, and yi is the

measured electrical conductivity of the polymer nanocomposites at its repeating experiment.

!

The experimental results of mixing parameters based on L9(33) OA are shown in Table 3. For every

combination of control factors, three measurements were performed. According to the measured

results, the maximum value of the electrical conductivity and mean value are 194.4852 S/cm and

156.6229 S/cm, respectively. To provide an efficient method on improving the electrical

conductivity is the main issue to be studied in this study. Based on Eq. 1, the measured electrical

conductivity was used to evaluate the quality characteristics by S/N ratios.

Table 3. Experimental results of mixing parameters based on L9(33) OA

Trial

no.

Control Factor Electrical conductivity

[S/cm]

S/N

[dB]

A [rpm] B [min] C [0C] y1 y2 y3

1 20 5 30 152.2522 159.098 148.811 43.7058

2 20 10 35 187.312 189.342 193.2917 45.5720

3 20 15 40 192.2917 194.4852 187.5195 45.6373

4 25 5 35 157.0495 151.982 155.8195 43.8013

5 25 10 40 148.6396 149.7996 153.5996 43.5585

6 25 15 30 139.5996 137.0495 136.6396 42.7815

7 30 5 40 122.0045 126.2522 119.086 41.7515

8 30 10 30 132.2522 135.0495 138.8113 42.6254

9 30 15 35 172.8113 168.4852 179.4852 44.7819

The effect of each factor level on the quality characteristic was obtained from S/N ratios. The

effect is defined as the variance from the total mean value , which is calculated as 43.80 dB.

Because the experimental design is an orthogonal array, it is possible to isolate the effects of the

control factors at different levels, and the mean S/N ratios for every control factor levels are

summarized into Table 4. From Table 4, the effects of all three control factors with their

corresponding levels are shown in Fig. 1. Since a higher S/N ratio means a better quality

Applied Mechanics and Materials Vols. 52-54 33

characteristic (i.e., bigger electrical conductivity), the optimal combination of control factor levels

is therefore determined as A1B3C2, i.e., A1 = 20 rpm, B3 = 15 min, C2 = 35 0C.

Table 4. Analysis of Control Factor

Control factors

A B C

Level 1 44.97 43.09 43.04

Level 2 43.38 43.92 44.72

Level 3 43.05 44.40 43.65

max-min 1.92 1.31 1.68

A 1 A 2 A 3 - - B 1 B 2 B 3 -- C 1 C 2 C 3

4 3 .0

4 3 .5

4 4 .0

4 4 .5

4 5 .0

S/N

rat

io (

dB

)

C o n tro l f a c to r

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

T h e la rg e r th e b e t te r

Figure 1. Effect of control factors

"Analysis of variance (ANOVA) is a statistical method use to separate the

individual effects from another control factors. The percentage contribution of each control factor is

use to measure the corresponding effect on the quality characteristic.

Table 5. Experimental results of mixing parameters based on L9(33) OA

Variance

Sources

Sum-of-quare

(SS)

Degree-of-

Freedom

(DoF)

Mean-square

(MS)

Pure SS (SS’) Contribution

(ρ)

A 6396.083 2 3198.041 6264.287 44.27196

B 2649.265 2 1324.632 2517.468 17.79185

C 3786.249 2 1893.124 3786.249 26.75878

Error (e) 1317.962 20 65.8981 11.17741

Total

Variance (T)

14149.56

26 100.00

The results of ANOVA are summarized in Table 5, it can be seen that factor A (rotational speed)

put on the biggest contribution (44.27196%) to the electrical conductivity, followed by factor C

(mixing temperature) 26.75878% and factor B (mixing time) 17.79185% respectively. Refer to

Table 1 and Table 4 can be seen that the rotational speed (factor A) generate the best electrical

conductivity on 20 rpm. It can be explain that to produce the polymer nanocomposites higher

rotational speed is not necessary, because higher shear forces can be disrupt small nanotube

aggregate in forming macroscopic networks, while mixing time (factor B) take 15 minutes as the

optimum time to generate the electrical conductivity, it takes longer time to get homogen mixture of

34 Advances in Mechanical Engineering

the polymer nanocomposites. The suitable mixing temperature on mixing parameters is 350C

because higher temperatures make cross linking between epoxy and conductive fillers occurred.

ANOVA result shows that the percentage contribution of the combined error is only as small as

11.1774% which can be concluded that no important factors were missed in the Taguchi approach

so that can be said that arrangement of the experimental trials in this study is successful.

Confirmation experiment is the final step of the Taguchi method to

examining the quality characteristic. Fig. 1 show that the optimal levels of control factors

determined as A1, B3, and C2 and use additive model to predict the S/N ratio obtained by the

confirmation experiment. This model describes the characteristic that the total effect caused by

several factors is equal to the summation of every individual effect. Since all factors used were

significant to influence S/N ratio, then predict can be calculated as :

predict = + (A1- )+(B3- )+(C2- ) (3)

= 46.49 (dB)

where is mean value of Total S/N ratio, and A1, B3, C2 are the S/N ratio on each significant level.

predict value (46.49 dB) shows nearly value to optimal combination (45.87 dB) which mean it just

meets the optimal combination levels (A1B3C2).

Table 6. Comparisons of electrical conductivity

Level Electrical Conductivity [S/cm] S/N Ratio

y1 y2 y3 Mean [dB]

Initial Combination A1B1C1 152.252 159.098 148.811 153.38 43.71

Optimal Combination A1B3C2 198.279 196.436 195.292 196.67 45.87

Table 6 shows that mean value and S/N ratio of electrical conductivity for initial combination with

level A1B1C1 are 153.38 S/cm and 43.71 dB, respectively. Compare to mean value and S/N ratio of

electrical conductivity for optimal combination with level A1B3C2 that are 196.67 S/cm and 45.87

dB, it can be concluded that optimal combination increase mean value of electrical conductivity

28.22%

The optimizations of mixing parameters using the Taguchi method were observed. The results are

as follows:

1. The rotational speed (A), mixing time (B), and mixing temperature (C) were selected as

control factors to conduct the Taguchi method. The experimental trials based on the L9(33) OA

were carried out.

2. According to ANOVA results, the most significant factor that influences the electrical

conductivity of the polymer nanocomposites is the rotational speed (A) with percentage

contribution 44.27%.

3. The confirmation experiment shows 28.22% improvement from the initial combination with

mean value of the electrical conductivity was only 153.38 S/cm significantly improved to 196.67

S/cm

Applied Mechanics and Materials Vols. 52-54 35

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Advances in Mechanical Engineering 10.4028/www.scientific.net/AMM.52-54 Optimization Mixing Parameters on the Electrical Conductivity of Polymer Nanocomposites Based on

the Taguchi Method 10.4028/www.scientific.net/AMM.52-54.31

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