Comparative Analysis of Machining Parameters In Milling Process of MMC and HMMC(Al+10%Sicp+5%Gr)

Comparative Analysis of Machining Parameters In Milling Process of MMC and HMMC(Al+10%Sicp+5%Gr)

1V. Dhivyadharshini, 2P. Karthikeyan 1UG Student,2Assistant Professor 1,2Department of Aeronautical Engineering

1,2Nehru Institute of Engineering and Technology, Coimbatore.

AbstractThis paper deals with the comparative analysis on the use of graphite (Gr) reinforcement in aluminium matrix composites has been reported to be beneficial in reducing wear due to its solid lubricant property, but it results in reduction of mechanical strength. Addition of silicon carbide (SiC), on the other hand, improves both strength and wear resistance of composites, but high amount of SiC makes machining difficult and composites become brittle. Thus, SiC can be advantageously used as a second reinforcement to overcome the problem of strength reduction of Gr reinforced composites, resulting in what is known as hybrid composites. Aluminium matrix composites reinforced with equal weight fraction of SiC and Gr particulates up to 10% are studied with regard to hardness improvement and modified dry sliding wear behaviour. Studies based on design of experiments techniques indicate that there is an increasing trend of wear in AlSiCGr hybrid composites beyond % reinforcement of 7.5%. Hybrid composites exhibit better wear characteristics compared to Gr reinforced composites. Interaction between load and sliding distance is noticed in both the composites and this may be attributed to the presence of Gr particulates.

Keywordsmmc; surface roughness; tool flank wear; taguchi; S/N; WC; PMMC; milling

1.INTRODUCTION

Aluminium matrix composites (AMCs) are replacing the conventional aluminium alloys due to improved strength to weight ratio, which is one of the most desirable characteristic in automotive engine pistons, brake pads, turbine blades, etc. to mention a few among the most common applications of AMCs. AMCs reinforced with soft reinforcement particles of Gr have been reported to be possessing better wear characteristics owing to the reduced wear because of formation of a thin layer of Gr particles, which prevents metal to metal contact of the sliding surfaces. A linear relation be-tween the wear volume and load is the observation of Liu et al. for laser processed Al Gr composites with 1.55 wt.%Gr. The wear has been significantly influenced by the formation of a thin lubricating film of Gr particulates and removal of worn material was noticed consequent to the failure of this film [1]. Lin et al. have investigated AlGr composite with 06 wt.%Gr and the results indicate reduced wear rate with increase in particulate content. Decrease of wear has been

attributed to prevention of direct contact of sliding surfaces and reduced ploughing effect of Al chips due to the quick formation of lubricating film of graphite particulates [2]. The investigation on machining of AlGr composites by Krishnamurthy et al. has indicated considerable reduction of cutting forces and this has been attributed to the possible reduction of friction due to solid lubrication of Gr particulates [3].

Thus, the addition of Gr facilitates easy machining and results in reduced wear of AlGr composites compared to Al alloy. But high amount of Gr may result in increase of wear due to decrease in fracture toughness with increase in

% reinforcement of Gr particulates as noticed by Ted Guo et al. [4]. Hassan et al. have reported decrease in hardness with increase in % reinforcement of Gr due to increased porosity [5]. The implication of these observations is that the % reinforcement of Gr in AlGr composites is bounded by certain limit beyond which it is not beneficial to add Gr as reinforcement. This should not discourage to make use of the beneficial influence of addition of Gr in AlGr composites. Hard ceramic particulates of SiC when added as a second reinforcement is a panacea towards the difficulties encountered with high % reinforcement of Gr in AlGr composites. AlGr composites containing SiC are re-ferred as AlSiCGr hybrid composites. The salient observations of some of the studies on AlSiCGr hybrid composites are high-lighted in the following few lines.

