Title: Machining fixture layout optimisation using genetic algorithm and artificial neural network

Authors: S. Selvakumar; K.P. Arulshri; K.P. Padmanaban

Addresses: Department of Mechanical Engineering, Kongu Engineering College, Erode, Tamilnadu, 638 052, India ' KPR Institute of Engineering and Technology, Coimbatore, Tamilnadu, 641 407, India ' SBM College of Engineering and Technology, Dindigul, Tamilnadu, 624 005, India

Abstract: The purpose of this research work is to design an optimum fixture layout in order to reduce the maximum elastic deformation of the workpiece caused by the clamping and machining forces acting on the workpiece while machining. First a genetic algorithm (GA) based optimisation procedure to solve the fixture layout optimisation problem is briefly explained, and then combined GA and artificial neural network (ANN) based optimisation procedure for fixture layout design is explained. In the combined GA and ANN approach, the resulting fixture layouts generated by GA are given as input to ANN and the maximum workpiece deformation for each fixture layout is found out by using ANN. The optimal fixture layout is the one which shows the minimum deformation among others. The results that are obtained by using GA and the combination of GA and ANN are compared. [Received 4 July 2011; Revised 7 March 2012; Accepted 25 June 2012]

Keywords: fixture layout; genetic algorithms; GAs; artificial neural networks; ANNs; finite element method; FEM; harmonic analysis; machining fixtures; optimisation; elastic deformation; workpiece deformation.

DOI: 10.1504/IJMR.2013.053286

International Journal of Manufacturing Research, 2013 Vol.8 No.2, pp.171 - 195

Published online: 29 Jan 2014 *

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