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Optimization of cutting parameters in Hybrid (Al6061/SiC/B4C/talc ) composites

by Taguchi Technique (Grey Relational Analysis)

Ramesh Kumar.C1, JaiGanesh.V2

1Research Scholar, Anna University, Tamilnadu, Chennai, TamilNadu,India

Email:[email protected]

2Professor Department of Mechanical Engineering, SA Engineering College, Tamilnadu, Chennai, India

ABSTRACT

The aluminium matrix composites,reinforced with ceramic particles like  SiC, B4C, Al2O3 etc., influence the tool wear, high cutting forces and poor surface finish during machining. The aim of this study is to investigate the effect of drilling parameters on Al6061/SiC/B4C/talc composites fabricated by stirring casting method.  These hybrid composites containing talc (solid lubricant) particles reduce thrust force,circularity and lower surface roughness. The drilling experiments were done based on Taguchi L27 orthogonal array on Al6061/SiC/B4C/talc composites, with HSS drill bits being 6mm,7mm, and 8mm diameter ) used in dry condition. The effect of various drilling input parameters like cutting speed, feed, depth of cut percentage of reinforcement on output parameters like thrust force, surface roughness and circularity was examined by ANOVA and the Grey relational analysis equations were utilized to find the optimum machining condition. The most important parameter,feed was found to have its impact on the speed, depth of cut and reinforcement of composites.

Keywords:- Hybrid metal matrix composites, Drilling, Grey relational analysis, Thrust force, Surface

Roughness and Circularity.

1.0 INTRODUCTION

Aluminum metal matrix composites having hard ceramic particles in the matrix have a poor surface finish and high tool wear during machining. The conventional materials are being rapidly replaced by metal matrix composite in several fields such as automotive industry, aerospace and electronics industries etc. The preparation of Al matrix composites (AMC) is carried out by the liquid metallurgy method. It is simple, economical and cheap compared with the other methods [1-4]. Udayprakash et al., performed experiment on hybrid AMMC with fly ash and boron carbide in the wire EDM. In this experiment it was found that voltage gap was an important impact parameter for MRR and roughness [5].Basavarajappa et al., found the process cutting parameters of drilling of hybrid AMMC with SiC and graphite reinforcements.Feed was found to be the major parameter that could cause effect in the composite [6].Charles et al., studied aluminium alloy hybrid Al/SiC/Fly ash composite fabricated by liquid metallurgy method and mathematical model for MRR and apparatus wear in EDM were produced[7]. Jenarthanan and Naresh studied and optimized the process parameters like machining force and MRR of GFRP composites by grey relational analysis [8]. RajMohan did drilling tests and anticipated push drive. It was found that feed was the significant parameter influencing the thrust force [9]. RiazAhamed et al., [10] Examined drilling of hybrid Al–5%SiCp– 5%B4Cp metal matrix composites and high speed steel used as a tool material while finding that the lower feed and speed provided better surface with low tool wear. Mahesh Babu et al., [11] examined the aspects of the surface quality on machining of hybrid (Al–SiC–B4C) composites. They affirmed that the feed rate was the most effective parameter which influenced cutting velocity, which inturn the surface roughness. Yahya Altunpak [12] examined the drilling of a hybrid Al/20% SiC/10 % Gr and Al/20% SiC/5% Gr composites. Looking at the results of different cutting conditions, the surface harshness had relatively expanded by feed rate.S.Senthilbabu, and B. Vinayagam  [13] included in the drilling of composites  the boring parameters as feed rate, drilling tool, and its geometry, cutting speed and different parameters similar to impact of coolants, heat treatment and so on. Grey relational analysis [14] was successfully utilized for examining multi performance characteristics including all parameters at once. Grey relational analysis changes over the numerous characteristics into one statistical score called Grey relational grade and establishes an optimum level of parameters which can then be taken. A few reviews on MMCs, drilling MMCs, investigation into the enhancement of the machinability of MMCs have been presented.It was done either to find new composites using better machinability or to test the influence of the machining parameters for new reinforced MMCs[15-18]on surface roughness.While,machining the HSS ,drill tool life  increased due to graphite reinforced aluminium matrix composites when compared with the base alloy.The energy required for drilling the can be  reduced composites compared with the base alloys, so that graphite acts as solid lubricant that reduces the friction on tool-work interface[19-20].