Riahi et al. have focused upon the influence of tribolayer containing primarily Gr on wear of Al10SiC4Gr hybrid composites [6].The investigations of Basavarajappa et al. on Al15SiC3Grcomposites have indicated that the degree of subsurface deformation and thereby the wear rate in graphite composites is less than that of graphite free composites [7]. Rohatgi et al. have reported that the reduction in friction coefficient of Al10SiC6Gr is due to the combination of increase in bulk mechanical properties as a result of addition of SiC and formation of graphite film [8]. Ted Guo et al. have observed that wear of Al10SiC 28Gr increases up to 5%Gr because of reduced fracture toughness and then de-creases due to formation of thick solid lubricant film which over-rides the effect of fracture toughness [4]. Thus, aluminium matrix hybrid composites

posses better tribological properties over composites with single reinforcement as envisaged by these investigations.

The reported studies have indicated that efforts are scarce on parametric studies on the tribologicalbehaviour of aluminium ma-trix hybrid composites. Consequently, the present investigation fo-cuses on the study of the influence of % reinforcement of SiC particulates, load, sliding speed and sliding distance on the tribologicalbehaviour of AlSiCGr hybrid composites.

1. Experimental procedures and measurements

   A.Materials

   AlSiCGr and AlGr composites required for the investigation are fabricated by stir casting [9]. LM25 is used as the matrix alloy and details of its composition is given in Table 1. Table 2 provides the details of SiC and Gr particulates which are used as reinforcements. Table 3 gives the details of hybrid composites. AlSiCGr hybrid composites with combined weight % reinforcement of 2.5%, 5%, 7.5% and 10% are used. In each of these composite as seen in Table 3, % reinforcement of each of SiC and Gr is equal. Similar details of AlGr composites are given in Table 4.

   1. xperiments

      The al cast composites are of 10 mm diameter, 50 mm length from which wear test specimens of length 35 mm and 8 mm diameter are machined. The end of the specimens are polished with abra-sive paper of grade 600 and followed by grade 1000. Dry sliding tests are carried out as per ASTM G99-95a test standards on pin-on-disc equipment the disc of which is of EN31 steel with surface roughness, Ra 0.1. The pins are cleaned with acetone and weighed before and after testing to an accuracy of 0.0001 g to determine the amount of wear. The sliding end of the pin and the disc surfaces are cleaned with acetone before testing. The hardness of the composites is evaluated using Brinells Hard-ness Tester.

      The experiments were performed on a vertical milling machine. The machining tests (face milling of the composites were performed) in a computer numerical controlled vertical machining center (VMC ARIX 100) capable of a working speed of 5000 rpm. The view of the experimental set-up for milling operation is shown in Figure 1.

      The surface roughness was measured using a surface analyzer of Surfcoder 3500 made by Kosaka and represented as the roughness average (Ra, µm). The results of the roughness average values shown in Table I.

      Table 1

      Chemical composition of the matrix alloy LM25.

      TABLE I. MACHINING PARAMETERS AND THEIR LEVELS

      Level	Machining parameters
      	Speed (rpm)	Feed rate (mm/min )	Depth of Cut (mm/min)
      Level 1	1000	10	0.5
      Level 2	1500	15	1.0
      Level 3	2000	20	1.5

      Table 2

      Details of reinforcements.

      Reinforceme nt	Hardness, GPa	Grain size, lm	Density, g/cm3
      SiC	24.5 29	10 20	3.22
      Gr	0.25	70 80	2.09 2.23

      Table 3
      Details of AlSiCGr hybrid composites.
      AlSiCGr hybrid composites
      Combined % reinforcement	0.00	2.50	5.00	7.50	10.0
      SiC	0.00	1.25	2.50	3.75	05.0
      Gr	0.00	1.25	2.50	3.75	05.0
      Hardness, BHN	67	72	70	68	66

      Table 3
      Details of AlSiCGr hybrid composites.
      AlSiCGr hybrid composites
      Combined % reinforcement	0.00	2.50	5.00	7.50	10.0
      SiC	0.00	1.25	2.50	3.75	05.0
      Gr	0.00	1.25	2.50	3.75	05.0
      Hardness, BHN	67	72	70	68	66

