Cluster Computing

, Volume 22, Supplement 3, pp 5825–5837 | Cite as

Research for service flow module granularity design based on fuzzy spaces quotient theory

  • Fei ZhangEmail author


In the research of modular design of service flow, this paper proposes a method to partition the service flow module based on fuzzy spaces quotient theory to reduce the subjectivity of module granularity selection. On the basis of service elements identification, the interrelation among service elements is analyzed in detail. And the further evaluation is made from three aspects such as service flow relevance, service source relevance and service function relevance. By working out similarity matrix between service elements and clustering attributes, the integrated fuzzy similarity matrix is obtained. And the service flow module granularity space is educated by cluster service elements through acquiring hierarchical structure using algorithm. Finally by the grey relational analysis theory and the proper index system, the optimal project of service flow module can be obtained. In this paper, the feasibility of the method above is verified by the maintenance service flow and the module granularity design of the excavator walking mechanism.


Modular design of service flow Fuzzy quotient space theory Granularity computing Process chain network Grey evaluation 



This work was financially supported by the National Natural Science Foundation of China (51305417) and the Zhejiang government Science Foundation (16NDJC282YB, 2015Z032).


  1. 1.
    Pahl, G., Beitz, W.: Engineering Design of a Systematic Approach. Springer, London (1996)Google Scholar
  2. 2.
    Suh, N.H.: The Principles of Design. Oxford University Press, New York (1990)Google Scholar
  3. 3.
    Ulrish, K.: The role of product architecture in the manufacturing firm. Res. Policy 24, 419–440 (1995)Google Scholar
  4. 4.
    Erixon, G., Von, Y., Xkull, A., Amstrom, A.: Modularity-the basis for product and factory re-engineering. Ann.-Manuf. Technol. 45(1), 1–6 (1996)Google Scholar
  5. 5.
    Kusiak, A., Huang, C.C.: Developments of modular products. TEEE Trans. Compon. Packag. Manuf. Technol.-Part A 19(4), 523–538 (1996)Google Scholar
  6. 6.
    Stone, R.B., Wood, K.L., Crawford, R.H.: A heuristic method for identifying modules for product architectures. Des. Stud. 21(1), 5–31 (2001)Google Scholar
  7. 7.
    Nuogang, S., Xuesong, M., Youyun, Z.: Product modular division based on house of quality matrix. J. Xi AN Jiaotong Univ. 40(1), 45–49 (2006)Google Scholar
  8. 8.
    Fan, B., Qi, G.: Modeling of product family structure and module analysis method based on complex network. Chin. J. Mech. Eng. 43(3), 187–198 (2007)Google Scholar
  9. 9.
    Gong, J., Qiu, J., Li, G.: Conceptual module identifying for mechanism based on gragh partitioning. J. Natl. Univ. Def. Technol. 29(3), 103–108 (2007)Google Scholar
  10. 10.
    Rijun, W., Jinsheng, Z., Peiqi, G., et al.: Integrated module division method based on axiomatic design and fuzzy program. Trans. Chin. Soci. Agric. Mach. 40(4), 179–183 (2009)Google Scholar
  11. 11.
    Gu, P., Sosal, E.S.: Product modularization for life engineering. Robot. Comput. Integr. Manuf. 15(5), 387–401 (1999)Google Scholar
  12. 12.
    Tseng, H.E., Chang, C.C., Li, J.D.: Modular design to support green life-cycle engineering. Expert Syst. Appl. 34(5), 2524–2537 (2008)Google Scholar
  13. 13.
    Tsai, Y., Wang, K.: The development of modular-based design in considering technology complexity. Eur. J. Oper. Res. 119(3), 629–703 (1999)zbMATHGoogle Scholar
  14. 14.
    Tao, T., Zhifeng, L.: Research on the methodology of green modular design. Chin. J. Mech. Eng. 39(11), 149–154 (2003)Google Scholar
  15. 15.
    Haihong, H., Zifeng, L., Shuwang, W.: Research on methodology of modular design for recycling. Tran. Chin. Soc. Agric. Mach. 37(12), 144–149 (2006)Google Scholar
  16. 16.
    Chen, X.: Research and Application of Green Module Partition Method for Electromechanical Product. Zhejiang University, Hangzhou (2012)Google Scholar
  17. 17.
