Investigation of the Machinability Characteristics of GFRP / Epoxy Composites Using Taguchi Methodology

Investigation of the Machinability Characteristics of GFRP/ Epoxy Composites using Taguchi Methodology

Hari Vasudevan1, a, Naresh Deshpande2, b and Ramesh Rajguru3,c 1, 2, 3 D.J. Sanghvi College of Engineering, Mumbai, India

[email protected], [email protected], [email protected]

Keywords: Machinability, CNC Turning, Epoxy, Polycrystalline Diamond Tool, Taguchi Methodology, Woven Fabric

Abstract. Many glass fiber reinforced plastic (GFRP) composite components made from primary

melt processes require additional machining to meet the requirements of assembly and accurate

dimensional tolerances. Importance of woven fabric based glass fibre reinforced composites is

widely known in many industrial applications. However, very little is known about machinability of

these composites. Cutting force is treated as one of the primary measures for determining the

machinability of any material.This paper presents an investigation into the longitudinal turning of

woven fabric and epoxy based GFRP composites, using polycrystalline diamond tool, so as to

analyze the effect of cutting parameters and insert radius on the cutting force. The force was

measured through longitudinal turning, according to the experimental plan, as developed on the

basis of Taguchi methodology. The signal to noise ratio and analysis of variance were applied to the

experimental data, in order to determine the effect of the process variables on tangential cutting

force. Statistical results indicated that the cutting force is significantly influenced (at a 95%

confidence level) by feed rate, followed by depth of cut, whereas, cutting speed and insert radius

have a smaller influence. The cutting force also increases with the increase in feed rate and depth of

cut.

Introduction

During the last decade, machining of components made of polymer matrix composites has been

developed as an alternative to the processes of injection molding, extrusion and sintering. Many

components made from primary melt processes also require additional machining to meet the

requirements of assembly and accurate dimensional tolerances.

Machining of fibre reinforced composites differs from that of metal alloys due to their

anisotropy, low thermal conductivity and difference between coefficient of linear expansion of the

matrix and the fibre. The quality of the machined surface depends upon the type of fibres and

matrix materials, type of weave of the fabric etc. Some of the typical problems faced during the

machining of fiber reinforced plastics (FRPs) are fibers getting pulled out, separation of the bond

between matrix and fibres, burning out of material, short tool life, powder type chips, high cutting

forces and poor surface finish. Moreover, cutting forces have a direct effect on power consumption

and tool wear. They are oscillating and periodic in nature. The oscillations are generated due to

repeated running of cutting tool into fibres and matrix phases. This often results in strong variations

of magnitudes of cutting forces. In order to achieve good machinability, it is desirable to have

minimum values of cutting force. Since, machining involves large number of process variables, the

optimization of cutting force is time consuming and costly. Instead of, one factor at a time

experimental approach, in the present study, the machining data is analyzed using Taguchi design of

experiments (DOE) and analysis of variance (ANOVA).

Palanikumar et.al [1] carried out optimization of turning process parameters of filament wound

GFRP/Epoxy composites. They used polycrystalline diamond (PCD) tool for turning and Taguchi’s

method with Pareto ANOVA for optimization of surface roughness. Davim and Mata [2] suggested

a new machinability index, using specific cutting pressure and roughness average, while turning

GFRP/Polyester composites. The pipes were manufactured using filament winding and hand lay-up

Applied Mechanics and Materials Vol. 612 (2014) pp 123-129© (2014) Trans Tech Publications, Switzerlanddoi:10.4028/www.scientific.net/AMM.612.123

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processes. PCD tool was used for turning and Taguchi’s method with ANOVA was used for

studying the influence of the machining parameters on specific cutting pressure and roughness

average. Palanikumar and Davim [3] assessed the influence of cutting parameters on tool wear,

while turning filament wound GFRP/Epoxy composites. They used coated cemented carbide tool

for turning and Taguchi’s method for optimization. Davim et.al [4] conducted a machinability

study, during precision turning of PA66 Polyamide with and without glass fibre reinforcement.