      Figure 1 Experimental set up

      Element	Si	Mg	Fe	Cu	Cr	Zn	Ni	Mn
      Content, %	7.1	0.3	0.3	<0.01 2	0.004	0.002	0.01	0.28

      S. no	Speed (rpm)	Feed (mm/ min)	Doc (mm)	Ra	S/N(Ra)	Fz	S/N(Fz)
      1	1000	10	0.5	0.88	1.1103	111.4	-40.9377
      2	1000	10	1	0.27	11.3727	136.6	-42.709
      3	1000	10	1.5	1.4	-2.9226	113.4	-41.0923
      4	1000	15	0.5	2.32	-7.3098	36	-31.1261
      5	1000	15	1	2.05	-6.2351	43.28	-32.7257
      6	1000	15	1.5	1.72	-4.7106	37.55	-31.4922
      7	1000	20	0.5	0.87	1.2096	103	-40.2567
      8	1000	20	1	0.77	2.2702	93.6	-39.4255
      9	1000	20	1.5	0.48	6.3752	82.21	-38.2985
      10	1500	10	0.5	0.75	2.4988	104.6	-40.3906
      11	1500	10	1	0.41	7.7443	93.27	-39.3948
      12	1500	10	1.5	0.43	7.3306	93.17	-39.3855
      13	1500	15	0.5	0.62	4.1522	92.23	-39.2974
      14	1500	15	1	0.35	9.1186	65.29	-36.2969
      15	1500	15	1.5	0.506	5.917	39.93	-32.026
      16	1500	20	0.5	0.44	7.1309	43.18	-32.7057
      17	1500	20	1	0.226	12.9178	53.69	-34.5979
      18	1500	20	1.5	0.567	4.9283	54.12	-34.6672
      19	2000	10	0.5	2.473	-7.8645	45.37	-33.1354
      20	2000	10	1	0.53	5.5145	21.07	-26.4733
      			120
      			100
      			80
      			60			Fx
      			40			Fy
      			20			Fz
      			0
      				1000 1500 2000
      				Cutting Speed rpm

      S. no	Speed (rpm)	Feed (mm/ min)	Doc (mm)	Ra	S/N(Ra)	Fz	S/N(Fz)
      1	1000	10	0.5	0.88	1.1103	111.4	-40.9377
      2	1000	10	1	0.27	11.3727	136.6	-42.709
      3	1000	10	1.5	1.4	-2.9226	113.4	-41.0923
      4	1000	15	0.5	2.32	-7.3098	36	-31.1261
      5	1000	15	1	2.05	-6.2351	43.28	-32.7257
      6	1000	15	1.5	1.72	-4.7106	37.55	-31.4922
      7	1000	20	0.5	0.87	1.2096	103	-40.2567
      8	1000	20	1	0.77	2.2702	93.6	-39.4255
      9	1000	20	1.5	0.48	6.3752	82.21	-38.2985
      10	1500	10	0.5	0.75	2.4988	104.6	-40.3906
      11	1500	10	1	0.41	7.7443	93.27	-39.3948
      12	1500	10	1.5	0.43	7.3306	93.17	-39.3855
      13	1500	15	0.5	0.62	4.1522	92.23	-39.2974
      14	1500	15	1	0.35	9.1186	65.29	-36.2969
      15	1500	15	1.5	0.506	5.917	39.93	-32.026
      16	1500	20	0.5	0.44	7.1309	43.18	-32.7057
      17	1500	20	1	0.226	12.9178	53.69	-34.5979
      18	1500	20	1.5	0.567	4.9283	54.12	-34.6672
      19	2000	10	0.5	2.473	-7.8645	45.37	-33.1354
      20	2000	10	1	0.53	5.5145	21.07	-26.4733
      			120
      			100
      			80
      			60			Fx
      			40			Fy
      			20			Fz
      			0
      				1000 1500 2000
      				Cutting Speed rpm

