Advances in Materials Science and Engineering

Volume 2014 (2014), Article ID 160519, 10 pages

http://dx.doi.org/10.1155/2014/160519

Research Article

Parametric Optimization of Squeeze Cast AC2A-Ni Coated Composite Using Taguchi Technique

A. R. Ravikumar,¹ K. S. Amirthagadeswaran,² and P. Senthil³

¹Department of Mechanical Engineering, Sri Shakthi Institute of Engineering & Technology, Coimbatore 641062, India

²Department of Mechanical Engineering, Government College of Technology, Coimbatore 641013, India

³Department of Mechanical Engineering, Coimbatore Institute of Engineering & Technology, Coimbatore 641109, India

Received 31 May 2013; Accepted 29 October 2013; Published 20 January 2014

Academic Editor: Martin Crimp

Copyright © 2014 A. R. Ravikumar et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

This paper mainly focusses on parametric optimization of squeeze cast AC2A Ni coated composite through Taguchi technique. Composite samples have been cast through squeeze casting for each experimental trial based on L16 orthogonal array. From analysis of variance (ANOVA), it has been found that reinforcement percentage, squeeze pressure, and pressure duration were the casting parameters making significant improvement in the mechanical properties such as hardness and ultimate tensile strength. Reinforcement percentage and squeeze pressure have been identified as the most influencing parameters from the percentage contribution analysis. The optimum parametric setting has been determined through Taguchi technique. It has been confirmed that AC2A-Ni coated composite obtained for the optimum parametric setting has exhibited better mechanical properties compared to the experimental trials.

1. Introduction

The increase in demand for light weight and energy efficient materials with high strength, stiffness, and wear resistance leads to the development of advanced materials like metal matrix composites (MMCs) [1–3]. Among the various matrix materials available, aluminium alloys are mostly employed in MMCs because of their light weight, economical viability, processing flexibility, corrosion resistance, high thermal conductivity, and heat treatment capability [4–6]. Particle reinforced aluminium metal matrix composites (PAMMCs) are the most attractive materials due to their improved strength, high modulus, and more resistance against wear and corrosion when compared to their monolithic alloy [7]. Even though specific strength of PAMMCs is not as high as that of continuous fiber reinforced MMCs, ease of processing, isotropic properties, and considerable cost make them potential candidates in various applications like aerospace, marine, military, and automobile [7, 8]. Moreover, the particle reinforcements reduce the troubles allied with manufacturing of continuous fiber reinforced MMCs such as fiber mismatch, fiber fracture, and heterogeneity in microstructure [9].

Oxides, carbides, nitrides, and borides are the various groups of ceramic reinforcements used in PAMMCs [10]. In the various groups, silicon carbide finds more application due to its low cost and easy availability [11]. In addition, SiC have been found to have excellent compatibility with the aluminium alloy matrix [12, 13].

MMCs are usually processed either by solid state processes (powder metallurgy) or liquid state processes (casting route) [14, 15]. In the former, distribution of the particle reinforcements is uniform and interfacial reactions can be controlled easily, but cost of the process is high. Casting is the most economical route of transferring the raw materials into the final near net shape and use of wide range of ceramic reinforcements is possible, but has difficulties like non uniform distribution of particles and extensive interfacial reactions [16]. Also the conventional casting has major drawbacks like porosities, hot tears, and so forth. Squeeze casting is known as very promising route of manufacturing near net shape MMCs economically in single step. In this process, solidification of melt takes place under high pressure, which eliminates formation of porosities caused by shrinkage and gas and also saves material by eliminating runner and riser. Moreover, shape tolerance, surface finish, and mechanical properties are highly improved with fine microstructure and adhesion of molten metal with reinforcement [11].