    Haan, J.D., Meijboom, B., Voordijk, H.: Modularity in supply chains: a multiple case study in the construction industry. Int. J. Oper. Prod. Manag. 26(6), 600–618 (2006)Google Scholar
  18. 18.
    Geum, Y., Kwak, R., Park, Y.: Modularizing services: a modified HoQ approach. Comput. Ind. Eng. 62(2), 579–590 (2012)Google Scholar
  19. 19.
    Zengchan, G.: To study on service modularity in the context of MC. Value Eng. 11, 99–102 (2009)Google Scholar
  20. 20.
    Sampson, S.E., Spring, M.: Customer roles in service supply chains and opportunities for innovation. J. Supply Chain Manag. 48(48), 30–50 (2012)Google Scholar
  21. 21.
    Naijing, W., Wenqing, S.: The application of systems engineering method in modularization design. Technol. Econ. 26(5), 40–47 (2007)Google Scholar
  22. 22.
    Wang, P.P., Ming, X.G., Li, D.: Modular development of product service system. Concurr. Eng. 19(1), 85–96 (2011)Google Scholar
  23. 23.
    Shaohua, H., Hanqing, C.: A systematic literature review on product service system design. Creat. Des. 2, 21–25 (2016)Google Scholar
  24. 24.
    Yang, M.: Product modular analysis based on green design. MING (Attitude) 15, 9–10 (2016)Google Scholar
  25. 25.
    Zhang, K.: Design for Disassembly Research on Green Design of Household Electrics. Nanjing University of Aeronautics and Astronautics, Nanjing (2016)Google Scholar
  26. 26.
    Wei, G., Guangfu, L., Lei, Z.: Research on product’s green module partition for whole life cycle. J. Hefei Univ. Technol. 33(10), 1441–1445 (2010)Google Scholar
  27. 27.
    Yanhui, C., Dejian, Z.: Dissimilarity calculation based cluster analysis method of module base. Comput. Integr. Manuf. Syst. 18(3), 466–471 (2012)Google Scholar
  28. 28.
    Wang, H., Lu, H.: Study based on correlation of structure module creation. Sci. Mosaic 3, 17–19 (2012)Google Scholar
  29. 29.
    Liu, W.: Product Family Planning Method Based on Multi-objective Genetic Algorithm. Zhejiang University, Hangzhou (2016)Google Scholar
  30. 30.
    Hong, T., Xiaowu, S., Sha, L.: Clustering algorithm based on hybrid intelligent algorithm. Microelectron. Comput. 28(12), 96–98 (2011)Google Scholar
  31. 31.
    Lei, W., Xuhui, X., Yingqing, X.: Modular Method of remanufacturing service resources. Comput. Integr. Manuf. Syst. 22(9), 2204–2216 (2016)Google Scholar
  32. 32.
    Zhang, M., Li, G., Gong, J.: Granulating process analysis of products based on the theory of fuzzy quotient space. J. Natl Univ. Def. Technol. 06, 181–186 (2012)Google Scholar
  33. 33.
    Ling, Z.: Theory and Application of Problem Solving. Tsinghua University Press, Beijing (2007)Google Scholar
  34. 34.
    Chao, F., Ming, X.: Optimization method of cloud service composition in cloud manufacturing environment. Appl. Res. Comput. 31(6), 1744–1747 (2014)MathSciNetGoogle Scholar
  35. 35.
    Gualandris, J., Kalchschmidt, M.: Product and process modularity: improving flexibility and reducing supplier failure risk. Int. J. Prod. Res. 51(19), 5757–5770 (2013)Google Scholar
  36. 36.
    Tang, X.Q., Zhu, P., Cheng, J.X.: The structural clustering and analysis of metric based on granular space. Pattern Recognit. 43(11), 3768–3786 (2010)zbMATHGoogle Scholar
  37. 37.
    Yang, X., fei, Z.: Study on service problem design of construction machinery based on PCN. J. Hebei Univ. Technol. 06, 63–68 (2016)Google Scholar
  38. 38.
    Normann, R.: Reframing business: when the map changes the landscape. Int. J. Serv. Ind. Manag. 15(1), 122–125 (2004)Google Scholar
  39. 39.
    Morris, B., Johnston, R.: Dealing with inherent variability—the difference between service and manufacturing explained. Int. J. Oper. Prod. Manag. 7(4), 13–22 (1987)Google Scholar
  40. 40.
    Bitner, M.J., MORGAN, F.N.: Service blueprinting: a practical tool for service innovation. Calif. Manag. Rev. 50(3), 66–94 (2008)Google Scholar
  41. 41.
    Tang, X.Q., Zhu, P., Cheng, J.X.: The structural clustering and analysis of metric based on granular space. Pattern Recognit. 43(11), 3768–3786 (2010)zbMATHGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2017

Authors and Affiliations

  1. 1.Institute of Mechanical EngineeringChina Jiliang UniversityHangzhouChina

Personalised recommendations