      Table 4
      Details of AlGr composites.
      AlGr composites
      % Reinforcement of Gr	0.00	2.50	5.00	7.50	10.0
      Hardness, BHN	67	62	55	53	52

      Table 4
      Details of AlGr composites.
      AlGr composites
      % Reinforcement of Gr	0.00	2.50	5.00	7.50	10.0
      Hardness, BHN	67	62	55	53	52

2. Taguchis Parameter Design

   Taguchi methods are statistical methods developed by Genichi Taguchi to improve the quality of manufactured goods, and more recently also applied to, engineering, biotechnology, marketing and advertising by minimizing the effect of the cause of variation without eliminating the cause. This method involves reducing the variation in a process through robust design of experiments. In this study, Taguchi method, a powerful tool for parameter design of performance characteristics, was used to determine optimal machining parameters for minimum surface roughness of End milling process.

   This method uses a special design of orthogonal arrays to study the entire parameter space with minimum number of experiments only. In this study, three machining parameters were used as control factors and each parameter was designed to have three levels shown in Table I. According to the Taguchi quality design concept, a L27 orthogonal array was chosen for the experiments (Table II).

   The experimental observation are presented and further transferred into signal to noise ratio (S/N ratio) as shown in Table III. S/N is defined as the ratio of mean of the signal to the standard deviation of the noise. S/N ratio takes in to account the amount of variability in the response data and closeness of the average response to the target. The S/N ratio depends on the type of quality characteristics; lower the better have selected for minimization problem of surface roughness values.

   The signal-to-noise (S/N) can be calculated as,

   S/N ratio for Surface finish= -10 log10 (y2) (1)

   The S/N ratio values of surface roughness value is calculated using the equation (1)

   Table 5. Hybrid MMC Speed Vs Cutting force

   SPEED	FEED	DOC	FX	FY	FZ
   1000	10	0.5	28.51	14.67	111.4
   1500	10	0.5	37.36	9.079	104.6
   2000	10	0.5	6.459	12.28	45.37

   Cutting force (N)

   Cutting force (N)

   TABLE II.EXPERIMENTAL RESULTS OF END MILLING PROCESS

   3	1000	10	1.5	30.97	-25.45	113.4
   4	1000	15	0.5	15.85	-11.35	36
   5	1000	15	1	20.21	-13.19	43.28
   6	1000	15	1.5	31.78	-19.28	37.55
   7	1000	20	0.5	24.35	-3.577	103

   3	1000	10	1.5	30.97	-25.45	113.4
   4	1000	15	0.5	15.85	-11.35	36
   5		15	1	20.21	-13.19	43.28
   6	1000	15	1.5	31.78	-19.28	37.55
   7	1000	20	0.5	24.35	-3.577	103

   Table 6.Hybrid MMC speed Vs Force

   Sl.

   	(rpm)	mm/ min	(mm)	Fx (N)	Fy (N)	Fz (N)
   1	1000	10	0.5	28.51	-14.67	111.4
   2	1000	10	1	33.53	-19.32	136.6

   	(rpm)	mm/ min	(mm)	Fx (N)	Fy (N)	Fz (N)
   1	1000	10	0.5	28.51	-14.67	111.4
   2	1000	10	1	33.53	-19.32	136.6

   No Speed Feed Doc

   Fx – Tangent force (N)

   Fx – Tangent force (N)

   Fx Fx

   40

   30

   20

   10

   0

   1 2 3 4 5 6 7 8 9

   Speed 1000 rpm

   Fy Fy

   Fy – Feed force (N)

   Fy – Feed force (N)

   30

   20

   10

   0

   1 2 3 4 5 6 7 8 9

   Speed 1000 rpm

   150

   Fz – Normal force (N)

   Fz – Normal force (N)

   100

   50

   0

   Fz Fz

   1 2 3 4 5 6 7 8 9

   Speed 1000 rpm

3. ANALYSIS OF RESULTS

   ANOVA results of AlSiCGr hybrid composites are given in Ta-ble7.FactorsA(% reinforcement),B(sliding speed),C(load) are significant as their P-value is less than 0.05.. The% contribution of the significant factors is calculated by dividing the sum of squares of a factor by the total sum of squares. The values of % contribution of the significant factors are indicated in Ta- ble8.The contribution of the sliding distance is highest followedby sliding speed, load and% reinforcement.