Seo and Kang [16] have reported that hardness and tensile strength of squeeze cast composite were improved with application of pressure up to 100 MPa. They have also noticed the fractures and split of many particles under an applied pressure of 130 MPa. Onat et al. [11] have noted that hardness of squeeze cast composite increased with the increase of volume fraction and squeeze pressure. Sukumaran et al. [17] have pointed out that squeeze cast composite has acquired mechanical properties which can be comparable with properties that are obtainable by hot working and also observed reduction in defect level due to applied pressure. Daoud et al. [18] have informed that application of squeeze pressure eliminated the excesses porosity and improved the hardness in the case of squeeze cast Al7075- Al₂O₃ composite.

Yue and Chadwick [19] have stated that there is no real value in manufacturing of particle reinforced composite castings with porosity, since the porosity dominates the mechanical responses during loading. Further, they declared that squeeze casting has a clear merit over its alternative techniques due to zero porosity. Suresh et al. [20] have identified that the squeeze pressure increased the mechanical properties of squeeze cast Al-Beryl composite compared to gravity cast composite. Kalkanli and Yilmaz [9] have observed that squeeze cast Al7075-SiCp composite revealed a maximum tensile strength when reinforcing 10% SiCp and also noticed that several samples were found with agglomerations. Kaynak and Boylu [21] have inferred that addition of Mg while processing squeeze cast Al-SiCp composite improved the wettability which resulted in certain bonding at the matrix-particulate interface. But, insufficient interfacial bond strength was noted under high stress level, which initiated crack at the interface.

However, there exist several problems in producing good quality PAMMCs. The main problem is the high reactivity (interfacial reaction) of SiCp with aluminium alloy to form aluminium carbide (Al₄C₃) which results in reinforcement degradation and reduction of composite strength. Another problem is poor wettability of ceramic particles in liquid aluminium alloy [22]. Particularly in Al-Si/SiCp composites, less silicon content leads to enhanced interfacial reactions and lack of wettability at the interface of the reinforcement and Al matrix. Ren et al. [23] have showed that the composite exhibited poor wettability, higher porosity, and poor thermophysical properties when Si content of Al alloy was lower than 6%. Samuel et al. [15] have made comparison of four composites and stated that low silicon content in the aluminium alloy accelerated the formation of Al₄C₃, while high silicon content decelerated the same. According to the research works [5, 24, 25], it is evident that the formation of Al₄C₃ could be suppressed by having a matrix alloy containing higher silicon content.

Metallic coating of the reinforcement is one of the successful methods to reduce or eliminate the interfacial reactions and promote wettability between SiCp and Al matrix. [5]. Tekmen and Cocen [26] have reported that squeeze cast Al alloy- (Al-7% Si-0.7% Mg) Ni coated SiCp composite showed improvement in the interfacial bonding and elimination of Al₄C₃. Ramesh et al. [27, 28] have reported that uniform distribution and excellent interfacial bonding of silicon nitride particles were highly achieved by good wettability of Ni-P coated silicon nitride (Si₃N₄) particles with Al matrix during the preparation of Al6061-Si₃N₄ composite. Also, they have stated that both mechanical and tribological properties were considerably improved with Ni-P coating. Yu et al. [29] have stated that tensile strength of squeeze cast Al6061-Y₂O₃ coated Al₂O₃ composite could be improved by 27% when compared to the uncoated one. Dikici et al. [30] have studied the effect of particle sol-gel coating on SiCp with A380 aluminium alloy composite and found clean and sharp interface between matrix and reinforcement. Ramesh et al. [31] have indicated that Ni-P coating on SiCp showed an appreciable improvement in mechanical properties of Al6061-SiCp composite.

From the literature, it was noted that Al- (less than 6%) Si alloy has not been considered as metal matrix with SiCp through squeeze casting process. In this direction, AC2A aluminium alloy has been considered as matrix and Ni coated SiCp as reinforcement for the production of squeeze cast AC2A-Ni coated SiCp composite in this study. The chemical composition of AC2A as per Japanese Industrial Standard (JIS H5202) is given in Table 1.

Table 1: Chemical composition of AC2A aluminium alloy.

