Fuzzy cutting force modelling in micro-milling using subtractive clustering for learning evaluation

Cutting forces prediction is very important for cutting tool’s design and process planning. This paper presents a fuzzy cutting force modelling method using subtractive clustering for learning evaluation. In this method, subtractive clustering, combined with the least-square algorithm, identifies the fuzzy prediction model directly from the information obtained from the sensors. In the micro-milling experimental case study, two fuzzy models learned through different evaluation strategies are tested. The modelling results are compared and discussed.