   TABLE 7.RESPONSE TABLE FOR SIGNAL TO NOISE RATIOS OF THRUST FORCE (SMALLER IS BETTER)

   Level	A	B	C
   1	-38.16	-38.41	-36.70
   2	-35.93	-34.81	-35.96
   3	-35.99	-36.87	-37.43
   Delta	2.23	3.60	1.47
   Rank	2	1	3

   Level	A	B	C
   1	-37.56	-37.72	-38.03
   2	-36.53	-35.65	-36.61
   3	-36.89	-37.61	-36.35
   Delta	1.03	2.07	1.68
   Rank	3	1	2

   Level	A	B	C
   1	-38.16	-38.41	-36.70
   2	-35.93	-34.81	-35.96
   3	-35.99	-36.87	-37.43
   Delta	2.23	3.60	1.47
   Rank	2	1	3

   Level	A	B	C
   1	-37.56	-37.72	-38.03
   2	-36.53	-35.65	-36.61
   3	-36.89	-37.61	-36.35
   Delta	1.03	2.07	1.68
   Rank	3	1	2

   1. MMC b)HMMC

      TABLE 8.ANALYSIS OF VARIANCE FOR S/N RATIO OF SURFACE ROUGHNESS a)MMC b)HMMC

      Source	DF	Sum of square	Mean square	F	P
      A	2	29.078	14.539	1.95	0.205
      B	2	58.854	29.427	3.94	0.064
      C	2	9.731	4.866	0.65	0.547
      A*B	4	106.052	26.513	3.55	0.060	SIGNIFICANT
      A*C	4	42.272	10.568	1.42	0.312
      B*C	4	74.808	18.702	2.50	0.125
      Error	8	59.730	7.466
      Total	26	380.524

      1. MMC

         Source	DF	Sum of square	Mean square	F	P
         A	2	4.946	2.473	0.41	0.675
         B	2	24.373	12.187	2.04	0.193
         C	2	14.780	7.390	1.24	0.341
         A*B	4	299.314	74.828	12.51	0.002	SIGNIFICANT
         A*C	4	24.235	6.059	1.01	0.455
         B*C	4	26.346	6.587	1.10	0.419
         Error	8	47.851	5.981
         Total	26	441.845

      2. HMMC

   Table 9.MAIN EFFECTS PLOT FOR S/N RATIO OF THRUST FORCE a)MMC b)HMMC

   A B

   A B

   Main Effects Plot (data means) for SN ratios Main Effects Plot (data means) for SN ratios

   -35

   -36

   Mean of SN ratios

   Mean of SN ratios

   -37

   -38

   C

   C

   1000

   1500

   2000 10

   15 20

   -36.0

   A B

   A B

   -36.5

   Mean of SN ratios

   Mean of SN ratios

   -37.0

   -37.5

   -38.0

   C

   C

   1000

   1500

   2000 10

   15 20

   -35

   -36

   -37

   -38

   0.5

   1.0

   1.5

   -36.0

   -36.5

   -37.0

   -37.5

   -38.0

   0.5

   1.0

   1.5

   Signal-to-noise: Smaller is better Signal-to-noise: Smaller is better

   Table 10.INTERACTON PLOT FOR S/N RATIO OF THRUST FORCEa)MMC b)HMMC

   Interaction Plot (data means) for SN ratios Interaction Plot (data means) for SN ratios

