Journal of Intelligent Manufacturing

, Volume 30, Issue 1, pp 383–403 | Cite as

Eco-modular product architecture identification and assessment for product recovery

  • Samyeon Kim
  • Seung Ki MoonEmail author


In order to improve the efficiency of disassembly and product recovery of an abandoned product at the end-of-life stage, it is essential to develop modular product architecture by considering manufacturing and recovering processes in early product design stage. In this paper, a novel concept of a design methodology is introduced to develop eco-modular product architecture and assess the modularity of the architecture from the viewpoint of product recovery. Eco-modular product architecture contributes to enhancing product recovery processes by recycling and reusing modules without full disassembly at component or material levels. It leads to less consumption of natural resources and less landfill damage to the environment. Three sustainable modular drivers, namely, interface complexity, material similarity, and lifespan similarity, are introduced to reconstruct the modular architecture of commercial products into the eco-modular architecture. Alternatives of modular architectures are identified by Markov Cluster Algorithm based on these sustainable modular drivers and physical interconnections of the components of product architecture. To select the eco-modular architecture from these alternatives, we propose modularity assessment metrics to identify independent interactions between modules and the degrees of similarity within each module. To demonstrate the effectiveness of the proposed methodology, a case study is performed with a coffee maker.


Eco-module Markov Cluster Algorithm Modularity assessment Product architecture Product recovery 



This work was supported by an AcRF Tier 1 Grant (RG94/13) from Ministry of Education, Singapore.