Ankesh Kumar et al., [21] performed experimental characterization on Aluminum matrix hybrid composites reinforced with alumina, rice husk ash and graphite. The result showed that decrease in hardness depended upon theincrease in the weight ratio of rice husk, ash and graphite present in the composites.N.Senthil kumar et al. [22] coducted experiments on the turning process by Taguchi method and they observed that the insert shape gave 36.94%, feed rate gave 30.82% of its performance. While doing machining of Al6061-SiC-Gr, nano composites, radial depth and tool improvement per revolution were observed to be important on surface roughness [23]. In micro milling feed per tooth and spindle speed were significant factors [24]. Preet kanwal Singh Bains et al. [25] observed in their review paper at PCD & diamond coated tools were better suited to machining of metal matrix composites. R. Elangovan et al., [26,27] concluded that research work on the machining of Aluminum – fly ash-SiC hybrid composites, and they reported that additional fly ash decreased PCD device wear that the SiC percentage increased and PCD tool wear increased.Ch. Shoba et al.,[28] observed that research work carried out on the machining of composite materials the cutting force components decreased due to increase in the amount %wt of the reinforcement.

In this paper, Al6061/SiC/ B4C/talc composite was developed by stir casting technique (29).Taguchi L27

orthogonal array based Grey relational analysis was experimentally conducted on CNC Radial drilling machine by

varying the different parameters used as  cutting speed, feed, drill diameter and % of reinforcement. Taguchi based

Grey relational analysis (GRA) was used to study the impact of the process parameters, namely thrust force, surface roughness (SR), and circularity. Finally  ANOVA was used to find out the influential output parameter.

2.0 Materials and methods

2.1 Materials

Al 6061 was the base metal matrix material used and reinforcement was SiC varying % wt of 5,10, & 15 (30

40 micron size), constant 3% wt of % B4C (20-30 micron size) and 2% wt of talc (0-50 micron size),and Al6061/SiC/B4C/talc composite. The Al606l as a base alloy was cut into small pieces and put into

graphite crucible in an electric furnace heated up to 600oC to 700oC . At this stage, mixtures of the (SiC/

B4C/ talc) particles were preheated at300oC and then added into Al6061 molten metal. To improve wettability

For reinforcement purpose magnesium (0.5%wt)was added  to Al6061molten metal. Further 5g of degassed C2Cl6- Solid hexocholroethane was added to remove impurities. The mixture of (Al6061/SiC/B4C/talc

) molten metal was stirred continuously for about 10 minutes by electric motor impeller at the speed of 300-

500 rpm for uniform dispersion of particulates in the melt and poured into preheated iron die.

2.2 Experimental Set-up

Drilling tests were conducted on CNC drilling machine type of Bharat Frietz Werner (BMV40T20) as shown in Fig.1 where the specimens were prepared in the form of 100mm×100mm×10mm blocks. The experimentation was

carried out with three step twist HSS drill bits (8mm,10mm and 12mmlarger diameter) as shown in Fig.2. Kistler

dynamometers were used to measure the cutting forces and torques. The surface finish of each drilled hole  (Fig.3) was measured with the aid of a Video Measuring System (VMS-2010 F) and the circularity of each drilled hole was measured with the aid of a computer controlled surface roughness tester (SE3500) at Anna university in Chennai.

Fig-1 Experimental set-up Fig-2 Drill bits Fig-3 Specimen after drilling

3.0 PLAN OF EXPERIMENTS

The drilling tests were carried out as per the orthogonal array based on the Taguchi technique which is formulated

by the four factors (parameters) and three levels. The drilling factors (parameter) considered for the experiments were cutting speed, feed, depth of cut and percentage of reinforcement and the output parameters were thrust force, surface roughness and circularity. While the experiments were confined to 27 tests, the process parameters and corresponding levels were obtained as shown in Table -1.

