Title: Modelling the machinability of self-lubricated aluminium/alumina/graphite hybrid composites using a fuzzy subtractive clustering-based system identification method
Authors: Mohammed T. Hayajneh, Adel Mahmood Hassan
Addresses: Industrial Engineering Department, Faculty of Engineering, Jordan University of Science and Technology, P.O. Box 3030, Irbid, 22110, Jordan. ' Industrial Engineering Department, Faculty of Engineering, Jordan University of Science and Technology, P.O. Box 3030, Irbid, 22110, Jordan
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.
Keywords: fuzzy logic; fuzzy subtractive clustering; modelling; machinability; drilling; self-lubricated MMCs; metal matrix composites; aluminium matrix composites; alumina; graphite; cutting torque; drilling; cutting force.
International Journal of Machining and Machinability of Materials, 2008 Vol.3 No.3/4, pp.252 - 271
Published online: 29 Oct 2008 *Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article