Research Article
Optimization of Processing Parameters in ECM of Die Tool Steel Using Nanofluid by Multiobjective Genetic Algorithm
Table 4
Process decision variables along with optimized response from GA for Cu nanoparticles suspended in aqueous NaNO3 electrolyte.
| Sl. number | Voltage (V) | Feed rate (mm/min) | Discharge rate (lit/min) | MRR (mm3/min) | Surface roughness (micron) |
| 1 | 17.688986 | 0.5399705 | 11.998816 | 375.78277 | 2.339779 | 2 | 17.999473 | 0.2344207 | 11.997052 | 291.21779 | 1.4973965 | 3 | 17.982536 | 0.3619794 | 11.990806 | 324.01735 | 1.6773238 | 4 | 17.812326 | 0.5399910 | 11.998295 | 375.72198 | 2.3501116 | 5 | 17.974140 | 0.4719105 | 11.991869 | 354.97140 | 2.0744706 | 6 | 17.986820 | 0.3385383 | 11.997917 | 317.93316 | 1.6169858 | 7 | 17.995289 | 0.2727332 | 11.99707 | 300.7935 | 1.5171501 | 8 | 17.981729 | 0.4545162 | 11.997314 | 350.07699 | 1.9885303 | 9 | 17.970973 | 0.5100869 | 11.997924 | 366.45561 | 2.2630915 | 10 | 17.991024 | 0.3212817 | 11.997223 | 313.33371 | 1.5817197 | 11 | 17.957900 | 0.5030484 | 11.997998 | 364.38746 | 2.2357070 | 12 | 17.955889 | 0.4263774 | 11.997138 | 342.11877 | 1.8942504 | 13 | 17.896183 | 0.5389892 | 11.998794 | 375.34015 | 2.3713213 | 14 | 17.917751 | 0.5150918 | 11.998277 | 368.07683 | 2.3296118 | 15 | 17.960839 | 0.4768214 | 11.996795 | 356.60081 | 2.1042235 | 16 | 17.913224 | 0.5219700 | 11.998223 | 370.14799 | 2.3709887 | 17 | 17.963386 | 0.4965703 | 11.997834 | 362.44458 | 2.1984027 | 18 | 17.997099 | 0.2431022 | 11.997066 | 293.37153 | 1.5003086 | 19 | 17.991022 | 0.3212817 | 11.997223 | 313.33371 | 1.5817197 |
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