Composite with aluminium 6061 matrix using red mud reinforcement to reduce the cost have been fabricated by stir casting method. A stirring arrangement has been used to ensure the uniform distribution. Scanning electron microscopy has been used to verify the uniform distribution of the reinforcement particles and energy dispersive spectroscopy has been used to confirm the presence of reinforcement inside Aluminium 6061 matrix. Macro Hardness has been obtained using Rockwell hardness tester at 60kg load by using 1/8inch steel ball at H scale and Vickers micro hardness measured using Vickers micro-hardness tester. The results have been analysed by applying Taguchi technique. The value of macro hardness and micro hardness has been found to be increased with an increase in percentage of reinforcement and ageing time, while it shows a reverse trend with increase in particle size of the reinforcement. The ANOVA analysis of the data observes that the ageing time has significant effect and particle size has least effect on both macro and micro hardness of the developed composite. Further, the experimental and predicted results have been found in close proximity to each other.

In Metal matrix composites (MMCs), hard ceramic reinforcements have been distributed in a matrix of metal or alloy. In such composites, both matrix and reinforcements has been physically and chemically separate phases [1,2]. MMCs exhibits hybridisation of valuable properties like high stiffness, strength, corrosion resistance, hardness, lightweight and high wear resistance when compared with the parent metal or alloy [2–5]. MMCs reinforced with particles have great potential of application in the fields of automobile, aircraft and transport industries [6–8]. Aluminium based MMCs has been used in making components of automobile, aerospace, marine and mineral processing equipments [9–11]. Aluminium metal matrix Composites (AMMCs) with ceramic particle reinforcements has been mostly used composite materials since they can be processed like unreinforced metal and alloys [12]. Ageing of MMCs can significantly improve the hardness [13]. AMMCs can be reinforced with hard ceramic reinforcements like SiC, Al2O3, B4C, TiC, TiB2, MgO, TiO2 and BN [14]. AMMCs can be fabricated using liquid state processing techniques and solid state processing techniques. Liquid state processing includes stir casting, squeeze casting, liquid infiltration, spray co-deposition, rheocasting and compocasting. Solid state processing such as powder metallurgy techniques, extrusion has been employed [15–17]. Out of the above discussed fabrication methods stir casting has been most simple, economical and flexible method. In this technique aluminium has been melted in an electrical furnace. Then molten aluminium is stirred with a stirrer to form vortex. Particle reinforcement should be added to the vortex at constant rate for uniform distribution. Then the mixture has been poured into moulds to obtain castings [18–20]. The distribution of reinforcement can be examined using scanning electron microscopy (SEM). Uniform distribution of particle reinforcement is necessary to obtain uniform properties [21]. Design of experiments (DOE) may be used to find out the impact of various parameters on the output in a systematic manner to reduce number of experiments, time and money. The DOE generally includes three steps: planning of experiment, conducting the experiment and the analysis of results. The planning phase has been most important out of these three phases [2]. The DOE techniques such as Taguchi method and response surface methodology (RSM) has become important during recent years [22]. In Taguchi design of experiment, orthogonal array has been used to reduce the number of experiments. This method is very simple, accurate, efficient and systematic to optimise performance, quality and cost [23]. The analysis of variance (ANOVA) can be used to find the significance of parameters [24]. The statistical relation between the output variable and input variables in an experiment can be determined by using some modelling techniques [25].

Literature reveals that very limited work on the effect of different parameters on macro and micro hardness of red mud based aluminium composite has been reported. Based on the findings of the literature, the authors have decided to work towards the development of red mud based aluminium composite with varying percentage and particles size of the reinforcement (Red mud), and their influence on the macro and micro hardness of the developed composite. During experimentation, to ensure the uniform distribution proper stirring arrangements has been done. Taguchi technique has been used to design the experiments for macro and micro hardness. SEM has been carried out to observe the uniform distribution in the developed composite matrix. Predicted results has also been validated by confirmation experiment and the ranking of influencing parameters has been ranked.

