Research Article
Optimization of Processing Parameters in ECM of Die Tool Steel Using Nanofluid by Multiobjective Genetic Algorithm
Table 3
Process decision variables along with optimized response from GA for aqueous NaNO3.
| Sl. number | Voltage (V) | Feed rate (mm/min) | Discharge rate (lit/min) | MRR (mm3/min) | Surface roughness (micron) |
| 1 | 12 | 0.1100281 | 8.134412 | 132.46309 | 1.513575 | 2 | 12.030211 | 0.1104329 | 9.087866 | 152.49089 | 1.777581 | 3 | 12.014045 | 0.1039534 | 10.04123 | 169.34532 | 2.152654 | 4 | 17.995146 | 0.5265484 | 11.98002 | 302.51291 | 2.656720 | 5 | 12.000245 | 0.1005786 | 9.147932 | 153.98288 | 1.791250 | 6 | 17.991590 | 0.3675932 | 11.97936 | 260.68191 | 2.254694 | 7 | 12.006746 | 0.2003393 | 8.234414 | 137.00311 | 1.560310 | 8 | 12.008757 | 0.1019808 | 10.06793 | 169.87964 | 2.159093 | 9 | 17.989152 | 0.3175749 | 11.99351 | 250.47074 | 2.189059 | 10 | 12.000737 | 0.1004096 | 9.719882 | 164.05383 | 2.038806 | 11 | 12.009474 | 0.2017167 | 8.488291 | 141.77756 | 1.587574 | 12 | 17.994398 | 0.5169848 | 11.97913 | 299.58104 | 2.623729 | 13 | 17.985153 | 0.2530979 | 11.99503 | 239.31519 | 2.164326 | 14 | 17.988464 | 0.3482414 | 11.99409 | 256.55458 | 2.219778 | 15 | 12.012065 | 0.1043002 | 8.710513 | 145.82497 | 1.564311 | 16 | 17.990082 | 0.4115904 | 11.98257 | 270.80421 | 2.330752 | 17 | 17.986068 | 0.3813624 | 11.99307 | 263.68107 | 2.268322 | 18 | 12.004311 | 0.1041213 | 8.848672 | 148.38304 | 1.639634 | 19 | 12.000057 | 0.2000266 | 8.109496 | 134.59464 | 1.771653 | 20 | 12.015943 | 0.1038107 | 8.938570 | 150.04776 | 1.691262 | 21 | 17.988003 | 0.4437773 | 11.99324 | 278.90557 | 2.397192 | 22 | 12.001201 | 0.1004778 | 8.995683 | 151.23304 | 1.714381 | 23 | 12 | 0.2 | 8.874121 | 132.46309 | 1.693575 | 24 | 17.995820 | 0.5399502 | 11.97976 | 306.69449 | 2.706127 | 25 | 12.007139 | 0.1076954 | 8.422892 | 140.26985 | 1.592297 | 26 | 17.985182 | 0.2532877 | 11.99497 | 239.34474 | 2.164350 | 27 | 12.013497 | 0.1039507 | 9.351800 | 157.47043 | 1.892639 |
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