Decisional DNA Based Framework for Representing Virtual Engineering Objects

  • Syed Imran Shafiq
  • Cesar Sanin
  • Edward Szczerbicki
  • Carlos Toro
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8397)


In this paper, we propose a frame-work to represent the Virtual Engineering Objects (VEO) utilizing Set of Knowledge Experience Structure (SOEKS) and Decisional DNA. A VEO will enable the discovery of new knowledge in a manufacturing unit and the generation of new rules that drive reasoning. The proposed VEO framework will not only be knowledge based representation but it will also have its associated experience embedded within it. This concept will evolve and discover implicit knowledge in industrial plant, which can be beneficial for the engineers and practitioners. A VEO will be a living representation of an object; capable of adding, storing, improving and sharing knowledge through experience, similar to an expert of that area.


Decisional DNA (DDNA) Set of Experience Knowledge Structure (SOEKS) Virtual Engineering Objects (VEO) 


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  1. 1.
    Verhagen, W.J.C., Garcia, P.B., Van Dijk, R.E.C., Curran, R.: A critical review of Knowledge-Based Engineering: An identification of research challenges. Advanced Engineering Informatics 26, 5–15 (2012)CrossRefGoogle Scholar
  2. 2.
    Baxter, D., Gao, J., Case, K., Harding, J., Young, R., Cochrane, S., Dani, S.: An engineering design knowledge reuse methodology using process modelling. International Journal of Research in Engineering Design 18, 37–48 (2007)CrossRefGoogle Scholar
  3. 3.
    Sanin, C., Szczerbicki, E.: Set of Experience: A Knowledge Structure for Formal Decision Events. Foundations of Control and Management Sciences 3, 95–113 (2005)Google Scholar
  4. 4.
    Sung, R.C.W., Ritchie, J.M., Lim, T., Kosmadoudi, Z.: Automated generation of engineering rationale, knowledge and intent representations during the product life cycle. Virtual Reality 16, 69–85 (2012)CrossRefGoogle Scholar
  5. 5.
    Sanin, C., Szczerbicki, E.: Towards the Construction of Decisional DNA: A Set of Experience Knowledge Structure Java Class within an Ontology System. Cybernetics and Systems 38, 859–878 (2007)CrossRefMATHGoogle Scholar
  6. 6.
    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
  7. 7.
    Sanin, C., Szczerbicki, E.: Extending Set of Experience Knowledge Structure into a Transportable Language extensible Markup Language. Cybernetics and Systems 37, 97–117 (2006)CrossRefGoogle Scholar
  8. 8.
    Sanín, C.: Smart Knowledge Management System, Thesis of Doctor of Philosophy Degree From The University of Newcastle Department Of Mechanical Engineering, Newcastle, Australia (2007)Google Scholar
  9. 9.
    Shafiq, S.I., Sanin, C., Szczerbicki, E., Toro, C.: Using Decisional DNA to Enhance Industrial and Manufacturing Design: Conceptual Approach. In: 34th International Conference on Information Systems Arhitecture and Technology, Szklarska Poreba, Poland, pp. 23–32. Wroclaw University of Technology (2013)Google Scholar
  10. 10.
    Davis, R., Shrobe, H., Szolovits, P.: What is a Knowledge Representation? AI Magazine 14, 17–33 (1993)Google Scholar
  11. 11.
    Toro, C., Sanín, C., Szczerbicki, E., Posada, J.: Reflexive Ontologies: Enhancing Ontologies With Self-Contained Queries. Cybernetics and Systems 39, 171–189 (2008)CrossRefMATHGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Syed Imran Shafiq
    • 1
  • Cesar Sanin
    • 1
  • Edward Szczerbicki
    • 2
  • Carlos Toro
    • 3
  1. 1.The University of NewcastleCallaghanAustralia
  2. 2.Gdansk University of TechnologyGdanskPoland
  3. 3.Vicomtech-IK4San SebastianSpain

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