Table.1. Experiments Factors( Parameters) and their Levels

Factor Drill

Speed (rpm)

A Feedrate (mm/min)

B Drill diameter (mm)

C % of reinforcement

D Level -1 750 50 5 5

Level -2 1000 100 6 10

Level -3 1250 150 8 15

3.1 Taguchi design Experiments

Design of experiments (DOE) is the best and useful statistical techniques for studying the impact of multiple variables continouously. This method is also used to reduce no of variations in parameters along with robust design of experiments. Taguchi technique is the suitable approach for process optimization and identification of optimal combination of the factors (variable) for a certain response. The entire objective of the technique is to deliver high quality product at a cheaper cost. The L27 orthogonal array used for the present work is listed in Table-2.

3.2 Grey relational analysis

Grey relational analysis is one of the significant theories and can be applied for analyzing the uncertainty, multi-input and discrete data [31,32]. A measurement of the total value of the data difference between sequences is

known as Grey relational analysis. It is used to measure a fairly accurate correlation between sequences. It is a

feasible method for examining the relation between the sequences with less data and can investigate numerous

factors.

3.3 Analysis Approach

The Taguchi\'s L27 orthogonal exhibit utilizing 27 various examinations was conducted. The Grey relational

analysis (GRA) contains 27 tests. The impact of these systems on the response variable was examined by GRA.

The drilling experiment test was evaluated by leading 27 tests and every analysis was termed as equivalence succession. The parametric conditions were compared to Thrust Force, Surface Roughness and Circularity.

Experimental values of thrust Force, Surface Roughness and Circularity are given in Table-2. The different target issue was changed over into single target optimization using GRA technique. The responses to be examined were thrust Force, Surface Roughness and Circularity with the goal  “the higher- the better”. The logarithmic change of loss function as mentioned below.

Xijk – (Xijk)min

Lower-is–better Xijk

* = ---------------------- -------- (1)

(Xijk)max-(Xijk)min

(Xijk)max – (Xijk)

Higher-is-better Xijk

* =---------------------- -------- (2)

(Xijk)max- (Xijk)min

Where (Xijk)minindicates the lower experimental value of Xijk ,(Xijk)max represents the upper experimental value of

Xijk (X1jk) *max is the standardized value after grey generation of the higher is better(X2jk)* max is the standardized value after Grey generation of the lower is better.

The maximum of the standard values calculated by using the formula R = (Xijk)*max = 1

where R is the absolute difference between each standardized and the reference value. The response variable,

trials and replications were estimated using the formula Δ ijk = [Xijk* - R ]

Calculated the grey relational coefficients for the every performance characteristic by (Δ ijk) min + ζ(Δijk)max

ζijk = --------------------------Δ ijk + ζ(Δijk)max

for i =1,2,3……..,p, j=1,2,3…..,q and k= 1,2,3…….,r ,ζ is the distinguishing coefficient is 0 to 1 (0.5 is widely used)

Calculated the grey relational grades are using the formulaP r γj =Σ Σ ζijk----------------------------- (3) i=1 j=1

p x r for j=1,2,3……9 where ‘n’ is the numbers of observations, ‘yI’is the experimental data of thrust force, surface roughness and circularity. From Table-3 the output results to be studied are thrust force, surface roughness,and circularity from the test specimens are repeated by doing 27 tests while selecting optimum levels for the factors based on response graph and ANOVA.

