Implementing Smart Virtual Product Development (SVPD) to Support Product Manufacturing

  • Muhammad Bilal AhmedEmail author
  • Cesar Sanin
  • Edward Szczerbicki
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11431)


This paper illustrates the concept of providing the manufacturing knowledge during early stages of product life cycle to experts working on product development. The aim of this research is to enable a more collaborative product development environment by using Smart Virtual Product Development (SVPD) system, which is powered by Set of Experience Knowledge Structure (SOEKS) and Decisional DNA (DDNA). It enhances the industrial product development process by storing, using and sharing previous manufacturing experience and knowledge. This knowledge is stored in form of formal decisional events after being collected from the set of similar products having some common functions and features. The proposed system uses a collective, team-like knowledge developed by product designers, manufactures, and metrologists. Implementing this system in the process of product development enables the small and medium enterprises (SMEs) to take proper decisions at appropriate time by reducing mistakes at an early stages of product development.


Smart virtual product development Product development Manufacturing capability analysis and process planning Set of experience knowledge structure Decisional DNA 


  1. 1.
    Clark, K.B., Fujimoto, T.: Product Development Performance: Strategy, Organization, and Management in the World Auto Industry. Harvard Business School, Boston (1991)Google Scholar
  2. 2.
    Hong, P., Doll, W.J., Nahm, A.Y., Li, X.: Knowledge sharing in integrated product development. Eur. J. Innov. Manag. 7, 102–112 (2004)CrossRefGoogle Scholar
  3. 3.
    Hayes, C.C., Goel, A.K., Tumer, I.Y., Agogino, A.M., Regli, W.C.: Intelligent support for product design: looking backward, looking forward. J. Comput. Inf. Sci. Eng. 11, 021007 (2011)CrossRefGoogle Scholar
  4. 4.
    Nonaka, I., Takeuchi, H.: The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation. Oxford University Press, Oxford (1995)Google Scholar
  5. 5.
    Hedberg Jr., T.D., Hartman, N.W., Rosche, P., Fischer, K.: Identified research directions for using manufacturing knowledge earlier in the product life cycle. Int. J. Prod. Res. 55, 819–827 (2017)CrossRefGoogle Scholar
  6. 6.
    Rodgers, P.A., Clarkson, P.J.: Knowledge usage in new product development (NPD). In: IDATER 1998 Conference. Loughbourogh University, Loughborough (1998)Google Scholar
  7. 7.
    Forbes, H., Schaefer, D.: Social product development: the democratization of design, manufacture and innovation. Prosedia CIRP 60, 404–409 (2017)CrossRefGoogle Scholar
  8. 8.
    Feng, S.C., Bernstein, W.Z., Hedberg, T., Feeney, A.B.: Toward knowledge management for smart manufacturing. J. Comput. Inf. Sci. Eng. 17, 031016 (2017)CrossRefGoogle Scholar
  9. 9.
    Sanin, C., Szczerbicki, E.: Towards the construction of decisional DNA: a set of experience knowledge structure Java class within an ontology system. Cybern. Syst. Int. J. 38, 859–878 (2007)CrossRefGoogle Scholar
  10. 10.
    Simpson, T.W., Maier, J.R., Mistree, F.: Product platform design: method and application. Res. Eng. Des. 13, 2–22 (2001)CrossRefGoogle Scholar
  11. 11.
    Francalanza, E., Borg, J., Constantinescu, C.: A knowledge-based tool for designing cyber physical production systems. Comput. Ind. 84, 39–58 (2017)CrossRefGoogle Scholar
  12. 12.
    Tjalve, E.: A Short Course in Industrial Design. Elsevier, Amsterdam (2015)Google Scholar
  13. 13.
    Unger, D., Eppinger, S.: Improving product development process design: a method for managing information flows, risks, and iterations. J. Eng. Des. 22, 689–699 (2011)CrossRefGoogle Scholar
  14. 14.
    Johansen, K.: Collaborative product introduction within extended enterprises. Doctoral dissertation. Institutionen för konstruktions-och produktionsteknik (2005)Google Scholar
  15. 15.
    Cagan, J., Vogel, C.M.: Creating breakthrough products: innovation from product planning to program approval. Financial Times Prentice Hall Press, Upper Saddle River (2002)Google Scholar
  16. 16.
    Wasim, A., Shehab, E., Abdalla, H., Al-Ashaab, A., Sulowski, R., Alam, R.: An innovative cost modelling system to support lean product and process development. Int. J. Adv. Manuf. Technol. 65(1–4), 165–181 (2013)CrossRefGoogle Scholar
  17. 17.
    Nunes, M.L., Pereira, A., Alves, A.: Smart products development approaches for Industry 4.0. Procedia Manuf. 13, 1215–1222 (2017)CrossRefGoogle Scholar
  18. 18.
    Khan, M.S., et al.: Towards lean product and process development. Int. J. Comput. Integr. Manuf. 26, 1105–1116 (2013)CrossRefGoogle Scholar
  19. 19.
    Brown, J.S., Duguid, P.: Balancing act: how to capture knowledge without killing it. Harvard Bus. Rev. 78, 73–80 (2000)Google Scholar
  20. 20.
    Sanin, C., Szczerbicki, E.: Set of experience: a knowledge structure for formal decision events. Found. Control Manag. Sci. 3, 95–113 (2005)Google Scholar
  21. 21.
    Sanin, C., Szczerbicki, E.: Experience-based knowledge representation: SOEKS. Cybern. Syst. Int. J. 40, 99–122 (2009)CrossRefGoogle Scholar
  22. 22.
    Shafiq, S.I., Sanín, C., Szczerbicki, E.: Set of experience knowledge structure (SOEKS) and decisional DNA (DDNA): past, present and future. Cybern. Syst. 45, 200–215 (2014)CrossRefGoogle Scholar
  23. 23.
    Ahmed, M.B., Sanin, C., Szczerbicki, E.: Experience based decisional DNA (DDNA) to support sustainable product design. In: Dao, D., Howlett, R.J., Setchi, R., Vlacic, L. (eds.) KES-SDM 2018. SIST, vol. 130, pp. 174–183. Springer, Cham (2019). Scholar
  24. 24.
    Shafiq, S.I., Sanin, C., Toro, C., Szczerbicki, E.: Virtual engineering process (VEP): a knowledge representation approach for building bio-inspired distributed manufacturing DNA. Int. J. Prod. Res. 54, 7129–7142 (2016)CrossRefGoogle Scholar
  25. 25.
    Shafiq, S.I., Sanin, C., Toro, C., Szczerbicki, E.: Virtual engineering object (VEO): toward experience-based design and manufacturing for Industry 4.0. Cybern. Syst. 46, 35–50 (2015)CrossRefGoogle Scholar
  26. 26.
    Sanin, C., Szczerbicki, E.: Using XML for implementing set of experience knowledge structure. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds.) KES 2005. LNCS (LNAI), vol. 3681, pp. 946–952. Springer, Heidelberg (2005). Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Muhammad Bilal Ahmed
    • 1
    Email author
  • Cesar Sanin
    • 1
  • Edward Szczerbicki
    • 2
  1. 1.The University of NewcastleCallaghanAustralia
  2. 2.Gdansk University of TechnologyGdanskPoland

Personalised recommendations