Abstract
In the present study, a subtractive clustering fuzzy identification method and a Sugeno-type fuzzy inference system are used. The influence of some parameters on the thrust force and torque in the drilling processes of self-lubricated aluminium/alumina/graphite composites was investigated. The models were identified by using cutting speed, feed and volume fraction of the reinforced particles as input data, and the thrust cutting force and cutting torque as the output data. The building of the model was carried out by using subtractive clustering in both the input and output spaces. The obtained models were capable of predicting the thrust cutting force and cutting torque for a given set of inputs (cutting speed, feed, and volume fractions of the reinforcement). These models were verified experimentally using different sets of inputs. The results showed that the studied composite could be considered as a possible substitute to other metallic materials used in transport industries.
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