JOURNAL ARTICLE

Machining fixture layout optimisation using genetic algorithm and artificial neural network

S. SelvakumarK. P. ArulshriK.P. Padmanaban

Year: 2013 Journal:   International Journal of Manufacturing Research Vol: 8 (2)Pages: 171-171   Publisher: Inderscience Publishers

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.

Keywords:
Fixture Clamping Genetic algorithm Machining Artificial neural network Deformation (meteorology) Engineering Page layout Computer science Algorithm Engineering drawing Structural engineering Mechanical engineering Artificial intelligence Materials science Machine learning Composite material

Metrics

23
Cited By
4.66
FWCI (Field Weighted Citation Impact)
29
Refs
0.94
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Manufacturing Process and Optimization
Physical Sciences →  Engineering →  Industrial and Manufacturing Engineering
Advanced Numerical Analysis Techniques
Physical Sciences →  Engineering →  Computational Mechanics
Advanced Measurement and Metrology Techniques
Physical Sciences →  Engineering →  Mechanical Engineering

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