用GAAA优化多阶段装配过程中的夹具布局

中国机械工程 ›› 2015, Vol. 26 ›› Issue (5): 658-663.

用GAAA优化多阶段装配过程中的夹具布局

谢伟松1;邓铮1;丁伯慧2

1.天津大学，天津，300072
2.天津大学机构理论与装备设计教育部重点实验室，天津，300072

出版日期:2015-03-10 发布日期:2015-03-06
基金资助:
国家自然科学基金资助项目（51205286, 51275348）

Fixture Layout Optimization in Multi-station Assembly Processes Using GAAA

Xie Weisong1;Deng Zheng1;Ding Bohui2

1.Tianjin University,Tianjin,300072
2.Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education,Tianjin University,Tianjin,300072

Online:2015-03-10 Published:2015-03-06
Supported by:
National Natural Science Foundation of China（No. 51205286, 51275348）

摘要/Abstract

摘要：

改进了遗传算法与蚁群算法的融合（GAAA）算法，利用它来解决多阶段装配过程中二维刚性零件的夹具布局优化问题，合理选择定位销的位置使得灵敏度指标最小化。通过改变遗传算法的变异算子，变异长度以及交叉、变异在蚁群算法中发生的位置，提高了GAAA的稳定性和收敛性。以汽车侧边装配为例验证了改进算法的有效性，结果表明改进后的GAAA比基本的GAAA和蚁群算法求得的结果要好，且收敛速度更快，稳定性更好。

关键词: 多阶段装配过程, 状态空间模型, 夹具布局优化, 遗传算法与蚁群算法的融合

Abstract:

GAAA (genetic algorithm-ant colony algorithm) was augmented to solve fixture layout optimization problems of 2D rigid parts in multi-station assembly processes, and the coordinates of two locating pins were properly selected to minimize the sensitivity index. The stability and convergence of GAAA were improved by changing the mutation operator, mutation length of genetic algorithm and the position where crossover and mutation occured in ant colony algorithm. A case about automotive side aperture assembly processes was studied to verify the effectiveness of the augmented GAAA. The results show that the augmented GAAA can generate more accurate results with a faster rate of convergence and a better stability than the basic GAAA and ant colony algorithm.

Key words: multi-station assembly process, state space model, fixture layout optimization, genetic algorithm-ant colony algorithm(GAAA)

中图分类号:

TH122
TH16

谢伟松, 邓铮, 丁伯慧 . 用GAAA优化多阶段装配过程中的夹具布局[J]. 中国机械工程, 2015, 26(5): 658-663.

Xie Weisong, Deng Zheng, Ding Bohui. Fixture Layout Optimization in Multi-station Assembly Processes Using GAAA[J]. China Mechanical Engineering, 2015, 26(5): 658-663.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: http://www.cmemo.org.cn/CN/

http://www.cmemo.org.cn/CN/Y2015/V26/I5/658

参考文献

[1]Kim P, Ding Y. Optimal Design of Fixture Layout in Multistation Assembly Processes[J]. IEEE Transactions on Automation Science and Engineering, 2004, 1(2): 133-145.
[2]Izquierdo L E, Hu S J, Jin R, et al. Robust Fixture Layout Design for a Product Family Assembled in a Multistage Reconfigurable Line[J]. Journal of Manufacturing Science and Engineering, 2009, 131(4): 041008.
[3]Huang W, Kong Z, Chennamaraju A. Robust Design for Fixture Layout in Multistation Assembly Systems Using Sequential Space Filling Methods[J]. Journal of computing and information science in engineering, 2010, 10(4): 041001.
[4]Selvakumar S, Arulshri K P, Padmanaban K P, et al. Design and Optimization of Machining Fixture Layout Using ANN and DOE[J]. The International Journal of Advanced Manufacturing Technology, 2013, 65(9/12): 1573-1586.
[5]Wang B F, Nee A Y C. Robust Fixture Layout with the Multi-objective Non-dominated ACO/GA Approach[J]. CIRP Annals-Manufacturing Technology, 2011, 60(1): 183-186.
[6]陈蔚芳, 倪丽君, 王宁生. 夹具布局和夹紧力的优化方法研究[J]. 中国机械工程, 2007, 18(12): 1413-1417.
Chen Weifang, Ni Lijun, Wang Ningsheng. Investigation on Optimization Method for Fixture Layout and Clamping Forces[J]. China Mechanical Engineering. 2007, 18(12): 1413-1417.

[7]Padmanaban K P, Prabhaharan G. Dynamic Analysis on Optimal Placement of Fixturing Elements Using Evolutionary Techniques[J]. International Journal of Production Research, 2008, 46(15): 4177-4214.
[8]Padmanaban K P, Arulshri K P, Prabhakaran G. Machining Fixture Layout Design Using Ant Colony Algorithm Based Continuous Optimization Method[J]. The International Journal of Advanced Manufacturing Technology, 2009, 45(9/10): 922-934.
[9]Ding Y, Shi J, Ceglarek D. Diagnosability Analysis of Multi-station Manufacturing Processes[J]. Journal of Dynamic Systems, Measurement, and Control, 2002, 124(1): 1-13.
[10]Wang H, Ceglarek D. Variation Propagation Modeling and Analysis at Preliminary Design Phase of Multi-station Assembly Systems[J]. Assembly Automation, 2009, 29(2): 154-166.
[11]Shi J. Stream of Variation Modeling and Analysis for Multistage Manufacturing Processes[M]. Boca Raton:CRC Press, 2010.
[12]Liu J, Jin J, Shi J. State Space Modeling for 3-D Variation Propagation in Rigid-body Multistage Assembly Processes[J]. IEEE Transactions on Automation Science and Engineering, 2010, 7(2): 274-290.
[13]Abellan-Nebot J V, Liu J, Subirón F R, et al. State Space Modeling of Variation Propagation in Multistation Machining Processes Considering Machining-induced Variations[J]. Journal of Manufacturing Science and Engineering, 2012, 134(2): 021002.
[14]丁建立, 陈增强, 袁著祉. 遗传算法与蚂蚁算法的融合[J]. 计算机研究与发展, 2003, 40(9): 1351-1356.
Ding Jianli, Chen Zengqiang, Yuan Zhuzhi. On the Combination of Genetic Algorithm and Ant Algorithm[J]. Journal of Computer Research and Development, 2003, 40(9): 1351-1356.
[15]Ciornei I, Kyriakides E. Hybrid Ant Colony-genetic Algorithm (GAAPI) for Global Continuous Optimization[J]. Systems, Man, and Cybernetics, Part B: IEEE Transactions on Cybernetics, 2012, 42(1): 234-245.