Optimization and predictive modeling using S/N, RSM, RA and ANNs for micro-electrical discharge drilling of AISI 304 stainless steel

@article{Sarikaya2016OptimizationAP,
  title={Optimization and predictive modeling using S/N, RSM, RA and ANNs for micro-electrical discharge drilling of AISI 304 stainless steel},
  author={Murat Sarikaya and Volkan Yilmaz},
  journal={Neural Computing and Applications},
  year={2016},
  volume={30},
  pages={1503-1517}
}
In present work, micro-deep holes on AISI 304 stainless steel were drilled via electrical discharge machining (EDM) method. In the first phase of this work, the effect of test parameters on the drilling performance and the profile of drilled holes were investigated experimentally. Test parameters including discharge current, dielectric spray pressure and electrode tool rotational speed were taken and then the machining rate (MR), electrode wear rate (EWR), average over-cut (AOC) and taper angle… CONTINUE READING

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