Full Text:   <2500>

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CLC number: TB491

On-line Access: 2015-09-03

Received: 2015-05-29

Revision Accepted: 2015-08-21

Crosschecked: 2015-08-25

Cited: 3

Clicked: 4771

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Yi-xiong Feng

http://orcid.org/0000-0001-7397-2482

Zhi-feng Zhang

http://orcid.org/0000-0002-7197-9557

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Journal of Zhejiang University SCIENCE A 2015 Vol.16 No.9 P.724-736

http://doi.org/10.1631/jzus.A1500155


A novel approach for parallel disassembly design based on a hybrid fuzzy-time model


Author(s):  Zhi-feng Zhang, Yi-xiong Feng, Jian-rong Tan, Wei-qiang Jia, Guo-dong Yi

Affiliation(s):  The State Key Laboratory of Fluid Power Transmission and Control, Zhejiang University, Hangzhou 310027, China

Corresponding email(s):   fyxtv@zju.edu.cn

Key Words:  Disassembly sequence planning, Dispatching disassembly process, Fuzzy time, Genetic algorithm (GA)


Zhi-feng Zhang, Yi-xiong Feng, Jian-rong Tan, Wei-qiang Jia, Guo-dong Yi. A novel approach for parallel disassembly design based on a hybrid fuzzy-time model[J]. Journal of Zhejiang University Science A, 2015, 16(9): 724-736.

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publisher="Zhejiang University Press & Springer",
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Abstract: 
This paper investigates the problem of parallel disassembly with the consideration of fuzziness. A novel approach is proposed based on optimized dispatching for parallel disassembly in which disassembly time is characterized by the fuzzy sets due to inevitable uncertainties. The proposed approach consists of three parts: in the first part, the fuzzy time-based dispatching disassembly process model is established; in the second part, the boundary conditions of the fuzzy time and the disassembly are derived, and the components’ disassembly order and available stations are encoded together to find the optimal disassembly path; in the final part, the approach is optimized by using genetic algorithm (GA) to minimize the total time and cost, and the solution is compared with other algorithms. Finally, a case study for a hydraulic press disassembly is presented to verify the effectiveness and feasibility of the proposed approach.

The work investigates an interesting disassembly problem with the two objectives: minimizing disassembly time and minimizing disassembly cost. A GA algorithm is proposed to solve this problem. A real case study is conducted to evaluate the proposed algorithm.

一种基于混合模糊模型的新型并行拆卸设计 方法

目的:解决考虑模糊环境条件影响下的复杂机械产品并行拆卸路径规划问题,并给出成本和模糊时间最优的拆卸方案。
创新点:建立混合模糊模型,引入三角模糊数表示拆卸工序加工时间,提高拆卸路径规划的环境适应性;采用并行加工方法,尽可能地提高生产资源利用效率,缩短加工时间和降低加工成本;使用混合编码方式,用同一条染色体表示拆卸工序和工位信息,简化模型表达和运算;在遗传算法中引入高斯变异方法,提高算法的收敛速度。
方法:1. 引入一个包含N个工位和L个零部件的拆卸序列规划问题,提出混合模糊拆卸模型实现对此问题的数学描述;2. 采用包含高斯变异算子的遗传算法,对结果进行优化计算,以得到最短的模糊加工时间和加工成本;3. 将本文所述方法的计算结果与快速搜索随机树算法的运行结果进行比较。
结论:在算法分别迭代50次、100次和150次的情况下,本文所述方法得到的最优解均优于快速搜索随机树算法的解,并且运行时间均短于快速搜索随机树算法。

关键词:并行拆卸;序列规划;模糊时间;遗传算法

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1]Aguinaga, I., Borro, D., Matey, L., 2008. Parallel RRT-based path planning for selective disassembly planning. International Journal of Advanced Manufacturing Technology, 36(11-12):1221-1233.

[2]Aydemir-Karadag, A., Turkbey, O., 2013. Multi-objective optimization of stochastic disassembly line balancing with station paralleling. Computers and Industrial Engineering, 65(3):413-425.

