Abstract
In the present paper an attempt is made to establish a response surface methodology based non-linear mathematical model for the friction–wear behaviour of as cast and heat-treated Al6061/9%Gr/WC (with WC at 1, 2 and 3 wt%) metal matrix composites (MMCs). During experimentation, the process parameters, namely percentage of WC, load, sliding distance and sliding velocity have been considered as inputs and wear loss (WL) and coefficient of friction (COF) have been treated as the responses. Results reveal that, for as-cast Al6061/9%Gr/WC hybrid composites, the WL decreases with increase in percentage of WC and increases with the increase in load, sliding distance and sliding velocity. Moreover, COF decreases with increase in percentage of WC and sliding velocity and increases with increase in the load and sliding distance. It has also been observed that the WL and COF of heat treated composites are found to be less than the as cast MMCs. Further, fuzzy grey relational analysis (GRA) has been used to perform the multi objective optimization of the said wear process. Finally, the evidence of wear phenomenon for the said composites have been examined with the help of scanning electron microscopy.
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Appendix
Appendix
Experiment no. | %Tungsten carbide (WC) | Load (N) | Sliding distance (m) | Sliding velocity (m/s) | As casted | |
|---|---|---|---|---|---|---|
Wear loss | COF | |||||
1 | 1 | 10 | 500 | 1 | 0.036 | 0.410 |
2 | 3 | 10 | 500 | 1 | 0.005 | 0.443 |
3 | 1 | 30 | 500 | 1 | 0.083 | 0.399 |
4 | 3 | 30 | 500 | 1 | 0.051 | 0.485 |
5 | 1 | 10 | 2500 | 1 | 0.084 | 0.420 |
6 | 3 | 10 | 2500 | 1 | 0.056 | 0.413 |
7 | 1 | 30 | 2500 | 1 | 0.125 | 0.329 |
8 | 3 | 30 | 2500 | 1 | 0.095 | 0.363 |
9 | 1 | 10 | 500 | 3 | 0.086 | 0.353 |
10 | 3 | 10 | 500 | 3 | 0.055 | 0.330 |
11 | 1 | 30 | 500 | 3 | 0.132 | 0.287 |
12 | 3 | 30 | 500 | 3 | 0.097 | 0.300 |
13 | 1 | 10 | 2500 | 3 | 0.133 | 0.510 |
14 | 3 | 10 | 2500 | 3 | 0.105 | 0.503 |
15 | 1 | 30 | 2500 | 3 | 0.185 | 0.354 |
16 | 3 | 30 | 2500 | 3 | 0.164 | 0.362 |
17 | 2 | 20 | 1500 | 2 | 0.090 | 0.404 |
18 | 2 | 20 | 1500 | 2 | 0.070 | 0.410 |
19 | 2 | 20 | 1500 | 2 | 0.075 | 0.390 |
20 | 2 | 20 | 1500 | 2 | 0.085 | 0.380 |
21 | 1 | 20 | 1500 | 2 | 0.090 | 0.378 |
22 | 3 | 20 | 1500 | 2 | 0.068 | 0.421 |
23 | 2 | 10 | 1500 | 2 | 0.051 | 0.418 |
24 | 2 | 30 | 1500 | 2 | 0.110 | 0.389 |
25 | 2 | 20 | 500 | 2 | 0.049 | 0.433 |
26 | 2 | 20 | 2500 | 2 | 0.090 | 0.441 |
27 | 2 | 20 | 1500 | 1 | 0.351 | 0.420 |
28 | 2 | 20 | 1500 | 3 | 0.399 | 0.385 |
29 | 2 | 20 | 1500 | 2 | 0.143 | 0.393 |
30 | 2 | 20 | 1500 | 2 | 0.151 | 0.390 |
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Ponugoti, G., Alluru, G.K. & Vundavilli, P.R. Response Surface Methodology Based Modelling of Friction–Wear Behaviour of Al6061/9%Gr/WC MMCs and Its Optimization Using Fuzzy GRA. Trans Indian Inst Met 71, 2465–2478 (2018). https://doi.org/10.1007/s12666-018-1377-x
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DOI: https://doi.org/10.1007/s12666-018-1377-x