Modares Mechanical Engineering

Modares Mechanical Engineering

Fixture's clamp layout optimization for sheet metal with initial variation based on ant colony algorithm

Authors
Milad Khodabandeh 1
Maryam Ghassabzadeh Saryazdi 2
Abdolreza Ohadi 1
1 Department of Mechanical Engineering, Amirkabir University of Technology, Tehran, Iran
2 Vehicle Research Technology Institute, Amirkabir University of Technology
Abstract
The fixtures play a significant role in harnessing the metal sheets in the assembly stage. The high flexibility of the metal sheets and the initial deviation in the pressed sheets cause deviation in the final product. Using the optimal layout of the clamping points in the fixture can reduce the deviation effectively and raising the final product quality. On the other hand, the cost of construction is intensively influence by the number of clamps, rising the number of clamps causes the cost of construction to increase and reducing it cause the deviation in the final product to increase. Therefore, the number of clamps should be considered in the optimal design of the fixture. It is challenging to achieve optimal design for fixture due to the difficulty in predicting sheet behavior and computational constraints. In this paper the relationship between the initial deviation of sheet and the deviation of final product is investigated and a method is proposed by using ant colony algorithm and finite element method for optimizing the position of the clamping points to reducing the deviation of the product after assembly with considering the minimizing the number of clamping points. Finally the proposed method is applied to a simple square sheet with initial deviation and based on the cost function, the number of clamping points and their position are optimized. The results show that reducing the amount of sheet deviation in the fixture causes reduce the deviation of final product.
Keywords
Fixture layout
Optimization
Ant colony algorithm
sheet metal
Deviation
[1] W. Cai, S. J. Hu, J. Yuan, Deformable sheet metal fixturing: principles, algorithms, and simulations, Journal of Manufacturing Science and Engineering, Vol. 118, No. 3, pp. 318-324, 1996.
[2] Y. Xing, Y. Wang, Fixture layout design based on two-stage method for sheet metal components, Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, Vol. 227, No. 1, pp. 162-172, 2013.
[3] Z. Ahmad, M. Zoppi, R. Molfino, Fixture layout optimization for large metal sheets using genetic algorithm, International Journal of Mechanical and Mechatronics Engineering, Vol. 7, No. 7, pp. 1487-1492, 2013.
[4] Z. Wang, B. Yang, Y. Kang, Y. Yang, Development of a prediction model based on RBF neural network for sheet metal fixture locating layout design and optimization, Computational Intelligence and Neuroscience, Vol. 2016, No. 127, pp1-6, 2016.
[5] Z. Wang, Y. Yang, B. Yang, Y. Kang, Optimal sheet metal fixture locating layout by combining radial basis function neural network and bat algorithm, Advances in Mechanical Engineering, Vol. 8, No. 12, pp. 1-10, 2016.
[6] B. Yang, Z. Wang, Y. Yang, Y. Kang, X. Li, Optimum fixture locating layout for sheet metal part by integrating kriging with cuckoo search algorithm, The International Journal of Advanced Manufacturing Technology, Vol. 91, No. 1-4, pp. 327-340, 2017.
[7] B. Yang, Z. Wang, Y. Yang, Y. Kang, C. Li, Optimization of fixture locating layout for sheet metal part by cuckoo search algorithm combined with finite element analysis, Advances in Mechanical Engineering, Vol. 9, No. 6, pp. 1- 10, 2017.
[8] Y. G. Liao, A genetic algorithm-based fixture locating positions and clamping schemes optimization, Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, Vol. 217, No. 8, pp. 1075-1083, 2003.
[9] J. A. Camelio, S. J. Hu, D. Ceglarek, Impact of fixture design on sheet metal assembly variation, Journal of Manufacturing Systems, Vol. 23, No. 3, pp. 182-193, 2004.
[10] W. Cai, Fixture optimization for sheet panel assembly considering welding gun variations, Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, Vol. 222, No. 2, pp. 235-246, 2008.
[11] X. Liao, G. G. Wang, Simultaneous optimization of fixture and joint positions for non-rigid sheet metal assembly, The International Journal of Advanced Manufacturing Technology, Vol. 36, No. 3-4, pp. 386-394, 2008.
[12] K. H. Hajikolaei, G. G. Wang, Optimization of fixture and joint positions in sheet metal assembly: the effect of fixture numbers and constraints, Proceeding of American Society of Mechanical Engineers, Washington, DC, Usa, August 28–31 , pp. 743-750, 2011.
[13] W. Xie, Z. Deng, B. Ding, H. Kuang, Fixture layout optimization in multistation assembly processes using augmented ant colony algorithm, Journal of Manufacturing Systems, Vol. 37, pp. 277-289, 2015.
[14] Y. Xing, M. Hu, H. Zeng, Y. Wang, Fixture layout optimisation based on a non-domination sorting social radiation algorithm for auto-body parts, International Journal of Production Research, Vol. 53, No. 11, pp. 3475- 3490, 2015.
[15] M. Dorigo, V. Maniezzo, A. Colorni, Ant system: Optimization by a colony of cooperating agents, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), Vol. 26, No. 1, pp. 29-41, 1996.
Modares Mechanical Engineering
Volume 18, Issue 3
May 2018
Pages 380-388