Cutting parameters optimisation in milling: expert machinist knowledge versus soft computing method

Abstract

In traditional machining operations, cutting parameters are usually selected prior to machining according to machining handbooks and user’s experience. However, this method tends to be conservative and sub-optimal since part accuracy and non machining failures prevail over machining process efficiency. In this paper, a comparison between traditional cutting parameter optimisation by an expert machinist and an experimental optimisation procedure based on Soft Computing methods is conducted. The proposed methodology increases the machining performance in 6.1% and improves the understanding of the machining operation through the use of Adaptive Neuro-fuzzy Inference Systems