Table-2 Experimental Data [Thrust Force(TF),Surface Roughness(SR)and Circularity(CIR) ]

for L27 orthogonal array SI.No Cutting Speed

(A) Feed

(B) Drill

(C) % of reinforcement (D) Torque Force (N-M) SR(Micron) CIR(mm)

1 750 15 6 5 118.1200 4.8100 0.0640

2 750 15 7 10 85.5508 3.6108 0.1043

3 750 15 8 15 92.7791 4.2258 0.1113

4 750 25 6 10 83.5742 4.5058 0.1095

5 750 25 7 15 119.9000 3.9020 0.1209

6 750 25 8 5 105.2400 3.7208 0.1120

7 750 35 6 15 104.8158 5.8158 0.1427

8 750 35 7 5 115.2642 3.5158 0.1477

9 750 35 8 10 141.1000 4.7500 0.1320

10 1000 15 8 5 79.1160 3.9726 0.1057

11 1000 15 6 10 78.4500 3.6576 0.1099

12 1000 15 7 15 93.4500 3.2900 0.1310

13 1000 25 8 10 96.5000 4.1500 0.1370

14 1000 25 6 15 74.7019 5.0676 0.1364

15 1000 25 7 5 90.1400 3.7676 0.1214

16 1000 35 8 15 131.6200 5.7926 0.1611

17 1000 35 6 5 85.4600 8.1500 0.1220

18 1000 35 7 10 116.3917 3.6776 0.1491

19 1250 15 7 5 55.0180 4.1030 0.1362

20 1250 15 8 10 87.0000 3.7230 0.1240

21 1250 15 6 15 54.5775 5.3193 0.1252

22 1250 25 7 10 86.2675 3.5293 0.1328

23 1250 25 8 15 81.4956 4.0443 0.2048

24 1250 25 6 5 59.3600 4.8100 0.1440

25 1250 35 7 15 109.8200 4.5060 0.1420

26 1250 35 8 5 107.9577 4.5393 0.1455

27 1250 35 6 10 82.2908 6.2243 0.1485

4.0. RESULTS AND DISCUSSIONS

An Experimental values of Thrust force, Surface roughness and Circularity are listed in Table. Generally the

thrust force, surface roughness and circularity belong to the “Higher – the –Better” method that in eq (2) and the experimental values to be calculated into GRG by using eq (3) are listed in Table-3.The experimental values were transformed into GRG values with the help of the software MINITAB 16 as use for the design of experiments. At the optimal level, any dominant factor will be got from the highest value of Grey relational grade from their considered levels. The response Table data is graphically shown in Fig [?].The grey relational grade gives the effect of drilling process parameters on achievement characteristics. In  other words, higher value belongs to the best quality performance. Basavarajappa et al (33) suggested the influence of graphite in Al/SiCp-Gr composite and in according to them addition of graphite inside the composite decreased the hardness and the strength of the composite. APPLYING THERE ARE FINGING TO OUR CASE FOR  machinability the reduction in torque, at the same time as drilling graphite composites can also be observed this property shows the positive impact of the graphite present in the composite.] [highly confusing]

For our  study, Basavarajappa experimental study helps us for that solid lubricant (graphite).Instead of graphite we have used talc based Al6061/SiC/B4C composite for drilling experiment.The depends upon Solid lubricant (talc) content that rate reduces the cutting force and surface roughness while doing machining in the hybrid Al6061/SiC/B4C/talc) composites. The solid lubricant (graphite) helps the materials to

shear easily (34-39). However, feed rate and spindle speed appear to deliver actual slight effect on cutting force.The purpose of using graphite instead of the talc use in the composite is that it easily permits to shear and roughness, minimum cutting force and better machinability. In the drilling the optimum parameters were observed to be: the cutting speed 1250 rpm, feed 15mm/rev, drill dia 7mm and reinforcement%5wt fromAl6061/SiC/B4C/talc composites. The combination of A3-B1-C2-D1 is the best value of the Grey relational grade for the factors shown in the Table . Figs-4 (a and b) response graphs and Table-4 show that the higher cutting speed, low feed rate, low drill dia and low percentage of reinforcement are chosen for better condition in the drilling of hybrid metal matrix composite.

