Advertisement

Design for Product Embedded Disassembly

  • Shingo Takeuchi
  • Kazuhiro Saitou
Part of the Studies in Computational Intelligence book series (SCI, volume 88)

This chapter discusses an application of multi-objective genetic algorithm for designing products with a built-in disassembly means that can be triggered by the removal of one or a few fasteners at the end of the product lives. Given component geometries, the method simultaneously determines the spatial configuration of components, locators and fasteners, and the end-of-life (EOL) treatments of components and subassemblies, such that the product can be disassembled for the maxim profit and minimum environmental impact through recycling and reuse via domino-like “self-disassembly” process. A multi-objective genetic algorithm is utilized to search for Pareto optimal designs in terms of 1) satisfaction of the distance specification among components, 2) efficient use of locators on components, 3) profit of EOL scenario, and 4) environmental impact of EOL scenario. The method is applied to a simplified model of the Power Mac G4 cube® for demonstration.

Keywords

Design for disassembly environmentally-conscious design Operant behavior design optimization multi-objective genetic algorithm 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Aanstoos, T.A., Torres, V.M., and Nichols, S.P. (1998) Energy model for end-of-life computer disposition, IEEE Transactions on components, packaging, and manufacturing technology, 21(4): 295–301.CrossRefGoogle Scholar
  2. 1.
    Baldwin, D.F., Abell, TE., Lui, M.-C., De Fazio, T.L., and Whitney, D.E. (1992) An integrated computer aid for generating and evaluating assembly sequences for mechanical products, IEEE Transactions on Robotics and Automation, 7(1): 78–94.CrossRefGoogle Scholar
  3. 2.
    Beasley, D. and Martin, R.R. (1993) Disassembly sequences for objects built from unit cubes, Journal of Compute-Aided Design, 25(12): 751–761.zbMATHCrossRefGoogle Scholar
  4. 3.
    Bonenberger, P.R. (2000) The First Snap-Fit Handbook: Creating Attachments for Plastic Parts, Hanser Gardner Publications, München, Germany.Google Scholar
  5. 4.
    Boothroyd, G. and Alting, L. (1992) Design for assembly and disassembly, Annals of CIRP, 41(22): 625–636.CrossRefGoogle Scholar
  6. 5.
    Boothroyd, G., Dewhurst, P., and Knight, W. (1994) Product Design for Manufacture and Assembly, Marcel Dekker, Inc., New York, NY.Google Scholar
  7. 6.
    Caudill, J.R., Zhou, M., Yan, P., and Jim, J. (2002) Multi-life cycle assessment: an extension of traditional life cycle assessment, In: M.S. Hundal (ed.), Mechanical Life Cycle Handbook, Marcel Dekker. New York, NY, pages 43–80.Google Scholar
  8. 7.
    Chen, R.W., Navinchandra, D., and Prinz, F. (1993) Product design for recyclability: a cost benefit analysis model and its application, IEEE Transactions on Components, Packaging, and Manufacturing Technology, 17(4): 502–507.CrossRefGoogle Scholar
  9. 8.
    Chen, S.-F., Oliver, J.H., Chou, S.-Y., and Chen, L.-L. (1997) Parallel disassembly by onion peeling, Transactions of ASME, Journal of Mechanical Design, 119(22): 267–274.CrossRefGoogle Scholar
  10. 9.
    Corcoran III, A.L. and Wainwright, R.L. (1992) A genetic algorithm for packing in three dimensions, Proceedings of the ACM/SIGAPP Symposium on Applied Computing, Kansas City, Missouri, pages 1021–1030.Google Scholar
  11. 10.
    Das, S.K., Yedlarajiah, P., and 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.zbMATHCrossRefGoogle Scholar
  12. 11.
    De Fazio, T.L. and Whitney, D.E. (1987) Simplified generation of all mechanical assembly, IEEE Transactions of Robotics and Automation, 3(6): 640–658.CrossRefGoogle Scholar
  13. 12.
    Deb, K., Pratap, A., Agarwal, S., and Meyarivan, T. (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II, IEEE Transactions on Evolutionary Computation, 6(2): 182–197.CrossRefGoogle Scholar
  14. 13.