2Materials and Method2.1Material PreparationAl 6061 which has been commercially available was selected as matrix material. Red Mud, an industrial waste has been selected as reinforcement material. Red mud has been procured from HINDALCO, Renukut, Uttar Pradesh, India. XRF analysis of red mud has been carried out and the major constituents have been Fe2O3-35.26%, Al2O3-21.89%, TiO2-15.11%, SiO2-12.46%, Na2O-11.82%, CaO-1.83% etc. Design of experiments has been carried out using Taguchi Orthogonal Array. L25 Orthogonal Array (OA) has been selected according to number of parameters and levels of parameters. The parameters selected, and their levels taken have been shown in Table 1. The parameters and their levels has been selected after taking into consideration different parameters influencing hardness for different composite materials available in literature.

Using stir casting technique, Aluminium has been melted in a graphite crucible to a temperature of 900°C inside a muffle furnace shown in Fig. 1.

Stirring of melted aluminium has been done with a mechanical stirrer shown in Fig. 1 to form a vortex. Preheated reinforcement preheated at 400°C has been added to vortex which ensures uniform distribution of particles. Magnesium has also been added in the melt to improve the wettability of the particles. The melt has been poured in metallic moulds to obtain the castings. After the fabrication aluminium red mud composite has been heat treated at 525°C for eight hours and then quenched in water. Scanning electron microscopy (SEM) of fabricated sample shows that the uniform distribution of particles has been observed. Fig. 2.

Energy dispersive spectroscopy (EDS) confirms the presence of constituents of red mud inside the aluminium 6061 matrix. Spectrum of EDS has been shown in Fig. 3.

2.2Macro Hardness TestMacro (Rockwell) hardness of the prepared specimens has been done on Standard Rockwell hardness testing machine. Specimens of size 10mm diameter and 15mm length have been prepared. Value of hardness has been taken by using steel ball indenter at H scale. Diameter of steel ball was 1/8″ (3.175mm). A load of 60kgf was used which includes 10kgf minor load and 50kgf major load. Readings have been taken at three different locations to avoid errors.

2.3Micro hardnessVicker's Micro hardness of the prepared specimens has been done on vicker's micro hardness tester. For conducting the tests, specimens of size 10mm diameter and 10mm length were prepared. Surface of the specimen have been polished using fine emery papers and after that by a polishing cloth using a polishing agent. The test method IS 1501-2002 has been used. Three readings for every type of sample have been taken at three different locations to avoid errors.

3Results and discussion3.1Macro hardnessIn order to find out the effect of parameters under study on hardness, these parameters have been studied at five levels. L25 orthogonal array have been selected for conducting the experiments. Seventy five experiments have been conducted with a repetition of three. The results obtained for hardness has been reported in Table 2. There are three types of quality characteristics in Taguchi method as follows: smaller is better, nominal is better and larger is better. For the present study, larger the better criteria have been chosen.

Macro-hardness results with S/N ratios.

Experiment no. | Percentage reinforcement | Particle Size | Ageing Time | Rockwell Hardness | S/N Ratio |
---|---|---|---|---|---|

