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 (mm^3/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