Element
Si
Cu
Fe
Mg
Mn
Ti
Pb
Zn
Ni
Sn
Al

Standard (wt%)
4–6
3–4.5
<0.75
<0.25
<0.55
<0.2
<0.15
<0.55
<0.30
<0.05
Rest

Ingot analysis (wt%)
4.81
3.69
0.24
0.16
0.11
0.04
0.027
0.02
0.011
0.009
91

AC2A alloy is widely used for producing automotive components such as brake cylinder, master cylinder, engine brackets, cylinder heads, and rear axle housings. Senthil and Amirthagadeswaran [32] have stated that squeeze casting is a very effective technique to process AC2A aluminium alloy for the production of brake cylinder with improved mechanical properties. It is expected that the mechanical properties may be increased further while processing this alloy with the addition of Ni coated SiCp through squeeze casting. In order to improve the quality of castings, the casting parameters have to be carefully controlled and optimized. Taguchi technique was employed to find out the optimum parametric setting in this study.

2. Taguchi Technique

Taguchi technique is a powerful offline quality control concept used to design high quality systems. This technique offers a simple, systematic, and efficient way to optimize designs for improved performance and quality with reduced experimental time and cost [33, 34]. It utilizes robust design to solve lot of complex problems in manufacturing industries for product or process. The methodology is effective to deal with responses that are influenced by multivariables (parameters). This technique significantly reduces the number of experiments which are required to model the response function compared with the full factorial design of experiments. Further, this technique determines the most influential parameter of the system, which, on control, would result in significant improvement in the performance [25].

Taguchi technique employs a special design of orthogonal arrays to study the entire parameter space with only a small number of well balanced experiments and signal-noise () ratio as the quality characteristic of choice [35]. ratio is the ratio of the mean (signal) to the standard deviation (noise). The quality characteristics normally used are lower-the-better, larger-the-better, and nominal-the-best [36]. This technique is executed with the following steps.

(i)Identify process parameters influencing output response of the process.(ii)Choose a suitable orthogonal array to carry out experiments.(iii)Examine the results to find out optimum parametric setting.(iv)Execute a statistical analysis of variance (ANOVA) to find significant parameters.(v)Run a confirmatory test using the optimum setting.

Five casting parameters, namely, reinforcement percentage, pouring temperature, mould temperature, squeeze pressure, and pressure duration, each at four levels were selected. A four level L₁₆(4⁵) orthogonal array with sixteen experimental runs was selected. Hardness and ultimate tensile strength were considered as quality characteristics with the concept of the “larger the better.” Mathematical equation of the ratio used for these types of response is given in

where and is the response value for an experimental condition repeated times.

3. Experiments and Tests

3.1. Experimental Details

3.1.1. Ni Coating on SiCp

Silicon carbide powder with particle size of range 5–40 μm was used as reinforcement. Silicon carbide particles were cleaned, sensitized, and activated with acetone, SnCl₂, and PdCl₂, respectively. Then, the activated particles were coated by using electroless plating bath containing 25 g NiSO₄·6H₂O, 9 g NaC₂H₃O₂, 23 g NaH₃PO₂·H₂O, and 0.001 g Pb²⁺ dissolved in 1litre distilled water (Figure 1).

Figure 1: Electroless nickel coating.

3.1.2. Squeeze Casting of AC2A-Ni Coated SiCp Composite

AC2A aluminium alloy was used as metal matrix. 5 Kg AC2A was melted in a graphite crucible by using an electric induction furnace and we waited until a homogeneous liquid phase is obtained. During melting, the surface of the melt was covered by coverall flux in order to avoid the entrapment of gases into the melt. After getting homogeneous liquid phase, the melt was degassed by using hexachloroethane degasser. The pure melt after degassing was agitated by using mechanical stirrer rotating at a speed of 300 rpm to create fine vortex. While stirring constantly for 10 minutes, Ni coated SiC particles were gradually added into the fine vortex. The addition of reinforcement is shown in Figure 2.

Figure 2: Addition of reinforcement.

