Prediction of Machining Responses in Wire EDM on Stainless Steel-316
In wire electrical discharge machining (WEDM), material is removed by means of the rapid and cyclic spark that discharges across the gap between the tool and workpiece. In the present work, process parameters of WEDM are tried to be optimize the response variable on Stainless Steel-316 alloy material. SS-316 combinations have been broadly utilized for their predominant properties. For example, high quality, high electrical and thermal conductivities, and low cost. The input parameters considered are pulse-on time, pulse-off time, and current to optimize the responses, viz. surface roughness (SR), volumetric material removal rate (VMRR), dimensional error (DE), and electrode wear (EW). Taguchi’s L27 orthogonal array was chosen to conduct the experiments according to design of experiments (DOE). SR is measured using surftron surface tester and VMRR is calculated based on machining time. DE and EW are measured by micrometer. By using artificial neural network, results were predicted and compared with the experimental results.
KeywordsWire EDM Stainless steel-316 Artificial neural network (ANN)
The work reported in this paper is supported by B.M.S. College of Engineering, through the Technical Education Quality Improvement Programme [TEQIP-III] of the MHRD, Government of India.
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