1 | 4 | 250 | 0.5 | 11.00 | 20.82785 |

2 | 4 | 177 | 6 | 18.00 | 25.10545 |

3 | 4 | 149 | 12 | 26.00 | 28.29947 |

4 | 4 | 74 | 18 | 35.00 | 30.88136 |

5 | 4 | 125 | 24 | 53.00 | 34.48552 |

6 | 8 | 250 | 6 | 19.00 | 25.57507 |

7 | 8 | 177 | 12 | 47.33 | 33.50273 |

8 | 8 | 149 | 18 | 46.00 | 33.25516 |

9 | 8 | 74 | 24 | 58.00 | 35.26856 |

10 | 8 | 125 | 0.5 | 14.67 | 23.3286 |

11 | 12 | 250 | 12 | 39.00 | 31.82129 |

12 | 12 | 177 | 18 | 44.00 | 32.86905 |

13 | 12 | 149 | 24 | 57.00 | 35.1175 |

14 | 12 | 74 | 0.5 | 24.00 | 27.60422 |

15 | 12 | 125 | 6 | 27.33 | 28.73279 |

16 | 16 | 250 | 18 | 51.00 | 34.1514 |

17 | 16 | 177 | 24 | 55.00 | 34.80725 |

18 | 16 | 149 | 0.5 | 20.00 | 26.0206 |

19 | 16 | 74 | 6 | 34.00 | 30.62958 |

20 | 16 | 125 | 12 | 45.00 | 33.06425 |

21 | 20 | 250 | 24 | 65.00 | 36.25827 |

22 | 20 | 177 | 0.5 | 21.67 | 26.71718 |

23 | 20 | 149 | 6 | 38.00 | 31.59567 |

24 | 20 | 74 | 12 | 48.00 | 33.62482 |

25 | 20 | 125 | 18 | 58.00 | 35.26856 |

Table 3 shows the means of S/N ratios and mean values for macro hardness of the developed composite at each level. The analysis shows that the ageing time affects the macro hardness most (rank 1), whereas, it has least affected by particle size (rank 3).

ANOVA table for Macro-hardness.

Source | Degree of Freedom | Sum of Squares | Mean Squares | F Ratio | P value | Percentage Contribution |
---|---|---|---|---|---|---|

Percentage reinforcement | 4 | 66.505 | 16.626 | 9.32 | .001 | 15.22 |

Particle Size | 4 | 9.287 | 2.322 | 1.30 | .324 | 2.12 |

Ageing Time | 4 | 339.668 | 84.917 | 47.61 | 0.000 | 77.75 |

Residual Error | 12 | 21.401 | 1.783 | 4.89 | ||

Total | 24 | 436.862 |

The analysis of variance (ANOVA) has been used to find out which parameters significantly affect the macro hardness. ANOVA table for S/N ratios has been given in Table 4. The Fishers (F) value shows that impact of ageing time has been highest followed by percentage reinforcement and particles size. Percentage contribution of each parameter has been given as reinforcement (15.22%), Particle size (2.12%) ageing time (77.75%). P value tells about the significance of the affecting parameters and its value for significant parameter must be less than 0.05 [26,27]. The result shows that the percentage reinforcement and ageing time significantly affect the macro-hardness.

Result of Micro-hardness and S/N ratio.

Experiment no. | Percentage reinforcement | Particle Size | Ageing Time | Micro Hardness | S/N Ratio |
---|---|---|---|---|---|

1 | 4 | 250 | 0.5 | 28 | 28.9432 |

2 | 4 | 177 | 6 | 40 | 32.0412 |

3 | 4 | 149 | 12 | 42 | 32.4650 |

4 | 4 | 74 | 18 | 60 | 35.5630 |

5 | 4 | 125 | 24 | 58 | 35.2686 |

6 | 8 | 250 | 6 | 40 | 32.0412 |

7 | 8 | 177 | 12 | 47 | 33.4420 |

8 | 8 | 149 | 18 | 53 | 34.4855 |

9 | 8 | 74 | 24 | 69 | 36.7770 |

10 | 8 | 125 | 0.5 | 42 | 32.4650 |

11 | 12 | 250 | 12 | 49 | 33.8039 |

12 | 12 | 177 | 18 | 50 | 33.9794 |

13 | 12 | 149 | 24 | 62 | 35.8478 |

14 | 12 | 74 | 0.5 | 50 | 33.9794 |

15 | 12 | 125 | 6 | 47 | 33.4420 |

16 | 16 | 250 | 18 | 51 | 34.1514 |

17 | 16 | 177 | 24 | 70 | 36.9020 |

18 | 16 | 149 | 0.5 | 46 | 33.2552 |

19 | 16 | 74 | 6 | 64 | 36.1236 |

20 | 16 | 125 | 12 | 50 | 33.9794 |

21 | 20 | 250 | 24 | 75 | 37.5012 |

22 | 20 | 177 | 0.5 | 46 | 33.2552 |

23 | 20 | 149 | 6 | 57 | 35.1175 |

24 | 20 | 74 | 12 | 67 | 36.5215 |

25 | 20 | 125 | 18 | 77 | 37.7298 |

The optimum value of Rockwell hardness and its confidence interval has been predicted theoretically using Taguchi's approach. By recognising the effect of factors, optimum value of Rockwell hardness has been calculated. The significant process parameters for Rockwell hardness are A5 and C5. The mean value of calculated Rockwell hardness has been given as [28]:

Where, TRHN is the average of all values of Rockwell hardness and its value was 38.20 RHN; A¯5 represents average value of Rockwell hardness at fifth level of reinforcement and its value was 46.13 RHN; C¯5 represents average value of Rockwell hardness at fifth level of ageing time and its value was equal to 35.19 RHN. By substituting all these values in equation 1, we get, μRHN = 43.12 RHN.

