Advertisement

A Distributed Service of Selective Disassembly Planning for Waste Electrical and Electronic Equipment with Case Studies on Liquid Crystal Display

  • Weidong LiEmail author
  • K. Xia
  • B. Lu
  • K. M. Chao
  • L. Gao
  • J. X. Yang
Chapter
Part of the Springer Series in Advanced Manufacturing book series (SSAM)

Abstract

Waste Electrical and Electronic Equipment (WEEE) are one of the most significant waste streams in modern societies. In the past decade, disassembly of WEEE to support remanufacturing and recycling has been growingly adopted by industries. With the increasing customization and diversity of Electrical and Electronic Equipment (EEE) and more complex assembly processes, full disassembly of WEEE is rarely an ideal solution due to high disassembly cost. Selective disassembly, which prioritizes operations for partial disassembly according to the legislative and economic considerations of specific stakeholders, is becoming an important yet still challenging research topic in recent years. In this chapter, a Particle Swarm Optimization (PSO)-based selective disassembly planning method embedded with customizable decision-making models and a novel generic constraint handling algorithm has been developed. With multi-criteria decision making models, the developed method is flexible to handle WEEE to meet the various requirements of stakeholders. Based on the generic constraint handling and intelligent optimization algorithms, the research is capable to process complex constraints and achieve optimized selective plans. Practical cases on Liquid Crystal Display (LCD) televisions have been used to verify and demonstrate the effectiveness of the research in different application scenarios. A distributed environment to deploy the service for remote access and control has been designed to support collaborative work.

Keywords

Particle Swarm Optimization Particle Swarm Optimization Algorithm Liquid Crystal Display Potential Recovery Disassembly Process 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This research was carried out as a part of the GREENet and CASES projects which are supported by a Marie Curie International Research Staff Exchange Scheme Fellowship within the 7th European Community Framework Programme under the grant agreement No 269122 and No 294931. The chapter reflects only the authors’ views and the Union is not liable for any use that may be made of the information contained therein.

The authors would also appreciate Mr Qiang Peng, the Technical Director of the Guangdong Changhong Electronics Company, Ltd., and his team for their strong support during the project in terms of technical consultancy/discussions and raw data providing/explanations.

