Modular Experience-Based Smart Innovation Engineering System

  • Mohammad Maqbool WarisEmail author
  • Cesar Sanin
  • Edward Szczerbicki
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 524)


The current paper presents the systematic approach for supporting the product innovation process of manufactured products. The proposed system uses a collective, team-like knowledge developed by innovation related experiences of the formal decisional events. The proposed system for smart innovation engineering carries the promise to support the innovation processes in a quick and efficient way. It stores the past decisional events or sets of experiences related to innovation issues, which significantly enhances innovation progression. Implementing this system in the process of product innovation enables entrepreneurs and organizations to take enhanced innovative decisions at appropriate time.


Smart innovation engineering Product innovation Product design Set of experience Decisional DNA Smart knowledge management system 


  1. 1.
    Sanin, C., Szczerbicki, E.: Towards decisional DNA: developing a holistic set of experience knowledge structure. Found Control Manage Sci 9, 109–122 (2008)Google Scholar
  2. 2.
    Sheu, D.D., Lee, H.-K.: A proposed process for systematic innovation. Int. J. Prod. Res. 49, 847–868 (2011)Google Scholar
  3. 3.
    Waris, M.M., Sanin, C., Szczerbicki, E.: Smart innovation management in product life cycle. In: Wilimowska, Z., Borzemski, L., Grzech, A., Świątek, J. (Eds.) Information Systems Architecture and Technology: Proceedings of 36th International Conference on Information Systems Architecture and Technology – ISAT 2015, Springer series: Advances in Intellignet Systems and Computing, vol. 432 (2015)Google Scholar
  4. 4.
    Waris, M.M., Sanin, C., Szczerbicki, E.: Framework for Product Innovation Using SOEKS and Decisional DNA, In: Nguyen, N.T, Trawinski, B., Fujita, H., Hong, T.P. (eds.) Intelligent Information and Database Systems. ACIIDS 2016, Part I, LNAI 9621, pp. 1–10 (2016)Google Scholar
  5. 5.
    Waris, M.M., Sanin, C., Szczerbicki, E.: Toward smart innovation engineering: decisional DNA-based conceptual approach. Cybern. Syst. 47(1–2), 149–159 (2016)CrossRefGoogle Scholar
  6. 6.
    O’Sullivan, D., Dooley, L.: Applying Innovation. Sage Publications (2008)Google Scholar
  7. 7.
    Frishammar, J.: Managing information in new product development: a literature review. Int. J. Innov. Technol. Manage. 2(3), 259–275 (2005)CrossRefGoogle Scholar
  8. 8.
    Smith, P.G., Reinertsen, D.G.: Developing Products in Half the Time, 2nd edn. Wiley (1998)Google Scholar
  9. 9.
    Capello, R.: Knowledge, innovation, and regional performance: toward smart innovation policies introductory remark to the special issue. Growth Change 44(2), 185–194 (2013)Google Scholar
  10. 10.
    Rampino, L.: The innovation pyramid: a categorization of the innovation phenomenon in the product-design field. Int. J. Design 5(1), 3–16 (2011)Google Scholar
  11. 11.
    Sanin, C., Szczerbicki, E.: Towards the construction of decisional DNA: a set of experience knowledge structure java class within an ontology system. Cybern. Syst. 38, 859–878 (2007)CrossRefzbMATHGoogle Scholar
  12. 12.
    Sanin, C., Toro, C., Haoxi, Z., Sanchez, E., Szczerbicki, E., Carrasco, E., Peng, W., Mancilla-Amaya, L.: Decisional DNA: a multi-technology shareable knowledge structure for decisional experience. Neurocomputing 88, 42–53 (2012)CrossRefGoogle Scholar
  13. 13.
    Sanin, C., Szczerbicki, E.: Set of experience: a knowledge structure for formal decision events. Found. Control Manage. Sci. 3, 95–113 (2005)Google Scholar
  14. 14.
    Shafiq, S.I., Sanin, C., Szczerbicki, E.: Set of experience knowledge structure (SOEKS) and decisional DNA (DDNA): past, present and future. Cybern. Syst. 45(2), 200–215 (2014)CrossRefGoogle Scholar
  15. 15.
    Herstatt, C., von Hippel, E.: From experience: Developing new product concepts via the lead user method: a case study in a\low-tech” field. J. Prod. Innovat. Manag. 9(3), 213–221 (1992)CrossRefGoogle Scholar
  16. 16.
    Dolan, R.J., Matthews, J.M.: Maximizing the utility of customer product testing: beta test design and management. J. Prod. Innovat. Manag. 10(4), 318–330 (1993)CrossRefGoogle Scholar
  17. 17.
    Ciccantelli, S., Magidson, J.: From experience: consumer idealized design: involving consumers in the product development process. J. Prod. Innovat. Manag. 10(4), 341–347 (1993)CrossRefGoogle Scholar
  18. 18.
    Piller, F.T., Walcher, D.: Toolkits for idea competitions: a novel method to integrate users in new product development. R&D Manage. 36(3), 307–318 (2006)CrossRefGoogle Scholar
  19. 19.
    Bryant, C.R., Stone, R.B., Greer, J.L., McAdams, D.A., Kurtoglu, T., Campbell, M.I.: A function-based component ontology for systems design. In: International Conference on Engineering Design. Paris, France, 28–31 Aug 2007Google Scholar
  20. 20.
    Kurtoglu, T., Campbell, M.I., Bryant, C.R., Stone, R.B., McAdams, D.A.: Deriving a component basis for computational functional synthesis. In: Proceedings of the International Conference on Engineering Design, Melbourne, Australia, 15–18 Aug 2005Google Scholar
  21. 21.
    Shafiq, S.I., Sanin, C., Szczerbicki, E., Toro, C.: Virtual engineering objects/virtual engineering processes: a specialized form of cyber physical systems and Industry 4.0. Procedia Comput. Sci. 60, 1146–1155 (2015)CrossRefGoogle Scholar
  22. 22.
    Shafiq, S.I., Sanin, C., Toro, C., Szczerbicki, E.: Virtual engineering (VEO): towards experience-based design and manufacturing for Industry 4.0. Cybern. Syst. 46, 35–50 (2015)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Mohammad Maqbool Waris
    • 1
    Email author
  • Cesar Sanin
    • 1
  • Edward Szczerbicki
    • 2
  1. 1.The University of NewcastleCallaghanAustralia
  2. 2.Gdansk University of TechnologyGdanskPoland

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