They used four different types of tool materials. The PCD tool gave the lowest force values

associated with best surface finish, followed by the ISO grade K15 uncoated carbide tool with chip

breaker, when machining reinforced polyamide. Khan and Kumar [5] conducted machining studies

on GFRP/Polyester composites, produced by filament winding process. Two different alumina

cutting tools were used namely a Ti (C, N) mixed alumina cutting tool and a Sic whisker reinforced

cutting tool. The machining process was performed at different cutting speeds, constant feed rate

and depth of cut. The performance of the tool was evaluated by measuring the flank wear and

surface roughness of the machined GFRP composite.

The machinability of composite materials is highly influenced by the type of fibre, type of resin,

fibre orientation and method of manufacturing. The extant literature survey reveals that PCD cutting

tool is more appropriate for cutting a hard material like GFRP. Also woven glass fibre reinforced

epoxy composites manufactured by hand lay-up process have not been widely explored for their

machining characteristics, despite their wide applications in electrical components, aerospace and

automotive structural parts. In this context, the present study is an attempt to find the effect of

cutting parameters and insert radius on the tangential cutting force during turning of Epoxy and

woven fabric based GFRP composites, manufactured by hand lay-up process.

Experimental Details

Work Material The work material selected for the study is glass fibre reinforced epoxy

composite. The E-glass reinforcement is of woven fabric form having following specifications.

Type of weave: plain, weight: 180±5 gm/m2 and 0.18mm thickness, manufactured using Hybon

multi-end roving. Epoxy resin manufactured by Huntsman; product Araldite LY3297; hardener

Aradur 3298 is used as polymer matrix material. The work specimens are tubular in shape 50 mm

long, with inner diameter of 20 mm and outer diameter of 55 mm. They are manufactured using

hand lay-up process and cured at room temperature. The volume fraction of the reinforcement is

70%. The work specimens before & after machining are as shown in Fig. 1 (a & b).

Cutting Tool The cutting tool selected for machining GFRP composites is PCD insert of the fine

grade. Three different types of inserts are used. They are ISO coded with CNMA 120404, CNMA

120408 & CNMA 120412 and are produced by Varun Tools Pvt. Ltd. The tool holder is of

WIDEX-ID1G with ISO coding PCLNL 25X25 M12.

Fig. 1. (a) Work specimens before machining ; (b) Work specimen after machining.

124 Advanced Research in Design, Manufacturing and Materials

Experimental set-up and plan The experiment for this work was planned using Taguchi’s DOE

as per the flow chart given in Fig. 2. Taguchi’s approach to parameter design provides the design

engineer with a systematic and efficient method for determining near optimum design parameters

for performance and cost. This method can reduce the number of experiments required to collect

necessary data. Four control factors, which could probably affect the cutting force, were selected for

the study, viz. insert nose radius, cutting speed, feed and depth of cut. Each factor was studied at

three levels. The most appropriate orthogonal array in this case is L27 OA. The factors are assigned

to column no. 1, 2, 5 and 8 respectively. The unassigned columns are treated as error. The output

response used to measure machinability is the tangential cutting force. Each trial was repeated once.

Also the trials were carried out in random order. The work piece was mounted on specially designed

mandrel, which was subsequently clamped by the lathe chuck. These experiments were conducted

on an Ace Jobber XL CNC lathe machine with the following specifications, swing over bed: 500

mm, swing over carriage: 260 mm, max. turning dia.: 270 mm, max. turning length: 400 mm, max.

spindle speed: 4000 rpm, spindle motor power: 7.5 KW and Fanuc series Oi-TD Mate CNC

controller. The machining tests were carried out without any coolant. The tangential cutting force

was measured with Kistler Piezo electric dynamometer of type-5233A, with built in charge

amplifier up to 10 KN. Data acquisition was accomplished by connecting this dynamometer to a

computer and using Kistler Dynoware type- 2825A software. Table 1 shows the values of selected

process parameters at three levels, where as Table 2 shows Orthogonal Array L27 and the measured

values of cutting force and the respective S/N ratios at different parameters settings. Sample graph

of the tangential force is shown in Fig. 3.