Blue Star universal testing machine (Model: UTE-40) of 40 tonne capacity with little modification shown in Figure 3 was employed to apply pressure on the liquid melt in the mould cavity for direct squeeze casting. SG400 spheroidal graphite iron (split mould material), EN8 alloy steel (punch material), and Dycote D140 (coating material on surfaces of mould cavity) were used during the conduct of experiments. Two electrical heaters were employed to preheat split mould assembly and punch. The composite melt was poured into the preheated mould cavity. Pressure was applied on the melt through the preheated punch and maintained until solidification was completed. Punch was then withdrawn and the casting was separated from the mould assembly.

Figure 3: Squeeze casting setup.

3.1.3. Parametric Constraints

The reinforcement (Ni coated SiCp) less than 2.5 wt% did not show any appreciable improvement in mechanical properties and the reinforcement greater than 10 wt% led to agglomerations in the castings. So, the addition of reinforcement was varied from 2.5 wt% to 10 wt%. Pouring temperature of 675°C was required for the effective reinforcement of SiCp in the melt. When pouring temperature was raised above 750°C, Ni coating on SiCp got degraded. The mould assembly was designed to withstand maximum squeeze pressure of 125 MPa. It was observed that there was an existence of micro pores in the castings for pressures below 50 MPa. The mould temperatures below 200°C resulted in premature solidification and temperatures above 350°C increased solidification time leading to loss in production and decreased life of the mould assembly. It was experimentally found that pressure duration from 25 seconds to 55 seconds exhibited an appreciable improvement in mechanical properties. Hence, the bounds for all these casting parameters were set as follows.

 Reinforcement weight percentage, (%): , pouring temperature, (°C): , squeeze pressure, (MPa): , mould temperature, (°C): , pressure duration, (s): .

All process parameters were fixed at four levels within the above bounds to conduct experiments according to L₁₆ (4⁵) orthogonal array. The details of all parameters and their levels are given in Table 2. Brake cylinder samples were cast for each experimental condition based on the array. A set of samples is shown in Figure 4.

Table 2: Levels for process control parameters.

Casting parameter
Notation
Level 1
Level 2
Level 3
Level 4

Reinforcement percentage (%)

2.5
5
7.5
10

Pouring temperature (°C)

675
700
725
750

Squeeze pressure (MPa)

50
75
100
125

Mould temperature (°C)

200
250
300
350

Pressure duration (s)

25
35
45
55

Figure 4: Squeeze cast samples.

3.2. Testing

3.2.1. Hardness Test

For Brinell hardness test, 250 kg load was applied through a ball indenter of 5 mm diameter on polished surface of the specimen and hardness values (BHN) were measured in four spots of functional areas as shown in Figure 5.

Figure 5: Locations of test specimens.

3.2.2. Tensile Test

INSTRON universal testing machine was employed for performing tensile test on the specimens. Four tensile test specimens, each of 4.53 mm diameter with a gauge length of 16 mm, were prepared and readings were noted.

4. Results and Discussion

4.1. Ratio Response

The ratios for hardness and ultimate tensile strength were calculated using (1) for each parametric setting and their values are given in Table 3.

Table 3: Design of experiments using L₁₆(4⁵) array.

Ex no.
Parametric setting
Hardness (BHN)
Ultimate tensile strength (MPa)
ratio for hardness
ratio for ultimate tensile strength

R₁
R₂
R₃
R₄
R₁
R₂
R₃
R₄
(dB)
(dB)