Predicted value of confidence interval can be obtained using the relation [28]

Where, CI=Confidence interval; Fα(1,fe)=The F-ratio at a confidence level of (1-α) against DOF=1 and error DOF (fe); Ve=Variance of error; R=Sample size for confirmation experiment; Neff=Effective number of replications=N/[1+total DOF in the estimation of mean]; N=Total number of results=75

Using the following values: Ve=1.783 (Table 4); Total degree of freedom in estimation of mean=8; neff=8.33; F0.05(1,8)=5.32

The confidence interval obtained was given as 2.19.

The CI of predicted Rockwell hardness at 95% confidence Interval=43.13±2.19 RHN

The optimum value of process parameters for the predicted range of Rockwell hardness obtained has been given as:

Reinforcement: 20%; Grain size: 74; Ageing time: 24 Hr.

3.1.3Confirmation ExperimentsOn the basis of conclusions drawn based on Taguchi's method, predicted results are verified by confirmation experiments. The castings have been done and experiments are conducted using optimum values of significant parameters. The average value of results has been reported in Table 5. The results obtained have been compared with estimated values. It has been observed that the experimental results come out to be near about the predicted results and reported well within the limits of confidence interval predicted.

ANOVA table for micro-hardness.

Source | Degree of Freedom | Sum of Squares | Mean Squares | F Ratio | P value | Percentage Contribution |
---|---|---|---|---|---|---|

Percentage reinforcement | 4 | 27.985 | 6.9964 | 14.12 | .000 | 28.39 |

Particle Size | 4 | 17.275 | 4.3187 | 8.71 | .002 | 17.52 |

Ageing Time | 4 | 47.369 | 11.8423 | 23.89 | 0.000 | 48.05 |

Residual Error | 12 | 5.947 | .4956 | 6.03 | ||

Total | 24 | 98.577 |

The way in how variables affect Rockwell hardness has been shown in Fig. 4.

Fig. 4 shows that the hardness increases with an increase in red mud content and this may be due to inclusion of hard ceramic constituents of red mud inside the Aluminium 6061 matrix same trend for aluminium alloy with the addition of ceramic reinforcement has been obtained by Selvakumar et al. [29]. With an increase in particle size of red mud, the value of hardness decreases. Reduction of hardness with an increase in size of particle may be due to more in-spreading of particles in the matrix with decrease in particle size as the number of particles are more in smaller size at same level of reinforcement. Hardness has also been found increasing with an increase in ageing time of the composite. This effect may be due to reduction in porosity of fabricated composite. In ANOVA analysis, it has been found that effect of percentage reinforcement and ageing time has been significant, while the effect of particle size has not been found significant. Ageing time has maximum effect on hardness followed by percentage reinforcement and particle size, respectively.

3.2Micro-hardnessTo find out the effect of chosen parameters on Vicker's micro-hardness, five levels of the parameters have been considered. L25 orthogonal array have been employed for conducting the experiments. Seventy five numbers of experiments has been done with a repetition of three. The results obtained for hardness has been reported in Table 6. ‘Larger is better’ quality characteristics of Taguchi technique have been chosen for the current study.

Result of Micro-hardness and S/N ratio.