Table 1: Control factors and their levels

Process parameters

designation Process parameters Units

Levels

Level 1 Level 2 Level 3

A Tool nose radius mm 0.4 0.8 1.2

B Cutting speed m/min 120 160 200

C Feed rate mm/rev 0.05 0.15 0.25

D Depth of cut mm 0.6 1 1.6

Fig. 2. Flow-chart for Taguchi’s Design of experiments (DOE).

Applied Mechanics and Materials Vol. 612 125

Table 2: Experimental plan L27 OA, main cutting force and S/N ratio

Exp.

run A B C D

Rdg.1

Fz (N)

Rdg.2

Fz (N)

Mean

Fz (N)

S/N (dB)

Force

1 1 1 1 1 10.65 7.84 9.245 -19.4173

2 1 1 2 2 44.43 32.04 38.235 -31.7618

3 1 1 3 3 89.9 71.47 80.685 -38.1921

4 1 2 1 2 13.73 11.2 12.465 -21.9583

5 1 2 2 3 55.6 52.43 54.015 -34.6540

6 1 2 3 1 29.69 26.64 28.165 -29.0069

7 1 3 1 3 17.94 15.47 16.705 -24.4806

8 1 3 2 1 19.93 15.53 17.730 -25.0405

9 1 3 3 2 46.84 50.96 48.900 -33.7939

10 2 1 1 1 7.84 7.02 7.430 -17.4330

11 2 1 2 2 31.13 29.3 30.215 -29.6084

12 2 1 3 3 81.12 67.69 74.405 -37.4673

13 2 2 1 2 12.6 12.36 12.480 -21.9247

14 2 2 2 3 48.83 46.63 47.730 -33.5781

15 2 2 3 1 22.22 26.67 24.445 -27.7996

16 2 3 1 3 18.07 16.72 17.395 -24.8150

17 2 3 2 1 18.4 16.45 17.425 -24.8370

18 2 3 3 2 39.89 45.84 42.865 -32.6629

19 3 1 1 1 9.49 11.66 10.575 -20.5311

20 3 1 2 2 28.69 24.05 26.370 -28.4557

21 3 1 3 3 67.78 69.09 68.435 -36.7060

22 3 2 1 2 14.92 15.44 15.180 -23.6267

23 3 2 2 3 54.87 44.71 49.790 -33.9878

24 3 2 3 1 27.68 14.47 21.075 -26.8823

25 3 3 1 3 20.26 16.85 18.555 -25.4057

26 3 3 2 1 18.89 24.26 21.575 -26.7458

27 3 3 3 2 43.95 42.51 43.230 -32.7169

Fig. 3. Sample tangential force graph

126 Advanced Research in Design, Manufacturing and Materials

Results and Discussion

The analysis was made using the popular software, specially used for design of experiment

applications, known as MINITAB 16. Response Table 3 shows the response for S/N ratio values of

cutting force at different levels of the selected parameters. Fig. 4 indicates the variation of the S/N

ratio of forces for different level of parameters. As the feed (C) and the depth of cut (D) are

increased from level one to three; the S/N ratio of cutting force decreases. The variation of the S/N

ratio of cutting force is more for feed rate than for the depth of cut. The nose radius (A) and cutting

speed (B) have a very less effect on the variation of the S/N ratio. The normal probability plot of

residuals for S/N ratios is shown in Fig. 5. It is almost linear, and hence we could proceed further

assuming that the error terms are normally distributed. ANNOVA Table 4 for S/N ratio of cutting

force, shows that feed rate (C), followed by the depth of cut (D) are the significant factors. Since

R2= 97.43% for the ANNOVA, the contribution of the factor interactions in the variation is

negligible.