1

91
87
91
90
259
248
259
256
39.0562
48.1437

2

110
104
108
107
313
296
308
305
40.6026
49.6948

3

124
118
123
122
350
333
347
344
41.7047
50.7139

4

112
106
111
110
319
302
316
313
40.8023
49.8914

5

117
111
115
116
333
316
328
330
41.1898
50.2791

6

115
109
113
112
328
310
322
319
40.9988
50.0908

7

127
121
126
125
362
345
359
356
41.9164
51.0125

8

128
122
126
124
365
347
359
353
41.934
51.0244

9

140
134
138
137
399
382
393
390
42.747
51.8403

10

121
116
121
120
345
330
345
342
41.5434
50.6379

11

120
114
117
120
342
325
333
342
41.4133
50.508

12

127
121
126
125
362
345
359
356
41.9164
51.0125

13

138
133
138
136
393
379
393
387
42.6837
51.7737

14

142
136
140
139
404
387
399
396
42.8727
51.9617

15

122
118
121
120
347
336
345
342
41.5997
50.6913

16

121
117
121
120
345
333
345
342
41.563
50.6587

Mean

Mean value of ratios was also calculated for hardness and ultimate tensile strength and their values () are given in Table 3. Consider

where (here ) and is ratio for th parametric setting. In order to find optimum level of the process parameters, average ratio response was estimated for every level of each parameter and the corresponding details are given in Tables 4 and 5. Based on the highest value of ratio, an optimum level for each parameter (: 4th level; : 3rd level; : 3rd level; : 2nd level; and : 3rd level) was noted. The optimum casting condition (reinforcement percentage of 10%, pouring temperature of 725°C, squeeze pressure of 100 MPa, mould temperature of 250°C, and pressure duration of 45 s) was noted to be same for both output responses. This is due to both output responses being often related in all aluminium alloy composites. The response graphs shown in Figures 6 and 7 described the variation of each process control parameter on the performance of the squeeze casting process. From the response graphs, it was observed that parameters and showed lesser variations on the output responses compared to other parameters. Therefore, analysis of variance (ANOVA) and test were used to analyze the experimental data.

Table 4: Average ratio response for hardness.

Level 1
40.5415
41.4192
40.7579
41.4404
41.0333

Level 2
41.5098
41.5044
41.3271
41.6584
41.7072

Level 3
41.905
41.6585
42.3146
41.5002
41.8259

Level 4
42.1798
41.5539
41.7365
41.537
41.5696

Max-Min
1.63833
0.23934
1.55676
0.21799
0.79258

Rank
1
4
2
5
3

Optimum level

Table 5: Average ratio response for ultimate tensile strength.

Level 1
49.6109
50.5092
49.8503
50.5326
50.1243

Level 2
50.6017
50.5963
50.4194
50.7502
50.8016

Level 3
50.9997
50.7314
51.3851
50.5724
50.8977

Level 4
51.2713
50.6467
50.8289
50.6284
50.66

Max-Min
1.6604
0.22218
1.53478
0.21766
0.7734

Rank
1
4
2
5
3

Optimum level

Figure 6: Response graph for hardness.

Figure 7: Response graph for ultimate tensile strength.

4.2. Analysis of Variance

Analysis of variance was performed on signal to noise ratios to find the significance of the process control parameters and their contribution in the process performance. The following terms were calculated and their values are given in Tables 6 and 7.

(i)Sum of squares due to mean:

(ii)Sum of squares due to parameter :

 Similarly, sum of squares due to parameters , , , and were calculated. Sum of squares due to parameters and were found to be less in this study. Therefore, their effects on the output responses were assumed to be negligible and treated as an error (pooled error). Sum of squares due to pooled error was also calculated as follows:

(iii)Total sum of squares:

Table 6: ANOVA for hardness.

Source
Pool
SS
DOF
MSS
ratio
PSS
PC (%)

6.16166
3
2.05389
55.6621
6.051
46.4248792

Yes
0.11986
3
0.03995

5.18222
3
1.72741
46.8141
5.072
38.9102514

Yes
0.10154
3
0.03385

1.46861
3
0.48954
13.2669
1.358
10.4183344

Pooled error

0.2214
6
0.0369

0.553
4.24653502

TSS

13.0339

13.03

Table 7: ANOVA for ultimate tensile strength.