References

  1. 1.
    Jovane F, Yoshikawa H, Alting L, Boer CR, Westkamper E, Williams D, Tseng M, Seliger G, Paci AM (2008) The incoming global technological and industrial revolution towards competitive sustainable manufacturing. CIRP Ann Manuf Technol 75:641–659Google Scholar
  2. 2.
    Walther G, Steinborn J, Spengler TS, Luger T, Herrmann C (2010) Implementation of the WEEE-directive—economic effects and improvement potentials for reuse and recycling in Germany. Int J Adv Manuf Technol 47:461–474CrossRefGoogle Scholar
  3. 3.
    Hicks C, Dietmar R, Eugster M (2005) The recycling and disposal of electrical and electronic waste in China—legislative and market responses. Environ Impact Assess Rev 25:447–459CrossRefGoogle Scholar
  4. 4.
    Kopacek B, Kopacek P (1999) Intelligent disassembly of electronic equipment. Annu Rev Control 23:165–170Google Scholar
  5. 5.
    Duflou JR, Seliger G, Kara S, Umeda Y, Ometto A, Willems B (2008) Efficiency and feasibility of product disassembly: a case-based study. CIRP Ann Manuf Technol 57:583–600Google Scholar
  6. 6.
    Kernbaum S, Heyer S, Chiotellis S, Seliger G (2009) Process planning for IT-equipment remanufacturing. CIRP J Manuf Sci Technol 2:13–20CrossRefGoogle Scholar
  7. 7.
    Hatcher GD, Ijomah WL, Windmill JFC (2011) Design for remanufacturing: a literature survey and future research needs. J Clean Prod 19:2004–2014CrossRefGoogle Scholar
  8. 8.
    Mayers CK (2007) Strategic, financial, and design implications of extended producer responsibility in Europe: a producer case study. J Ind Ecol 11:113–131CrossRefGoogle Scholar
  9. 9.
    Sander K, Schilling S, Tojo N, van Rossem C, Vernon J, George C (2007) The producer responsibility principle of the WEEE directive. DG ENV. Study Contract N° 07010401/2006/449269/MAR/G4. https://ec.europa.eu/environment/waste/weee/pdf/final_rep_okopol.pdf. Accessed on 01 July 2012
  10. 10.
    Giuntini R, Gaudette K (2003) Remanufacturing: the next great opportunity for boosting US productivity. Business Horizons, November–December 2003, pp 41–48Google Scholar
  11. 11.
    Kara S, Pornprasitpol P, Kaebernick H (2006) Selective disassembly sequencing: a methodology for the disassembly of end-of-life products. CIRP Ann Manuf Technol 55(1):37–40Google Scholar
  12. 12.
    Masui K, Mizuhara K, Ishii K, Rose C (1999) Development of products embedded disassembly process based on end-of-life strategies. In: Proceedings of the EcoDesign’99: 1st international symposium on environmentally conscious design and inverse manufacturing, Tokyo, pp 570–575Google Scholar
  13. 13.
    Chiodo JD, Harrison DJ, Billett EH (2001) An initial investigation into active disassembly using shape memory polymers. Proc Inst Mech Eng Part B: J Eng Manuf 215(5):733–741CrossRefGoogle Scholar
  14. 14.
    Jones N, Harrison D, Billett E, Chiodo J (2004) Electrically self-powered active disassembly. Proc Inst Mech Eng Part B: J Eng Manuf 218(7):689–697CrossRefGoogle Scholar
  15. 15.
    Braunschweig A (2004) Automatic disassembly of snap-in joints in electromechanical devices. In: Proceedings of the 4th international congress mechanical engineering technologies’04, Varna, pp 48–56Google Scholar
  16. 16.
    Hussein H, Harrison D (2008) New technologies for active disassembly: using the shape memory effect in engineering polymers. Int J Prod Dev 6(3/4):431–449CrossRefGoogle Scholar
  17. 17.
    Ijomah WL, Chiodo JD (2010) Application of active disassembly to extend profitable remanufacturing in small electrical and electronic products. Int J Sustain Eng 3(4):246–257CrossRefGoogle Scholar
  18. 18.
    Sundin E, Lindahl M, Ijomah WL (2009) Product design for product/service systems—design experiences from Swedish industry. J Manuf Technol Manag 20(5):723–753CrossRefGoogle Scholar
  19. 19.
    Dindarian A, Gibson AAP, Quariguasi-Frota-Neto J (2012) Electronic product returns and potential reuse opportunities: a microwave case study in the United Kingdom. J Clean Prod 32:22–31CrossRefGoogle Scholar
  20. 20.
    Santochi M, Dini G, Failli F (2002) Computer aided disassembly planning: state of the arts and perspectives. CIRP Ann Manuf Technol 51(2):507–529Google Scholar
  21. 21.
    Lambert AJD (2002) Determining optimum disassembly sequences in electronic equipment. Comput Ind Eng 43(3):553–575CrossRefGoogle Scholar
  22. 22.
    Kuo TC (2012) Waste electronics and electrical equipment disassembly and recycling using Petri net analysis: considering the economic value and environmental impacts. Comput Ind Eng (to appear)Google Scholar
  23. 23.
    Renteria A, Alvarez E, Perez J, Pozo D (2011) A methodology to optimize the recycling process of WEEE: case of television sets and monitors. Int J Adv Manuf Technol 54:789–800CrossRefGoogle Scholar
  24. 24.
    Ryan A, O’Donoghue L, Lewis H (2011) Characterising components of liquid crystal displays to facilitate disassembly. J Clean Prod 19:1066–1071CrossRefGoogle Scholar
  25. 25.
    Li WD, Ong SK, Nee AYC (2002) Hybrid genetic algorithm and simulated annealing approach for the optimization of process plans for prismatic parts. Int J Prod Res 40(8):1899–1922zbMATHCrossRefGoogle Scholar
  26. 26.
    Li WD, McMahon CA (2007) A simulated annealing-based optimization approach for integrated process planning and scheduling. Int J Comput Integr Manuf 20(1):80–95CrossRefGoogle Scholar
  27. 27.
    Kennedy J, Eberhart R (1995) Particle swarm optimization. In: Proceedings of IEEE international conference on neural networks IV, pp 1942–1948Google Scholar
  28. 28.
    Reddy SVB, Shunmugam MS, Narendran TT (1999) Operation sequencing in CAPP using genetic algorithm. Int J Prod Res 37:1063–1074zbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  • Weidong Li
    • 1
    Email author
  • K. Xia
    • 2
  • B. Lu
    • 3
  • K. M. Chao
    • 1
  • L. Gao
    • 2
  • J. X. Yang
    • 3
  1. 1.Faculty of Engineering and ComputingCoventry UniversityCoventryUK
  2. 2.The State Key Laboratory of Digital Manufacturing Equipment and TechnologyHuazhong University of Science and TechnologyWuhanChina
  3. 3.Research Centre of Eco-Environmental SciencesChinese Academy of SciencesBeijingChina

Personalised recommendations