Table 3: Response table for cutting force (S/N ratio) at different factor levels

The optimum settings as per the response table are A2B3C1D1and the ANOVA results for S/N

ratio indicated the significance of feed rate C and depth of cut D at 95% confidence level. The

estimated mean of the response characteristic S/N ratio (η) can be computed by using the following

Eq.1 [6].

= ̅ + 1 − ̅ + 1 − ̅ . (1)

Where ̅ = overall mean of S/N ratio (η) for tangential cutting force = -28.27 dB; C1 = average

value of S/N ratio (η) for tangential cutting force at first level of feed = -22.18 dB and D1 = average

value of S/N ratio (η) for tangential cutting force at first level of depth of cut = -24.22 dB. Hence

= -18.13 dB, and therefore the predicted value of mean tangential force = 8.0631 N.

Level A B C D

1 -28.7 -28.84 -22.18 -24.22

2 -27.79 -28.18 -29.85 -28.5

3 -28.37 -27.83 -32.83 -32.14

Delta 0.91 1.01 10.66 7.92

Rank 4 3 1 2

Applied Mechanics and Materials Vol. 612 127

Fig. 4. Main effects plot of S/N ratios for tangential cutting force.

Fig. 5. Normal probability plot for S/N ratios

128 Advanced Research in Design, Manufacturing and Materials

Table 4: S/N ANOVA for cutting force

Source SS DOF MS F ratio SS’ P(%)

(A) 3.85 2 1.92 1.57 1.41 0.1644

(B) 4.71 2 2.36 1.93 2.27 0.2647

(C) 543.97 2 271.98 222.57 541.53 63.1602

(D) 282.86 2 141.43 115.74 280.42 32.7062

Error 22 18 1.22

31.76 3.7042

Total 857.39 26

R2= 97.43%

Conclusion

Within the range of cutting parameters used in this study, the following conclusions are arrived at.

Statistical results indicate that the cutting force is significantly influenced (at a 95% confidence

level) by the feed rate followed by the depth of cut, whereas, the cutting speed and insert radius

have a smaller influence. The cutting force also increases with the increase in feed rate and depth of

cut respectively.

Based on the analysis of the S/N ratio, the optimal cutting force is achieved, when the nose

radius is set at level 2 and cutting speed is set to level 3 of the experimental range, where as the feed

rate & depth of cut are set at their low level (level 1) of the experimental range. Confirmatory

experiment at the optimum settings gave the value of tangential force as 7.01N, which is within

95% confidence interval of the predicted value, hence validating the results.

References

[1] K. Palanikumar, Cutting Parameters Optimization for Surface Roughness in Machining of

GFRP Composites using Taguchi’s Method, Journal of Reinforced Plastics and composites. 25

(2006) 1739-1751.

[2] J. Paulo Davim and Francisco Mata, A new machinability index in turning fiber reinforced

plastics, Journal of Materials Processing Technology. 170 (2005) 436–440.

[3] K. Palanikumar and J. Paulo Davim, Assessment of some factors influencing tool wear on the

machining of glass fiber-reinforced plastics by coated cemented carbide tools, Journal of

Materials Processing Technology. 209 (2009) 511-519.

[4] J. Paulo Davim, Leonardo R. Silva, António Festas, A.M. Abrão, Machinability study on

precision turning of PA66 polyamide with and without glass fiber reinforcing, Materials and

Design. 30 (2009) 228–234.

[5] M. Adam Khan and A. Senthil Kumar, Machinability of glass fibre reinforced plastic (GFRP)

composite using alumina-based cutting tools, Journal of Manufacturing Processes. 13 (2011)

67-73.

[6] Madhav S. Phadke, Quality Engineering Using Robust Design, P T R Prentice-Hall, New

Jersey, 1989.

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