Experiment no. | Percentage reinforcement (by wt.) | Particle Size (μm) | Ageing Time (hr.) | Micro Hardness (HV) | S/N Ratio |
---|---|---|---|---|---|

1 | 4 | 250 | 0.5 | 28 | 28.9432 |

2 | 4 | 177 | 6 | 40 | 32.0412 |

3 | 4 | 149 | 12 | 42 | 32.4650 |

4 | 4 | 74 | 18 | 60 | 35.5630 |

5 | 4 | 125 | 24 | 58 | 35.2686 |

6 | 8 | 250 | 6 | 40 | 32.0412 |

7 | 8 | 177 | 12 | 47 | 33.4420 |

8 | 8 | 149 | 18 | 53 | 34.4855 |

9 | 8 | 74 | 24 | 69 | 36.7770 |

10 | 8 | 125 | 0.5 | 42 | 32.4650 |

11 | 12 | 250 | 12 | 49 | 33.8039 |

12 | 12 | 177 | 18 | 50 | 33.9794 |

13 | 12 | 149 | 24 | 62 | 35.8478 |

14 | 12 | 74 | 0.5 | 50 | 33.9794 |

15 | 12 | 125 | 6 | 47 | 33.4420 |

16 | 16 | 250 | 18 | 51 | 34.1514 |

17 | 16 | 177 | 24 | 70 | 36.9020 |

18 | 16 | 149 | 0.5 | 46 | 33.2552 |

19 | 16 | 74 | 6 | 64 | 36.1236 |

20 | 16 | 125 | 12 | 50 | 33.9794 |

21 | 20 | 250 | 24 | 75 | 37.5012 |

22 | 20 | 177 | 0.5 | 46 | 33.2552 |

23 | 20 | 149 | 6 | 57 | 35.1175 |

24 | 20 | 74 | 12 | 67 | 36.5215 |

25 | 20 | 125 | 18 | 77 | 37.7298 |

The Table 7 shows the means of S/N ratios and mean values for micro hardness of the developed composite at each level. The analysis ranks the ageing time as one, and which means it mainly affects the macro hardness, whereas, particle size has been ranked 3 which means it affects the hardness least.

Response table of S/N ratios for micro-hardness.

Responses of S/N ratios for micro-hardness | |||
---|---|---|---|

Level | Percentage Reinforcement (by wt.) | Particle Size (μm) | Ageing Time (hr.) |

1 | 32.86 | 35.79 | 32.38 |

2 | 33.84 | 34.58 | 33.75 |

3 | 34.21 | 34.23 | 34.04 |

4 | 34.88 | 33.92 | 35.18 |

5 | 36.03 | 33.29 | 36.46 |

Delta | 3.17 | 2.50 | 4.08 |

Rank | 2 | 3 | 1 |

Responses of means of micro-hardness | |||

1 | 45.60 | 62.00 | 42.40 |

2 | 50.20 | 54.80 | 49.60 |

3 | 51.60 | 52.00 | 51.00 |

4 | 56.20 | 50.60 | 58.20 |

5 | 64.40 | 48.60 | 66.80 |

Delta | 18.80 | 13.40 | 24.40 |

Rank | 2 | 3 | 1 |

The analysis of variance (ANOVA) has been done to find out which parameters significantly affect the macro hardness. ANOVA table for S/N ratios has been given in Table 8. The Fishers (F) value shows that impact of ageing time (23.89) is highest when compared to percentage reinforcement (14.12) and particles size (8.71). Percentage contribution of each parameter has been given as reinforcement=28.39%, Particle size=17.52%, and ageing time=48.05%. P value tells about the significance of the affecting parameters and its value for significant parameter must be less than 0.05 [26,27]. The result shows that all the parameters are significantly affecting the micro-hardness.

ANOVA table for micro-hardness.

Source | Degree of Freedom | Sum of Squares | Mean Squares | F Ratio | P value | Percentage Contribution |
---|---|---|---|---|---|---|

Percentage reinforcement (by wt.) | 4 | 27.985 | 6.9964 | 14.12 | .000 | 28.39 |

Particle Size (μm) | 4 | 17.275 | 4.3187 | 8.71 | .002 | 17.52 |

Ageing Time (hr.) | 4 | 47.369 | 11.8423 | 23.89 | 0.000 | 48.05 |

Residual Error | 12 | 5.947 | .4956 | 6.03 | ||

Total | 24 | 98.577 |

The optimum value of micro-hardness and its confidence interval have been predicted theoretically using Taguchi's approach. By recognising the effect of factors, optimum value of micro hardness has been calculated. The significant process parameters for micro hardness are A5, B1 and C5. The mean value of calculated micro-hardness can be given as [28]:

