Title: Optimisation of surface roughness in hard turning AISI D2 steel using TSK-type fuzzy logic rules
Authors: Arup Kumar Nandi, J. Paulo Davim
Addresses: Central Mechanical Engineering Research Institute, Durgapur-713209, West Bengal, India. ' Department of Mechanical Engineering, University of Aveiro, Campus Santiago, 3810-193 Aveiro, Portugal
Abstract: In the present work, an intelligent method is adopted to optimise the machining parameters to obtain a desired surface roughness on AISI D2 steel in Hard turning operations. In order to perform the turning operation a ceramic insert tool is used. The task of this optimisation is carried out by two stages: in the first stage, a rule-based model is constructed based on experimental (training) data, and later, a genetic algorithm (GA) is used to optimise the critical machining parameters based on this model as predictor. Developing a suitable model for a machining process is a difficult and primary task for optimisation of machining process. Due to non-linearity of the cutting parameters, tool-work combination and rigidity of machine tool, it has been shown that mathematical or analytical approaches failed to develop models for manufacturing processes.
Keywords: rule-based modelling; hard turning; AISI D2 steel; optimisation; surface roughness; linear regression; GAs; genetic algorithms; fuzzy logic; machining parameters; ceramic inserts.
International Journal of Materials and Product Technology, 2009 Vol.35 No.1/2, pp.167 - 183
Published online: 16 May 2009 *Full-text access for editors Access for subscribers Purchase this article Comment on this article