   -32

   -36

   A

   -40

   -32

   10 15 20

   B

   -32

   -36

   -40

   -32

   A

   1000

   1500

   2000

   A

   1000

   1500

   2000

   -36

   A

   -40

   B

   10

   15

   20

   B

   10

   15

   20

   C

   0.5

   1.0

   1.5

   C

   0.5

   1.0

   1.5

   -32

   10 15 20

   1. A

      1000

      1500

      2000

      A

      1000

      1500

      2000

      B

      10

      15

      20

      B

      10

      15

      20

      -32

      -36

      -40

      -36

      -40

      -36

      C

      0.5

      1.0

      1.5

      C

      0.5

      1.0

      1.5

   2. C

   -40

   1000

   1500

   2000

   0.5

   1.0

   1.5

   1000

   1500

   2000

   0.5

   1.0

   1.5

   Signal-to-noise: Smaller is better Signal-to-noise: Smaller is better

   Table 11.RESIDUAL PLOTS FOR S/N RATIO OF THRUST FORCEa)MMC b)HMMC

   Residual Plots for SN ratios

   Normal Probability Plot of the Residuals Residuals Versus the Fitted Values

   Residual Plots for SN ratios

   Normal Probability Plot of the Residuals Residuals Versus the Fitted Values

   99

   Percent

   Percent

   90

   50

   10

   1

   3.0 99 2

   Residual

   Residual

   Percent

   Percent

   Residual

   Residual

   1.5 90 1

   -1

   -1

   0.0 50 0

   -1.5 10

   -2

   -3.0 1

   -4 -2

   0 2 4

   Residual

   -45

   -40

   Fitted Value

   -35

   -30

   -4 -2

   0 2 4

   Residual

   -42

   -39

   -36

   Fitted Value

   -33

   -30

   4.8

   Frequency

   Frequency

   3.6

   2.4

   1.2

   0.0

   Histogram of the Residuals Residuals Versus the Order of the Data

   3.0

   Residual

   Residual

   1.5

   0.0

   -1.5

   -3.0

   Histogram of the Residuals Residuals Versus the Order of the Data

   8

   2

   Frequency

   Frequency

   Residual

   Residual

   6 1

   4 0

   -1

   2

   -2

   0

   -2.4

   -1.2

   0.0

   Residual

   1.2

   2.4

   2 4 6 8 10 12 14 16 18 20 22 24 26

   Observation Order

   -2 -1

   0 1 2

   Residual

   2 4 6 8 10 12 14 16 18 20 22 24 26

   Observation Order

4. RESULTS AND DISCUSSION

   Experimental observations are analyzed for identifying the optimum level of parameters. Fig. 3 shows graphically the effect of 3 control factors on surface roughness on AMC. The analysis of experimental data was carried out using Minitab 15 software. Analysis of the result leads to the conclusion that factors for AMC at level B1 A2 C3 gives the minimum surface roughness for AMC. The influence of control parameter on the output has been evaluated using S/N ratios response analysis. The control factor with the greatest influence of was determined by difference between max and min values means of S/N ratios. Ranking of predominant parameter influencing the surface roughness

   using in the S/N ratio obtained for different parameter levels are listed in the following table. From these tables that affect the response feed rate is the dominant factor which influences the response of surface roughness. Increasing feed rate results is better Surface finish

5. CONCLUSION

   This paper has presented an investigation on the optimization and the effect of machining parameters on the surface roughness in End Milling operations. An optimum parameter combination for minimum SR was obtained by using the signal-to-noise (S/N) ratio. It can be observed from these tables that feed rate was the most dominant

   parameter influencing the surface roughness in Aluminum Matrix Composites. The fine surface roughness values obtained is 0.596µm using the optimal combination levels of machining parameter are speed 1500 rpm, feed rate 10 mm/min and Depth of cut 1.5mm/min.

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1. Y.Z. Zhan and G.D. Zhang: Mater. Des., 2006, 27,79.

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