Where, T¯HV has been average of all values of Micro hardness and reported as 53.60 HV; A¯5 represents average value of micro-hardness at fifth level of reinforcement and reported as 64.40 HV; B¯1 reported as average value of Micro Hardness at first level of reinforcement and has been equal to 62.00 HV; C¯5 represents average value of micro-hardness at fifth level of ageing time and given as 66.80 HV. By substituting all these values in equation 3, we get, μHV=86 HV. Predicted value of confidence interval can be obtained using equation 2.

Using the following values:

Ve=0.4956 (Table 8); Total degree of freedom in estimation of mean=12; neff=5.769; F0.05 (1, 12)=4.75

The confidence interval=1.11

The CI of predicted micro-hardness at 95% confidence Interval is=86±1.11 HV

The optimum value of process parameters for the predicted range of micro-hardness given as:

Reinforcement: 20%; Grain size: 74μm; Ageing time: 24 Hr.

3.2.3Confirmation ExperimentsOn the basis of conclusions drawn based on Taguchi's method predicted results have been verified by confirmation experiments. The castings have been done and experiments have been conducted using optimum values of significant parameters. The average value of results has been reported in Table 9. The results obtained have been compared with estimated values. It has been found that experimental results have been near about the predicted results and observed within the limits of confidence interval predicted.

3.2.4Effect of selected Parameters on Micro-hardnessThe pattern of micro hardness behaviour with variables has been shown in Fig. 5.

The micro-hardness has been found of increasing nature with an increase in percentage of red mud and similar trend of micro-hardness has been observed in composites reported by Karabulut et al. [30] and Topcu et al. [31]. This may be due to an increase in hard reinforcement particles inside the matrix. Analysis also shows that with decrease in size of reinforcement particles, micro-hardness increases. Decrease in value of micro hardness with increase in particle size may be due to increase in voids and decrease in surface contact between the particles and matrix. It has also been found that with an increase in ageing time of the developed composite, micro-hardness of the composite increases and similar kind of trends has been reported in literature for some other aluminium based composites. This improvement in micro-hardness may be due to the reduction in porosity of the fabricated composites. In ANOVA analysis all the variables, i.e., percentage reinforcement, particle size and ageing time has been found significant. The order of significance of the factors has been ageing time, percentage reinforcement and particle size, respectively.

4ConclusionsRed mud based Aluminium 6061 composite has been successfully fabricated using stir casting method by achieving uniform dispersion of reinforcement particles. SEM images verify that uniform distribution of red mud particles has been obtained in Aluminium matrix. It has been found that the value of Rockwell hardness increased with an increase in percentage of reinforcement particles and ageing time, whereas, it shows a reverse trend with an increase in particle size. From ANOVA analysis, it has been found that the effect of percentage of reinforcement is 15.22% and ageing time is 77.75% and has significant effect on macro hardness of the composite, however, the effect of particle size is 2.12% and has not been found significantly effecting the hardness. Hence, it can be concluded that the ageing time has been most influencing parameter for macro hardness followed by percentage reinforcement and particle size.

Further, micro hardness shows an improvement with an increase in percentage of reinforcement particles and ageing time and has been found to be decreased with an increase in size of reinforcement particles. ANOVA analysis for micro-hardness concludes that all parameters are significantly affecting the micro hardness and the order of significance with their contribution is ageing time (48.5%), percentage of reinforcement (28.39%), and particle size (17.52%), respectively. Also, theoretically predicted and practically obtained results of confirmation experiments for macro and micro-hardness have been found within the calculated limits. Finally, it can be concluded that ageing time has significant effect on hardness and particle size of the reinforcement has least effect on hardness of the developed composite under study.

Authors are very much thankful to the Science and Engineering Research Board, New Delhi (India) for funding this research project through Fast Track Young Scientist Engineering Science Scheme vide their letter No. SB/FTP/ETA-148/2013, Dated: 31/10/2013.