Table-3 Grey relational coefficient and Grade Relational Grade TF CIR SR (GRG)

1 0.4051 1.0000 0.6152 0.6734

2 0.5828 0.6360 0.8834 0.7007

3 0.5311 0.5981 0.7220 0.6171

4 0.5987 0.6074 0.6665 0.6242

5 0.3984 0.5530 0.7988 0.5834

6 0.4606 0.5946 0.8494 0.6349

7 0.4627 0.4722 0.4903 0.4751

8 0.4162 0.4568 0.9150 0.5960

9 0.3333 0.5087 0.6247 0.4889

10 0.6381 0.6280 0.7807 0.6823

11 0.6444 0.6054 0.8686 0.7061

12 0.5267 0.5124 1.0000 0.6797

13 0.5079 0.4909 0.7386 0.5791

14 0.6825 0.4930 0.5775 0.5843

15 0.5488 0.5509 0.8357 0.6451

16 0.3596 0.4203 0.4926 0.4242

17 0.5835 0.5483 0.3333 0.4884

18 0.4117 0.4527 0.8624 0.5756

19 0.9899 0.4937 0.7493 0.7443

20 0.5716 0.5399 0.8488 0.6534

21 1.0000 0.5350 0.5449 0.6933

22 0.5772 0.5057 0.9104 0.6644

23 0.6164 0.3333 0.7631 0.5710

24 0.9005 0.4681 0.6152 0.6612

25 0.4392 0.4744 0.6665 0.5267

26 0.4476 0.4635 0.6605 0.5239

27 0.6095 0.4545 0.4530 0.5057

750 1000 1250

0.70

0.65

0.60

0.55

0.50

15 25 35

6 7 8

0.70

0.65

0.60

0.55

0.50

5 10 15

cs

Mean of Means

FD

Dd % ref

Main Effects Plot for Means

Data Means

750 1000 1250

-3

-4

-5

-6

15 25 35

6 7 8

-3

-4

-5

-6

5 10 15

cs

Mean of SN ratios

FD

Dd % ref

Main Effects Plot for SN ratios

Data Means

Signal-to-noise: Larger is better

Fig-4 Response graphs

(a)Mean effect plot for Means (b) Mean effect plot for SN ratios

Table-4 Response table for Grey relational grade

The SEM (Scanning Electronic Microscope) image shows drilled surface in Fig-5 which is supported to drill

machined under optimized process parameters. (A3-B1-C2-D1) gives higher Grey relational grade value (0.7443).

The drill geometry represents  thermally softened materials and reduction in forces.

Fig-5 SEM micro structure of drilled surface for optimum parameter (A3-B1-C2-D1)

4.1 Analysis of Variance

The method of ANOVA is used to examine variability of an output to several inputs. The aim of the analysis of

variance is to examine which machining parameters significantly affect the achievement characteristic [40, 41].The

total sum of the squared deviations SST is calculated from the values of the total mean Grey relational grade (GRG)

by giving eq (4) mSST = Σ (γj - γm) --------------------------- (4)j=1Level CuttingSpeed(A)Feed(B)Drill dia(C)% reinforcement(D)

1 0.5993 0.6834 0.6013 0.6277

2 0.5961 0.6164 0.6351 0.6109

3 0.6160 0.5116 0.5750 0.5727

Delta 0.0199 0.1718 0.0602 0.0550

Rank 4 1 2 3

Mean Grey relational grade = 0.6038

Anywhere m is the number of experiments in the orthogonal array then γj is the Grey relational grade for

the jth experiment and γm is the total of the mean Grey relational grade in the optimum level. The analysis is

performed at a level of 5% association that is up to the level of confidence  95%.The Table represents the

result of ANOVA for the response characteristic of hybrid Al6061/SiC/B4C/talc composite.

The result of ANOVA for the response characteristic of hybrid Al6061/SiC/B4C/talc composite is shown

Table-5.The table exposes that the feed (75.9076%) is the most important machining factor followed

by drill dia (9.2079%),% of reinforcement(8.040%)and speed (1.15499%) influencing the multiple

performance characteristics for hybrid Al6061/SiC/B4C/talc composite.