  1. Asikoglu, O., & Simpson, T. W. (2012). A new method for evaluating design dependencies in product architectures. Paper presented at the 12th AIAA aviation technology, integration, and operations (ATIO) conference and 14th AIAA/ISSMO multidisciplinary analysis and optimization conference Indianapolis, Indiana, USA, Sept 17-19, 2012.Google Scholar
  2. Baayen, H. (2000). Eco-indicator 99 manual for designers. Ministry of Housing, Spatial Planning and the Environment, Hague, Netherlands. Accessed Dec 1, 2015, from
  3. Behdad, S., Berg, L. P., Thurston, D., & Vance, J. (2014). Leveraging virtual reality experiences with mixed-integer nonlinear programming visualization of disassembly sequence planning under uncertainty. Journal of Mechanical Design, 136(4), 041005. doi: 10.1115/1.4026463.Google Scholar
  4. Behdad, S., Kwak, M., Kim, H., & Thurston, D. (2010). Simultaneous selective disassembly and end-of-life decision making for multiple products that share disassembly operations. Journal of Mechanical Design, 132(4), 041002–041002. doi: 10.1115/1.4001207.Google Scholar
  5. Bernardes, J. S., Vieira, F. R., Costa, L. M., & Zaverucha, G. (2015). Evaluation and improvements of clustering algorithms for detecting remote homologous protein families. BMC Bioinformatics, 16(1), 1–14. doi: 10.1186/s12859-014-0445-4.Google Scholar
  6. Borjesson, F., & Hölttä-Otto, K. (2014). A module generation algorithm for product architecture based on component interactions and strategic drivers. Research in Engineering Design, 25(1), 31–51. doi: 10.1007/s00163-013-0164-2.Google Scholar
  7. Chiriac, N., Hölttä-Otto, K., Lysy, D., & Suh, E. S. (2011). Level of modularity and different levels of system granularity. Journal of Mechanical Design, 133(10), 101007.Google Scholar
  8. Chun-Che, H., & Kusiak, A. (1998). Modularity in design of products and systems. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, 28(1), 66–77. doi: 10.1109/3468.650323.Google Scholar
  9. Dahmus, J. B., Gonzalez-Zugasti, J. P., & Otto, K. N. (2001). Modular product architecture. Design Studies, 22(5), 409–424. doi: 10.1016/S0142-694X(01)00004-7.Google Scholar
  10. Dobberfuhl, A., & Lange, M. W. (2009). Interfaces per module: Is there an ideal number? Paper presented at the ASME 2009 international design engineering technical conferences and computers and information in engineering conference, San Diego, California, USA, Aug 30–Sept 2, 2009.Google Scholar
  11. Du, G., Jiao, R. J., & Chen, M. (2014). Joint optimization of product family configuration and scaling design by Stackelberg game. European Journal of Operational Research, 232(2), 330–341. doi: 10.1016/j.ejor.2013.07.021.Google Scholar
  12. Erixon, G. (1996). Modular function development MFD, support for good product structure creation. Paper presented at the DS 53: Proceedings of the 2nd WDK workshop on product structuring, Delft University of Technology, Netherlands, June 03–04Google Scholar
  13. Erixon, G. (1998). Modular function deployment—a method for product modularisation. PhD thesis, The Royal Institute of Technology, Sweden.Google Scholar
  14. Fixson, S. K. (2005). Product architecture assessment: A tool to link product, process, and supply chain design decisions. Journal of Operations Management, 23(3–4), 345–369. doi: 10.1016/j.jom.2004.08.006.Google Scholar
  15. Fujita, K., & Yoshida, H. (2004). Product variety optimization simultaneously designing module combination and module attributes. Concurrent Engineering, 12(2), 105–118. doi: 10.1177/1063293x04044758.Google Scholar
  16. GÜngÖr, A., & Gupta, S. M. (2001). Disassembly sequence plan generation using a branch-and-bound algorithm. International Journal of Production Research, 39(3), 481–509. doi: 10.1080/00207540010002838.Google Scholar
  17. Helmer, R., Yassine, A., & Meier, C. (2010). Systematic module and interface definition using component design structure matrix. Journal of Engineering Design, 21(6), 647–675. doi: 10.1080/09544820802563226.Google Scholar
  18. Hirtz, J., Stone, R. B., McAdams, D. A., Szykman, S., & Wood, K. L. (2002). A functional basis for engineering design: Reconciling and evolving previous efforts. Research in Engineering Design, 13(2), 65–82. doi: 10.1007/s00163-001-0008-3.Google Scholar
  19. Hölttä, K. M. M., & Otto, K. N. (2005). Incorporating design effort complexity measures in product architectural design and assessment. Design Studies, 26(5), 463–485. doi: 10.1016/j.destud.2004.10.001.Google Scholar
  20. Ilgin, M. A., & Gupta, S. M. (2010). Environmentally conscious manufacturing and product recovery (ECMPRO): A review of the state of the art. Journal of Environmental Management, 91(3), 563–591. doi: 10.1016/j.jenvman.2009.09.037.Google Scholar
  21. Ishii, K., Eubanks, C. F., & Di Marco, P. (1994). Design for product retirement and material life-cycle. Materials & Design, 15(4), 225–233. doi: 10.1016/0261-3069(94)90007-8.Google Scholar
  22. Jose, A., & Tollenaere, M. (2005). Modular and platform methods for product family design: Literature analysis. Journal of Intelligent Manufacturing, 16(3), 371–390. doi: 10.1007/s10845-005-7030-7.Google Scholar
  23. Jung, S., & Simpson, T. W. (2014). A clustering method using new modularity indices and genetic algorithm with extended chromosomes. Paper presented at the DSM 14 proceedings of the 16th international DSM conference: Risk and change management in complex systems, Paris, France, July 2–4, 2014.Google Scholar
  24. Jung, S., Simpson, T. W., & Asikoglu, O. (2014). Using interfaces to drive module definition: Investigating the impact of a new design dependency measure. Paper presented at the ASME 2014 international design engineering technical conferences and computers and information in engineering conference (DETC2014-34555), Buffalo, New York, USA, Aug 17–20, 2014.Google Scholar
  25. Kara, S., Mazhar, M., Kaebernick, H., & Ahmed, A. (2005). Determining the reuse potential of components based on life cycle data. CIRP Annals—Manufacturing Technology, 54(1), 1–4. doi: 10.1016/S0007-8506(07)60036-5.Google Scholar
  26. Kim, S., Baek, J. W., Moon, S. K., & Jeon, S. M. (2015). A new approach for product design by integrating assembly and disassembly sequence structure planning. In Proceedings of the 18th Asia Pacific symposium on intelligent and evolutionary systems (Vol. 1, pp. 247–257). Springer International Publishing, Switzerland.Google Scholar
