Fuzzy cutting force modelling in micro-milling

Authors:
Qun Ren;Luc Baron;Marek Balazinskia;Krzysztof Jemielniak
Affiliations:
Mechanical Engineering Department, École Polytechnique de Montréal, Montréal, QC, Canada;Mechanical Engineering Department, École Polytechnique de Montréal, Montréal, QC, Canada;Mechanical Engineering Department, École Polytechnique de Montréal, Montréal, QC, Canada;Faculty of Production Engineering, Warsaw University of Technology, Warsaw, Poland
Venue:
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Year:
2013

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Abstract

Reliable prediction of cutting forces is essential for micromilling. In this paper, a fuzzy cutting force modelling method based on subtractive clustering method filters the noise and estimates the instantaneous cutting forces using observations acquired by sensors during cutting experiments. In the experimental case study, four data sets of micromilling cutting force are used. Each data set is used to generate a learning system which is tested by the other three data sets. It is proven that the proposed algorithm has the capability to filter and model the cutting force in spite of uncertainties in the micromilling process.