    Desai, A. and Mital, A. (2003) Evaluation of disassemblability to enable design for disassembly in mass production, International Journal of Industrial Ergonomics, 32(4): 265–281.CrossRefGoogle Scholar
  15. 14.
    Dutta, D. and Woo, T.C. (1995) Algorithm for multiple disassembly and parallel assemblies, Transactions of ASME, Journal of Engineering for Industry, 117: 102–109.CrossRefGoogle Scholar
  16. 15.
    Fonseca, C.M. and Fleming, P.J. (1993) Genetic algorithms for multiobjective optimization: formulation, discussion and generalization, Proceedings of the 5th International Conference on Genetic Algorithms, July 17–22, Urbana-Champaign, IL, pages 416–423.Google Scholar
  17. 16.
    Fujita, K., Akagi, S., and Shimazaki, S. (1996) Optimal space partitioning method based on rectangular duals of planar graphs, JSME International Journal, 60: 3662–3669.Google Scholar
  18. 17.
    Glover, F. (1974) Heuristics for Integer Programming using Surrogate Constraints, Business Research Division, University of Colorado.Google Scholar
  19. 18.
    Glover, F. (1986) Further paths for integer programming and links to artificial intelligence, Journal of Computer and Operations Research, 13(5): 533–549.zbMATHCrossRefMathSciNetGoogle Scholar
  20. 19.
    Goggin, K. and Browne, J. (2000) The resource recovery level decision for end-of-life products, Production Planning and Control, 11(7): 628–640.CrossRefGoogle Scholar
  21. 20.
    Goosey, M. and Kellner, R. (2003) Recycling technologies for the treatment of end of life printed circuit boards (PCBs), Circuit World, 29(3): 33–37.CrossRefGoogle Scholar
  22. 21.
    Grignon, P.M. and Fadel, G.M. (1999) Configuration design optimization method, Proceedings of the ASME Design Engineering Technical Conferences and Computers in Engineering Conference, September 12–15, Las Vegas, Nevada, DETC99/DAC-8575.Google Scholar
  23. 22.
    Homem dé Mello, L.S. and Sanderson, A.C. (1990) AND/OR graph representation of assembly plans, IEEE Transactions on Robotics and Automation, 6(2): 188–199.CrossRefGoogle Scholar
  24. 23.
    Homem dé Mello, L.S. and Sanderson, A.C. (1991) A correct and complete algorithm for generation of mechanical assembly sequences, IEEE Transactions on Robotics and Automation, 7(2): 228–240.CrossRefGoogle Scholar
  25. 24.
    Hula, A., Jalali, K., Hamza, K., Skerlos, S., and Saitou, K. (2003) Multi-criteria decision making for optimization of product disassembly under multiple situations, Environmental Science and Technology, 37(23): 5303–5313.CrossRefGoogle Scholar
  26. 25.
    Jain, S. and Gea, H.C. (1998) Two-dimensional packing problems using genetic algorithm, Journal of Engineering with Computers, 14: 206–213.CrossRefGoogle Scholar
  27. 26.
    Kaufman, S.G., Wilson, R.H., Jones, R.E., Calton, T.L., and Ames, A.L. (1996) The Archimedes 2 mechanical assembly planning system, Proceedings of the IEEE International Conference on Robotics and Automation, April, 1996, Minneapolis, Minnesota, pages 3361–3368.Google Scholar
  28. 27.
    Kroll, E., Beardsley, B., and Parulian, A. (1996) A methodology to evaluate ease of disassembly for product recycling, IIE Transactions, 28(10): 837–845.Google Scholar
  29. 28.
    Kolli, A., Cagan, J., and Rutenbar, R. (1996) Packing of generic, three- dimensional components based on multi-resolution modeling, Proceedings of the ASME Design Engineering Technical Conferences and Computers in Engineering Conference, August 18–22, Irvine, California, DETC/DAC-1479.Google Scholar
  30. 29.
    Kuehr, R. and Williams, E. (Eds.) (2003) Computers and the Environment, Kluwer Academic Publishers, Dordrecht, The Netherlands.Google Scholar
  31. 30.
    Kuo, T. and Hsin-Hung, W. (2005) Fuzzy eco-design product development by using quality function development, Proceedings of the EcoDesign: Fourth International Symposium on Environmentally Conscious Design and Inverse Manufacturing, December 12–14, Tokyo, Japan, 2B-3-3F.Google Scholar
