Intelligent design based on holographic model using parametric design method

  • Xiaojun Liu
  • Liang Tang
  • Yang Yi
  • Zhonghua Ni
Original Research


The variant design of existing products accounts for a considerable proportion in the process of new product design. Parametric design technology is an effective mean to reuse existing design solutions. However, the current design technology has been unable to meet the needs of product-level parametric rapid design. This paper proposes a product-level parametric management and rapid design method based on the idea of holographic modeling. Firstly, a mechanism to manage the parametric based model (PBM) is set up, and then the dimension management technology is put forward with analyzing the data structure of the base model, meanwhile, the dimension expression, classification, nomenclature and management rules are given. Then, the rapid design method based on PBM is studied, the rapid design principle of the 3D model is described, and the corresponding depth traversal of dimension process is given. At last, a parametric design system for compensator product is developed.


Parametric based model Management mechanism Parametric design Holographic model 



The authors acknowledge the financial sponsored by the National Natural Science Foundation of China (Grant no. 51405081), Qing Lan Project, the Fundamental Research Funds for the Central Universities, and the Six talent peaks project in Jiangsu Province.


  1. Aldefeld B (1988) Variation of geometries based on a geometric-reasoning method. Comput Aided Des 20(3):117–126. CrossRefzbMATHGoogle Scholar
  2. Ashley S (1997) Rapid-response design. Mech Eng 119(12):72–74Google Scholar
  3. Bodein Y, Rose B, Caillaud E (2014) Explicit reference modeling methodology in parametric cad system. Comput Ind 65(1):136–147. CrossRefGoogle Scholar
  4. Brown DC (1998) Defining configuring. Artif Intell Eng Des Anal Manuf 12(4):301–305. CrossRefGoogle Scholar
  5. Chang KH, Joo SH (2006) Design parameterization and tool integration for cad-based mechanism optimization. Adv Eng Softw 37(12):779–796. CrossRefGoogle Scholar
  6. Chapman CB, Pinfold M (2001) The application of a knowledge based engineering approach to the rapid design and analysis of an automotive structure. Adv Eng Softw 32(12):903–912. CrossRefzbMATHGoogle Scholar
  7. Fujita K, Yoshida H (2004) Product variety optimization simultaneously designing module combination and module attributes. Concurr Eng 12(2):105–118. CrossRefGoogle Scholar
  8. Gao XS, Chou SC (1998) Solving geometric constraint systems. I. A global propagation approach. Comput Aided Des 30(1):47–54. CrossRefGoogle Scholar
  9. GB/T12777-2008 (2008) General technical conditions for metal bellows expansion joint. China StandardGoogle Scholar
  10. Ghassabzadeh M, Ghassemi H (2013) An innovative method for parametric design of planing tunnel vessel hull form. Ocean Eng 60(2):14–27. CrossRefGoogle Scholar
  11. Gunn TG (1982) The mechanization of design and manufacturing. Sci Am 247(3):114–130. CrossRefGoogle Scholar
  12. Guo Y, Hu J, Peng Y (2012) A CBR system for injection mould design based on ontology: a case study. Comput Aided Des 44(6):496–508. CrossRefGoogle Scholar
  13. Huang GQ, Li L, Chen X (2007) A tandem evolutionary algorithm for platform product customization. J Comput Inf Sci Eng 7(2):151–159. CrossRefGoogle Scholar
  14. Lee JY, Kim K (1996) Geometric reasoning for knowledge-based parametric design using graph representation. Comput Aided Des 28(10):831–841. CrossRefGoogle Scholar
  15. Lee JY, Kim K (1998) A 2-d geometric constraint solver using dof-based graph reduction. Comput Aided Des 30(11):883–896. CrossRefzbMATHGoogle Scholar
  16. Leizerowicz W, Lin J, Fox MS (1996) Collaborative design using WWW. In: Proceedings of the WET-ICE’96, CERC, University of West VirginiaGoogle Scholar
  17. Li L, Huang GQ (2009) Multiobjective evolutionary optimisation for adaptive product family design. Int J Comput Integr Manuf 22(4):299–314. CrossRefGoogle Scholar
  18. Light R, Gossard D (1982) Modification of geometric models through variational geometry. Comput Aided Des 14(4):209–214. CrossRefGoogle Scholar
  19. Mercado-Colmenero JM, Rubio-Paramio MA, Vizan-Idoipe A et al (2017) A new procedure for the automated design of ejection systems in injection molds. Robotics Comput Integr Manuf 46:68–85. ppCrossRefGoogle Scholar
  20. Mok CK, Chin KS, Lan HB (2008) An internet-based intelligent design system forinjection moulds. Robotics Comput Integr Manuf 24(1):1–15. CrossRefGoogle Scholar
  21. Münzer C, Shea K, Helms B (2012) Automated parametric design synthesis using graph grammars and constraint solving. In: ASME 2012 international design engineering technical conferences and computers and information in engineering conference, pp 517–528.
  22. Nayak RU, Chen W, Simpson TW (2002) A variation-based method for product family design. Eng Optim 34(1):65–81. CrossRefGoogle Scholar
  23. Qian XM (2005) Research on the key technique of concurrent engineering oriented product development process. Doctoral dissertation, Nanjing University of Aeronautics and Astronautics.
  24. Qian XM, Wang NS, Chen WF et al (2003) Research on product structure model based on rapid product design. Comput Integr Manuf Syst 9(1):11–14. Google Scholar
  25. Rahimifard A, Weston RH (2009) A resource-based modelling approach to support responsive manufacturing systems. Int J Adv Manuf Technol 45(11–12):1197–1214. Google Scholar
  26. Simpson TW, Maier JR, Mistree F (2001) Product platform design: method and application. Res Eng Des 13(1):2–22. CrossRefGoogle Scholar
  27. Sutherland IE (1964) Sketchpad: a man-machine graphical communication system (outstanding dissertations in the computer sciences), vol 18, no 3, pp 265–272. Garland Publishing, Inc, New York.
  28. Suzuki H, Ando H, Kimura F (1990) Geometric constraints and reasoning for geometrical cad systems. Comput Graph 14(2):211–224. CrossRefGoogle Scholar
  29. Tao CS (2004) Research on partial parametric design method and system realization. Doctoral dissertation, Nanjing University of Science and Technology.
  30. Tseng MM, Jiao J (1997) Case-based evolutionary design for mass customization. Comput Ind Eng 33(1):319–323. CrossRefGoogle Scholar
  31. Tseng MM, Jiao J, Merchant ME (1996) Design for mass customization. CIRP Ann Manuf Technol 45(1):153–156. CrossRefGoogle Scholar
  32. Wang F, Yu XL (2001) Research and development of product-level three-dimensional parametric design system. J Comput Aided Des Comput Graph 13(11):1012–1018. Google Scholar
  33. Xu MX (1998) Research and implementation of parametric design model. Doctoral dissertation, Graduate School of Chinese Academy of Sciences (Institute of Computing Technology)Google Scholar
  34. Zhang F, Chen ZN, Yan XG et al (2008) Product configuration model based on SML. China Mech Eng 19(6):683–687. Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Mechanical EngineeringSoutheast UniversityNanjingPeople’s Republic of China
  2. 2.Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical InstrumentsSoutheast UniversityNanjingPeople’s Republic of China

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