[3]Das, S.K., Yedlarajiah, P., Narendra, R., 2000. An approach for estimating the end-of-life product disassembly effort and cost. International Journal of Production Research, 38(3):657-673.

[4]González, B., Adenso-Díaz, B., 2006. A scatter search approach to the optimum disassembly sequence problem. Computers and Operations Research, 33(6):1776-1793.

[5]Gungor, A., Gupta, S.M., 2001. A solution approach to the disassembly line balancing problem in the presence of task failures. International Journal of Production Research, 39(7):1427-1467.

[6]Ilamparithi, T., Nandi, S., Subramanian, J., 2015. A disassembly-free offline detection and condition monitoring technique for eccentricity faults in salient-pole synchronous machines. IEEE Transactions on Industry Applications, 51(2):1505-1515.

[7]Kang, J.G., Lee, D.H., Xirouchakis, P., et al., 2001. Parallel disassembly sequencing with sequence-dependent operation times. CIRP Annals-Manufacturing Technology, 50(1):343-346.

[8]Lambert, A.J.D., 2006. Exact methods in optimum disassembly sequence search for problems subject to sequence dependent costs. Omega, 34(6):538-549.

[9]Li, H., 2005. Fuzzy Mathematics and Practical Calculation Method. Science Press, Beijing, China, p.352-364 (in Chinese).

[10]Li, J.R., Khoo, L.P., Tor, S.B., 2005. An object-oriented intelligent disassembly sequence planner for maintenance. Computers in Industry, 56(7):699-718.

[11]Li, Z., Cheng, Z., Feng, Y., et al., 2013. An integrated method for flexible platform modular architecture design. Journal of Engineering Design, 24(1):25-44.

[12]Li, Z.K., Li, X.R., Zhu, Z.C., 2011. Scalable platform robust reconfiguration method with sensitivity analysis and fuzzy clustering. Applied Mechanics and Materials, 52-54:1026-1031.

[13]Liu, A., Lu, S.C.Y., 2014. Alternation of analysis and synthesis for concept generation. CIRP Annals-Manufacturing Technology, 63(1):177-180.

[14]Liu, A., Wuest, T., Wei, W., et al., 2014. Application of prospect theory on car sharing product service system. The 6th CIRP Conference on Industrial Product-Service Systems, Ontario, Canada, p.350-355.

[15]Rickli, J.L., Camelio, J.A., 2013. Multi-objective partial disassembly optimization based on sequence feasibility. Journal of Manufacturing Systems, 32(1):281-293.

[16]Shi, Y., Li, B., Zhang, Z., 2011. Layout design of satellite module using a modified artificial bee colony algorithm. Advanced Science Letters, 4(8-10):3178-3181.

[17]Tang, Y., 2009. Learning-based disassembly process planner for uncertainty management. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 39(1):134-143.

[18]Tian, G., Zhou, M., Chu, J., 2013. A chance constrained programming approach to determine the optimal disassembly sequence. IEEE Transactions on Automation Science and Engineering, 10(4):1004-1013.

[19]Tian, G., Chu, J., Hu, H., et al., 2014. Technology innovation system and its integrated structure for automotive components remanufacturing industry development in China. Journal of Cleaner Production, 85:419-432.

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

[21]Xia, K., Gao, L., Li, W., et al., 2014. Disassembly sequence planning using a simplified teaching-learning-based optimization algorithm. Advanced Engineering Informatics, 28(4):518-527.

[22]Zhang, X.F., Yu, G., Hu, Z.Y., et al., 2014. Parallel disassembly sequence planning for complex products based on fuzzy-rough sets. International Journal of Advanced Manufacturing Technology, 72(1-4):231-239.

[23]Zimmermann, H.J., 2001. Fuzzy Set Theory—and Its Applications. Kluwer Academic Publishers, Boston, USA, p.57-60.

[24]Zussman, E., Zhou, M., 1999. A methodology for modeling and adaptive planning of disassembly processes. IEEE Transactions on Robotics and Automation, 15(1):190-194.

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