Table-5 Result for Analysis of Variance of GRG Source DOF Seq .SS Adj.SS Adj.MS F P % contribution

Cutting Speed 2 0.002053 0.002053 0.001026 1.83 0.190 1.15499

Feed rate 2 0.134925 0.134925 0.067463 119.99 0.000 75.9076

Drill dia 2 0.016367 0.016367 0.008184 14.56 0.000 9.2079 % reinforcement 2 0.014284 0.014284 0.007142 12.70 0.000 8.040

Residual Error 18 0.010120 0.010120 0.000562 5.6934

Total 26 0.177749 100

S = 0.0237111 R-Sq = 94.31% R-Sq(adj) = 91.78%

4.2 Confirmation Experiment

Later, the optimal level machining parameters is identified.The last step is to predict and verify the

enhancement of the performance characteristics by the optimal level of the machining parameters. To calculate

predicated Grey relational grade by the optimal response using the following eq(5):  nȠPredicted = Ƞmean +Σ (Ƞi -Ƞmean) ----------------------- (5) i =1

where Ƞmean is the total mean grade, Ƞi is the mean GRD at the optimum level, n is the no of main parameters that

much affects the quality characteristics. This confirmation experiment aim is to verify the improvement in the

quality characteristics. From eq (5) the Grey relational grade is predicted for the optimal parameters (A3-B1-

C2-D1); then its value is (0.77395).The final confirmation was conducted by optimum combination of

parameters  (A3-B1-C2-D1).Table-6 exposes the comparison of predicted Grey relational grade with the

actual Grey relational grade one.The confirmation test showed the Grey relational grade value to be 0.7443.

Table-6 Confirmation experiment for GRG

Initial wear Parameters Optimal wear Parameters

Prediction Experiment

Level A1-B1-C1-D1 A3-B1-C2-D1 A3-B1-C2-D1

GRG 0.6734 0.77395 0.7443

GRG improvement difference= 0.10055

5.0 CONCLUSIONS

Al6061/SiC/B4C/talc composites were fabricated by stir casting process in the constant weight percentage of both (3%weight) B4C particulate and talc (2%weight) particulate of different range (5%, 10%, 15%) weight of SiC particulate reinforced with Al 6061.

The Grey relational analysis method used to Taguchi’s L27orthogonal array with the help of ANOVA that support

for optimization of drilling process parameters in hybrid composites. The optimization of multi response drilling

experiment was conducted on Al6061/SiC/B4C/talc composites by different types of high speed steel drill bits.

This method was used to predict the precious cutting force, circularity and surface roughness. The following results

have been obtained from the above study.

1.Lower feed rate gives a lower value of surface roughness and cutting forces while higher feed rate particles are pulled out from the composites and the surface roughness is increases.The higher cutting speed, low feed

rate, low drill dia and low percentage of reinforcement are chosen for best in the drilling of hybrid metal matrix

composite.

2.Depending upon the talc content the cutting force, circularity and surface roughness will vary. The talc presence in the composites improves the machinability.

3.As a result for optimal recommended process parameters was attain the combination of A3-B1-C2-D1 is the

best value of the grey relational grade for the factors. In the drilling optimum parameters observed that the cutting

speed 1250 rpm, feed 15mm/min, drill dia 7mm and reinforcement % 5 wt from Al6061/Sic/B4C/talc composites.

4. Analysis of variance exposes that the feed rate has maximum influence (75.9076%) followed by drill dia (9.2079), % of Reinforcement (8.040) and speed (1.15499)  on the drilling of composites.

5. In this study confirmatory experiment shows that predicted and experimental valves are found. The

improvement in the initial drilling parameters to the optimal drilling parameters is 0.10055 from GRG.

ACKNOWLEDGEMENT

The authors would like to Prof .Dr. V. Jai Ganesh, Professor,Department of Mechanical Engineering, SA Engineering College, Chennai, for his support, advice and sharing his expertise.

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