Modeling and Optimization of Roll-bonding Parameters for Bond Strength of Ti/Cu/Ti Clad Composites by Artificial Neural Networks and Genetic Algorithm

Authors

1 Department of Materials Science and Engineering, Shahid Bahonar University of Kerman, Kerman, Iran

2 Department of Mechanical Engineering, Faculty of Engineering, University of Hormozgan, Bandar Abbas, Iran

3 Department of Materials Science and Engineering, School of Engineering, Shiraz University, Shiraz, Iran

Abstract

This paper deals with modeling and optimization of the roll-bonding process of Ti/Cu/Ti composite for determination of the best roll-bonding parameters leading to the maximum Ti/Cu bond strength by combination of neural network and genetic algorithm. An artificial neural network (ANN) program has been proposed to determine the effect of practical parameters, i.e., rolling temperature, reduction in thickness, post-annealing time, post-annealing temperature and rolling speed on the bond strength of Ti/Cu composite. The most suitable model with correlation coefficient (R2) of 0.98 and mean absolute error (MAPE) 3.5 was determined using genetic algorithm (GA) and the optimum practice condition are proposed. Moreover, the sensitivity analysis results showed the post-annealing temperature with the negative effects is the most influential parameter on the strength of bonding.

Keywords

References

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International Journal of Engineering
Volume 30, Issue 12
TRANSACTIONS C: Aspects
December 2017
Pages 1885-1893

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