  32. 31.
    Lambert, A.J.D. (1999) Optimal disassembly sequence generation for combined material recycling and part reuse, Proceedings of the IEEE International Symposium on Assembly and Task Planning, Portugal, pages 146–151.Google Scholar
  33. 32.
    Lee, S. and Shin, Y.G. (1990) Assembly planning based on geometric reasoning, Computer and Graphics, 14(2): 237–250.CrossRefGoogle Scholar
  34. 33.
    Li, J.R., Tor, S.B., and Khoo, L.P. (2002) A hybrid disassembly sequence planning approach for maintenance, Transactions of ASME, Journal of Computing and Information Science in Engineering, 2(1): 28–37.CrossRefGoogle Scholar
  35. 34.
    Matsui, K., Mizuhara, K., Ishii, K., and Catherine, R.M. (1999) Development of products embedded disassembly process based on end-of-life strategies, Proceedings of EcoDesign: First International Symposium on Environmentally Conscious Design and Inverse Manufacturing, February 1–3, Tokyo, Japan, pages 570–575.Google Scholar
  36. 35.
    Minami, S., Pahng, K.F., Jakiela, M. J., and Srivastave, A. (1995) A cellular automata representation for assembly simulation and sequence generation, Proceedings of the IEEE International Symposium on Assembly and Task Planning, August 10–11, Pittsburgh, Pennsylvania, pages 56–65.Google Scholar
  37. 36.
    O’Shea, B., Kaebernick, H., Grewal, S.S., Perlewitz, H., Müller, K., and Seliger, G. (1999) Method for automatic tool selection for disassembly planning, Assembly Automation, 19(1): 47–54.CrossRefGoogle Scholar
  38. 37.
    Reap, J. and Bras, B. (2002) Design for disassembly and the value of robotic semi-destructive disassembly, Proceedings of the ASME Design Engineering Technical Conferences and Computers and Information in Engineering Conference, September 29 – October 2, Montreal, Canada, DETC2002/DFM-34181.Google Scholar
  39. 38.
    Rose, C.M. and Stevels, A.M. (2001) Metrics for end-of-life strategies (ELSEIM), Proceedings of the IEEE International Symposium on Electronics and the Environment, May 7–9, Denver, Colorado, pages 100–105.Google Scholar
  40. 39.
    Sodhi, R., Sonnenberg, M. and Das, S. (2004) Evaluating the unfastening effort in design for disassembly and serviceability, Journal of Engineering Design, 15(1): 69–90.CrossRefGoogle Scholar
  41. 40.
    Srinivasan, H. and Gadh, R. (2000) Efficient geometric disassembly of multiple components from an assembly using wave propagation, Transactions of ASME, Journal of Mechanical Design, 122(2): 179–184.CrossRefGoogle Scholar
  42. 41.
    Sung, R.C.W., Corney, J.R., and Clark, D.E.R. (2001) Automatic assembly feature recognition and disassembly sequence generation, Transactions of ASME, Journal of Computing and Information Science in Engineering, 1(4): 291–299.CrossRefGoogle Scholar
  43. 42.
    Takeuchi, S. and Saitou, K. (2005) Design for product-embedded disassembly, Proceedings of the ASME Design Engineering Technical Conferences, Long Beach, California, September 24–28, DETC2005-85260.Google Scholar
  44. 43.
    Takeuchi, S. and Saitou, K. (2006) Design for optimal end-of-life scenario via product-embedded disassembly, Proceedings of the ASME Design Engineering Technical Conferences, Philadelphia, Pennsylvania, September 10–13, DETC2006-99475.Google Scholar
  45. 44.
    Williams, E.D. and Sasaki, Y. (2003) Energy analysis of end-of-life options for personal computers: resell, upgrade, recycle, Proceedings of the IEEE International Symposium on Electronics and the Environment, May 19–22, Boston, MA, pages 187–192.Google Scholar
  46. 45.
    Woo, T.C. and Dutta, D. (1991) Automatic disassembly and total ordering in three dimensions, Transactions of ASME, Journal of Engineering for Industry, 113: 207–213.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Shingo Takeuchi
    • 1
  • Kazuhiro Saitou
    • 1
  1. 1.Department of Mechanical EngineeringUniversity of MichiganAnn ArborUSA

Personalised recommendations