Title: Modelling of tool life and surface roughness in hard turning using soft computing techniques: a comparative study
Authors: D. Cica; B. Sredanovic; D. Kramar
Addresses: Faculty of Mechanical Engineering, University of Banja Luka, Vojvode Stepe Stepanovica 71, Banja Luka 78000, Bosnia and Herzegovina ' Faculty of Mechanical Engineering, University of Banja Luka, Vojvode Stepe Stepanovica 71, Banja Luka 78000, Bosnia and Herzegovina ' Faculty of Mechanical Engineering, University of Ljubljana, Ljubljana 1000, Slovenia
Abstract: In this paper the potential of soft computing techniques for tool wear and surface roughness prediction in hard turning operations under high pressure cooling conditions using coated carbide tools was investigated. An experimental investigation was conducted to analyse the effects of various cutting conditions on these two parameters analysed in the hard turning of the 100Cr6 steel (62 HRC). On the basis of experimental results two different methods, namely, artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are developed for tool wear and surface roughness prediction. The estimation results obtained by both models are compared with experimental results and very good agreement is observed.
Keywords: soft computing; tool wear; surface roughness; hard turning; modelling; tool life; surface quality; high pressure cooling; coated carbide tools; artificial neural networks; ANNs; adaptive neuro-fuzzy inference system; ANFIS; neural networks; fuzzy logic.
International Journal of Materials and Product Technology, 2015 Vol.50 No.1, pp.49 - 64
Available online: 11 Jan 2015 *Full-text access for editors Access for subscribers Purchase this article Comment on this article