Abstract
The surface quality of wire electric discharge machining is determined by formation of recast layer and its roughness profile. These characteristics has a great relationship with the process parameters. To attain an intense knowledge of the surface roughness and recast layers of a surface machined by WEDM on stainless steel 316, the inputs and outputs correlation has been constructed using artificial neural network model. Particle swarm optimization algorithm is used to extract the optimal set of process parameters for multi responses. Thick white layers (13–16 µm) and rough surface (3.5-4 µm) was found at high pulse on time while very thine white layer (3-5 µm) and finish surface (1.5-2 µm) can be observed at low pulse on time.
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