• Sadhana Mishra
• Neha Gupta

Surface Roughness (Ra) during the process has been considered as productivity estimate with the aim to minimize it. With an intention of minimizing surface roughness is been taken as most important output parameter. This can be satisfied by selecting an optimal process environment (optimal parameter setting). Objective function is obtained by Neural Network tool of MATLAB. Then objective function is optimized using Genetic Algorithm optimization tool of MATLAB. The model is shown to be effective Surface Roughness improved using optimized machining parameters.

EDM, WEDM, Surface Roughness, Work piece.

"Advanced Genetic Algorithm and ANN Based Surface Roughness Estimation", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.513-517, June-2019, Available :http://www.jetir.org/papers/JETIR1906C83.pdf

"Advanced Genetic Algorithm and ANN Based Surface Roughness Estimation", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp513-517, June-2019, Available at : http://www.jetir.org/papers/JETIR1906C83.pdf