Source
Pool
SS
DOF
MSS
ratio
PSS
PC (%)

6.34772
3
2.11591
60.0074
6.242
47.8843

Yes
0.10382
3
0.03461

5.04659
3
1.6822
47.7073
4.941
37.9028

Yes
0.10774
3
0.03591

1.42958
3
0.47653
13.5144
1.324
10.1554

Pooled error

0.21156
6
0.03526

0.529
4.05748

TSS

13.0355

13.04

(iv)Degree of freedom for parameter: . Degree of freedom for pooled error: .(v)Mean sum of squares due to parameter :

 Similarly, mean sum of squares for all other parameters and pooled error were calculated.(vi) ratio for parameter ,

 Similarly, ratio was calculated for parameters and . The calculated ratio for parameters , , and was found to be greater than the distribution value ( at 5% level of significance). Therefore, the parameters , , and were confirmed as significant parameters in this study.(vii)Pure sum of squares due to parameter :

(viii)Percentage contribution of parameter ,

 Similarly, pure sum of squares and percentage contribution of parameters , , and pooled error were calculated. The percentage contribution of pooled error was noted to be less than 5% for both output responses in this study. The percentage contribution of all significant parameters is clearly shown in Figure 8.

Figure 8: Percentage contribution.

4.3. Predicted Mean and Confidence Interval

Predicted mean for hardness and ultimate tensile strength and confidence interval (CI) for the predicted mean were determined by using the following:

where and = (Number of experiments)/(1 + Total DOF associated with ).

The confidence interval for hardness and ultimate tensile strength was noted to be ±0.37 dB and 0.36 dB, respectively, at 5% level of significance. The predicted mean of hardness (43.26 dB) showed the variation from 42.89 to 43.63 dB. The predicted mean of ultimate tensile strength (52.31 dB) showed the variation from 51.95 to 52.67 dB.

4.4. Confirmation Experiments

Two samples were made for the optimum parametric setting. The values of hardness and ultimate tensile strength measured in the functional volume were found to be 147, 141, 145, and 144 BHN and 419, 402, 414, and 410 MPa, respectively, and their ratios were 43.18 dB and 52.28 dB, respectively. These ratio values were found within the confidence interval limits. A comparison was made for different casting conditions (: 0.1 MPa , , , and ) in the microstructural aspect as shown in Figure 9. The castings obtained for optimum condition showed better grain refinement and uniform distribution of reinforcements when compared with other conditions.

Figure 9: Microstructures. (a) Gravity cast at : 0.1MPa , (b) squeeze cast at low level within DOE, (c) squeeze cast at better level within DOE, (d) squeeze cast at optimum level .

5. Conclusion

Taguchi technique was employed to find the optimum parametric setting of squeeze casting process for producing high quality castings of AC2A-Ni coated SiCp Composite. The optimum parametric setting was found as follows:

 reinforcement percentage: 10%, pouring temperature: 725°C, squeeze pressure: 100 MPa, mould temperature: 250°C, pressure duration: 45 seconds.

This setting was verified through the confirmation experiments. The castings produced for the optimum setting were found to be defects free and sound. From the ANOVA, reinforcement percentage, squeeze pressure, and pressure duration were identified as significant casting parameters in this study. From the percentage contribution analysis, it was noted that reinforcement percentage and squeeze pressure were the most important parameters for the improvement of mechanical properties.

Nomenclature

BHN: | Brinell hardness number
DOF: | Degree of freedom
DOE: | Design of experiments
gpl: | Gram per litre
MSS: | Mean sum of squares
: | Number of experiments
: | Number of observations
PC: | Percentage contribution
PSS: | Pure sum of squares
R₁: | Readings measured in spot P
R₂: | Readings measured in spot Q
R₃: | Readings measured in spot R
R₄: | Readings measured in spot S
SS: | Sum of squares
TSS: | Total sum of squares.

Conflict of Interests

The authors declare that they have no conflict of interests regarding the publication of this paper.

Acknowledgments

The authors are thankful to M/S Unique Shell Mould (India) Pvt. Ltd., Coimbatore, and Sri Krishna College of Engineering and Technology, Coimbatore, for providing research facilities to carry out this research work.

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