A Method of Optimal Module Partition in Green Product Configuration Design under Uncertainty

Article Preview

Abstract:

The principle and main steps of module partition in green product configuration design under uncertainty, and how to determine the correlation between the basic elements of a product, and how to calculate the green degree of module are discussed in this paper. Let the maximum degree of cluster inner a module and the minimum coupling degree among modules and the maximum green degree of modules as the objective function, the mathematic model of uncertainly optimizing for green module partition is set up. And then It is transformed to an ascertainable combinatorial optimization model by de-fuzzy operator, and it is solved by GA (Genetic Algorithm,). The methods of chromosome encoding and the methods of selection and crossover and mutation operator are presented in this paper. A computational example is studied; its result verifies the effectiveness and practical value of the method proposed in this paper.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

438-445

Citation:

Online since:

December 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Liu Guang-fu, Liu Xue-ping, Liu Zhi-feng. Structure of green design and implementation strategy[J]. China Mechanical Engineering, 2000, 11(9): 965-968.

Google Scholar

[2] Liu Fei, Cao Hua-jun, He Nai-jun. Research status and development trend of green manufacturing[J]. China Mechanical Engineering, 2000, 11(1-2): 105-110.

Google Scholar

[3] Li Fang-yi, Wang Jing-song, Li Jian-feng. Present situation and prospect of research on green design of products[J]. Aeronautical Manufacturing Technology, 2004, 29(10): 73-78.

Google Scholar

[4] Lu Chang-ming, Chen Feng, Deng Jing-lian. Effect of green product design of the module[J]. Machine design and research, 2006, 22(6): 13-16.

Google Scholar

[5] LiTing-ting, Gong Jing-zhong, Li Guo-xi. Maintenance module driven[J]. Manufacturing and research of machinery. 2007, 45(02): 166-168.

Google Scholar

[6] Tseng H E, Chang C C, Li J D. Modular design to support green life-cycle engineering[J]. Expert Systems with Applications, 2008, 34(4): 2524-2537.

DOI: 10.1016/j.eswa.2007.04.018

Google Scholar

[7] Guo Wei , Liu Guang-fu, Zhang-Lei. Research on green product module partition method oriented to the whole life cycle[J]. Journale of HeFei University of Technology( Natural Science Edition) 2010, 33(10): 1441-1445, 1449.

Google Scholar

[8] Smith S, Yen C C. Green product design through product modularization using atomic theory [J]. Robotics and Computer Integrated Manufacturing, 2010, 26(6): 790-798.

DOI: 10.1016/j.rcim.2010.05.006

Google Scholar

[9] Chen Xiao-bing. Research and application of green module partition method of electromechanical products[D]. Zhejiang University, (2012).

Google Scholar

[10] Ji Y J, Jiao R J, Chen L, Wu C L. Green modular design for material efficiency: a leader–follower joint optimization model[J]. Journal of Cleaner Production, 2013, 41(2): 187-201.

DOI: 10.1016/j.jclepro.2012.09.022

Google Scholar

[11] Tang Wen-yan, Wu Chun-yan, Ma Bao. Research aim. module partition method based on fuzzy clustering analysis[J]. Mechanical layout, 2012, 29(10): 24-28.

Google Scholar

[12] Tang T-ao, Liu Zhi-feng, Liu Guang-fu. green module paitition design method research. Chinese Journale of Mechanical Engineering, 2003, 39(11): 149-154.

Google Scholar

[13] Zhang Shi-fang, San Yang, Qin Chuan-dong. Dynamical fuzzy multiple attribute decision making of the WIKOR expansion method[J]. 2012, 18(1): 186-191.

Google Scholar

[14] Wang Xiao-ping, Cao Li-ming. the theory of Genetic Algorithm [M]. Xi'an Jiao Tong University Press . 2002. 1: 28, 38.

Google Scholar

[15] Liu Dian-ting, Zhou De-jian. Uncertain moduleing of production planning under the condition of SMT products and GA solution[J]. Journal of Guilin University of technology, 20118, 31(2): 278-285.

Google Scholar