Abstract

The effect of lubrication-cooling condition on surface roughness in finish face milling operations has been widely investigated. Different cutting speeds and lubrication cooling conditions (dry, wet and MQL), in finish face milling of AISI 420 B stainless steel, have been considered. The evolution of the surface finish and tool wear with cutting time have been monitored. Analytical and artificial neural networkmodels, able to predict the surface roughness under different machining conditions, have been proposed.

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