  27. Krause, D., Beckmann, G., Eilmus, S., Gebhardt, N., Jonas, H., & Rettberg, R. (2014). Advances in product family and product platform design. In T. W. Simpson, J. Jiao, Z. Siddique, & K. Hölttä-Otto (Eds.), Integrated development of modular product families: A methods toolkit (pp. 245–269). New York: Springer.Google Scholar
  28. Kwak, M. J., Hong, Y. S., & Cho, N. W. (2009). Eco-architecture analysis for end-of-life decision making. International Journal of Production Research, 47(22), 6233–6259. doi: 10.1080/00207540802175329.Google Scholar
  29. Lambert, A. J. D. (2002). Determining optimum disassembly sequences in electronic equipment. Computers & Industrial Engineering, 43(3), 553–575. doi: 10.1016/S0360-8352(02)00125-0.Google Scholar
  30. Lei, X., Wang, F., Wu, F.-X., Zhang, A., & Pedrycz, W. (2016). Protein complex identification through Markov clustering with firefly algorithm on dynamic protein–protein interaction networks. Information Sciences, 329, 303–316. doi: 10.1016/j.ins.2015.09.028.Google Scholar
  31. Lindahl, M., Sundin, E., Östlin, J., & Björkman, M. (2006). Concepts and definitions for product recovery analysis and clarification of the terminology used in academia and industry. In D. Brissaud, S. Tichkewitch, & P. Zwolinski (Eds.), Innovation in life cycle engineering and sustainable development (pp. 123–138). Netherlands: Springer.Google Scholar
  32. Ljungberg, L. Y. (2007). Materials selection and design for development of sustainable products. Materials & Design, 28(2), 466–479. doi: 10.1016/j.matdes.2005.09.006.Google Scholar
  33. Mazhar, M. I., Kara, S., & Kaebernick, H. (2007). Remaining life estimation of used components in consumer products: Life cycle data analysis by Weibull and artificial neural networks. Journal of Operations Management, 25(6), 1184–1193. doi: 10.1016/j.jom.2007.01.021.Google Scholar
  34. Meng, X., Jiang, Z., & Huang, G. Q. (2007). On the module identification for product family development. The International Journal of Advanced Manufacturing Technology, 35(1–2), 26–40. doi: 10.1007/s00170-006-0712-2.Google Scholar
  35. Moon, S. K., & McAdams, D. A. (2012). A market-based design strategy for a universal product family. Journal of Mechanical Design, 134(11), 111007. doi: 10.1115/1.4007395.Google Scholar
  36. Moon, S. K., Park, K. J., & Simpson, T. W. (2014). Platform design variable identification for a product family using multi-objective particle swarm optimization. Research in Engineering Design, 25(2), 95–108. doi: 10.1007/s00163-013-0166-0.Google Scholar
  37. Moon, S. K., Simpson, T. W., & Kumara, S. R. T. (2010). A methodology for knowledge discovery to support product family design. Annals of Operations Research, 174(1), 201–218. doi: 10.1007/s10479-008-0349-7.Google Scholar
  38. Mudgal, S., Tinetti, B., Lyons, L., Lavelle, P., Cornier, A., & Sannier, C. (2011). Preparatory studies for ecodesign requirements of EuPs (III): Lot 25: Non-tertiary coffee machines, Task 2: Economic and market analysis, Report for European Commission (DG ENER) (pp. 1–35). Paris, France: BIO Intelligence Service.Google Scholar
  39. Newcomb, P. J., Bras, B., & Rosen, D. W. (1998). Implications of modularity on product design for the life cycle. Journal of Mechanical Design, 120(3), 483–490.Google Scholar
  40. Otto, K. N., & Wood, K. L. (2001). Product design: Techniques in reverse engineering and new product development: Upper Saddle River. New Jersey: Prentice Hall.Google Scholar
  41. Pimmler, T. U., & Eppinger, S. D. (1994). Integration analysis of product decompositions. Paper presented at the Proceedings of the ASME design engineering technical conferences—6th international conference on design theory and methodology Minneapolis, MN, USA.Google Scholar
  42. Ramani, K., Ramanujan, D., Bernstein, W. Z., Zhao, F., Sutherland, J., Handwerker, C., et al. (2010). Integrated sustainable life cycle design: A review. Journal of Mechanical Design, 132(9), 091004. doi: 10.1115/1.4002308.Google Scholar
  43. Smith, S., & Chen, W.-H. (2011). Rule-based recursive selective disassembly sequence planning for green design. Advanced Engineering Informatics, 25(1), 77–87. doi: 10.1016/j.aei.2010.03.002.
  44. Smith, S., Smith, G., & Chen, W.-H. (2012). Disassembly sequence structure graphs: An optimal approach for multiple-target selective disassembly sequence planning. Advanced Engineering Informatics, 26(2), 306–316. doi: 10.1016/j.aei.2011.11.003.
  45. Sosa, M. E., Eppinger, S. D., & Rowles, C. M. (2003). Identifying modular and integrative systems and their impact on design team interactions. Journal of Mechanical Design, 125(2), 240–252. doi: 10.1115/1.1564074.
  46. Thebeau, R. E. (2001). Knowledge management of system interfaces and interactions from product development processes. M.S. Thesis, Massachusetts Institute of Technology, USA.Google Scholar
  47. Thierry, M., Salomon, M., van Nunen, J., & van Wassenhove, L. (1995). Strategic issues in product recovery management. California Management Review, 37(2), 114–135.Google Scholar
  48. 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. doi: 10.1016/j.eswa.2007.04.018.Google Scholar
  49. Ulrich, K. T. (1995). The role of product architecture in the manufacturing firm. Research Policy, 24(3), 419–440. doi: 10.1016/0048-7333(94)00775-3.Google Scholar
  50. Ulrich, K. T., & Eppinger, S. D. (2008). Product design and development (4th ed.). Boston: McGraw-Hill Higher Education.Google Scholar
  51. Van Dongen, S. M. (2000). Graph clustering by flow simulation. Ph.D. Thesis, Utrecht University, Netherlands.Google Scholar
  52. Yan, J., Feng, C., & Cheng, K. (2012). Sustainability-oriented product modular design using kernel-based fuzzy c-means clustering and genetic algorithm. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 226(10), 1635–1647.Google Scholar
  53. Yigit, A. S., Ulsoy, A. G., & Allahverdi, A. (2002). Optimizing modular product design for reconfigurable manufacturing. Journal of Intelligent Manufacturing, 13(4), 309–316. doi: 10.1023/a:1016032714680.Google Scholar
  54. Yu, T.-L., Yassine, A., & Goldberg, D. (2007). An information theoretic method for developing modular architectures using genetic algorithms. Research in Engineering Design, 18(2), 91–109. doi: 10.1007/s00163-007-0030-1.Google Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.School of Mechanical and Aerospace EngineeringNanyang Technological UniversitySingaporeSingapore

Personalised recommendations