A Novel Approach to Product Lifecycle Management and Engineering Using Behavioural Models for the Conceptual Design Phase

Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 565)


This work builds upon a previous proposal for the use of the extended SAPPhIRE model of causality as a foundation for a PLM system, and more specifically the management of design data at the conceptual design phase. During the conceptual design phase, the product definition is in a state of flux as multiple iterations and options are considered until a suitable baseline design is developed. The role of PLM systems is to manage the people, processes and products involved in developing and sustaining a product in order to increase stakeholder satisfaction and product quality while reducing lifecycle costs. At the conceptual design stage, a balance must be struck between the freedom to iterate and the need to control the design process and capture relevant data.

Currently, PLM systems are not well suited for the support of the conceptual design stage due to their reliance on the product structure, as the unavoidable, significant design changes to the physical configuration in the early design stages make it difficult to maintain a coherent product definition. This paper presents a case study of the product data created during the conceptual design phase of the SpudNik-1 CubeSat. The results demonstrate the ability of the model to represent a variety of design data representing different subsystems at several levels of maturity. This could prove to be more consistent and easier to use for conceptual design and is one part of a larger goal of redesigning PLM systems for the support of the extended product lifecycle.


Conceptual design Behaviour Function Causal Satellite Nanosatellite Product lifecycle management Behavioural model 


  1. 1.
    Knoll, D., Fortin, C., Golkar, A.: Review of concurrent engineering design practice in the space sector: state of the art and future perspectives. In: 2018 IEEE International Systems Engineering Symposium (ISSE), Rome, Italy (2018)Google Scholar
  2. 2.
    Fortin, C., McSorley, G., Knoll, D., Golkar, A., Tsykunova, R.: Study of data structures and tools for the concurrent conceptual design of complex space systems. In: Ríos, J., Bernard, A., Bouras, A., Foufou, S. (eds.) PLM 2017. IAICT, vol. 517, pp. 601–611. Springer, Cham (2017). Scholar
  3. 3.
    Knoll, D., Golkar, A.: A coordination method for concurrent design and a collaboration tool for parametric system models. Concurr. Eng. 26(1), 5–21 (2017). Scholar
  4. 4.
    Vuletic, T., et al.: The challenges in computer supported conceptual engineering design. Comput. Ind. 95, 22–37 (2018). Scholar
  5. 5.
    Stark, J.: Product Lifecycle Management (Volume 1). DE. Springer, Cham (2015). Scholar
  6. 6.
    Torres, V.H., et al.: Approach to integrate product conceptual design information into a computer-aided design system. Concurr. Eng. 21(1), 27–38 (2013). Scholar
  7. 7.
    Regazzoni, D., Rizzi, C.: Conceptual design knowledge management in a PLM framework. In: 4th International Conference on Product Life Cycle Management (PLM 2007) (2007)Google Scholar
  8. 8.
    Chandrasegaran, S.K., et al.: The evolution, challenges, and future of knowledge representation in product design systems. Comput.-Aided Des. 45(2), 204–228 (2013). Scholar
  9. 9.
    Sundarsan, R., et al.: A product information modeling framework for product lifecycle management. Comput.-Aided Des. 37(13), 1399–1411 (2005). Scholar
  10. 10.
    Chakrabarti, A., et al.: A functional representation for aiding biomimetic and artificial inspiration of new ideas. Artif. Intell. Eng. Des. Anal. Manuf. 19(2), 113–132 (2005). Scholar
  11. 11.
    McSorley, G., Fortin, C., Huet, G.: Modified SAPPhIRE model as a framework for product lifecycle management. In: DS 77: Proceedings of the DESIGN 2014 13th International Design Conference, Dubrovnik, Croatia, pp. 1843–1852 (2014)Google Scholar
  12. 12.
    Hubka, V.: Principles of Engineering Design. Butterworth Scientific, London (1982)Google Scholar
  13. 13.
    Gero, J.S., Kannengiesser, U.: The situated function–behaviour–structure framework. Des. Stud. 25(4), 373–391 (2004)CrossRefGoogle Scholar
  14. 14.
    Umeda, Y., et al.: Supporting conceptual design based on the function-behavior-state modeler. Artif. Intell. Eng. Des. Anal. Manuf. 10(4), 275–288 (1996). Scholar
  15. 15.
    Jagtap, S.: Capture and structure of in-service information for engineering designers. University of Cambridge, Cambridge (2008)Google Scholar
  16. 16.
    Tsykunova, R.: Study of data structures, tools and processes to support concurrent conceptual design of space products. Skolkovo Institute of Science and Technology (2016)Google Scholar
  17. 17.
    Chakrabarti, A., Srinivasan, V.: SAPPhIRE–an approach to analysis and synthesis. In: ICED 2009: Proceedings of the 17th International Conference on Engineering Design, California, USA, pp. 417–428 (2009)Google Scholar
  18. 18.
    Munakata, R., et al.: CubeSat design specification. California Polytechnic State University, San Luis Obispo, California, 20 February 2014Google Scholar
  19. 19.
    NASA: NASA Systems Engineering Handbook. National Aeronautics and Space Administration (NASA), Washington, DC (2016)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2019

Authors and Affiliations

  1. 1.University of Prince Edward IslandCharlottetownCanada
  2. 2.Skoltech, Skolkovo Innovation CenterMoscowRussia

Personalised recommendations