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Abstract

Data generated throughout the product development lifecycle is often unused to its full potential, particularly for improving the engineering design process. Although Knowledge-Based Engineering (KBE) approaches are not new, the Digital Twin (DT) concept is giving new momentum to it, fostering the availability of lifecycle data with the potential to be transformed into new design knowledge. This approach creates an opportunity to research how digital infrastructures and new knowledge-based processes can be articulated to implement more effective KBE approaches. This paper describes how combining a DT-based Digital Platform (DP) with new engineering design processes can improve Knowledge Management (KM) in product design. A case study of a company in the energy sector highlights the challenges and benefits of this approach.

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References

  1. Abburu, S., Berre, A.J., Jacoby, M., Roman, D., Stojanovic, L., Stojanovic, N.: Cognitive digital twins for the process industry. In: Proceedings of the Twelfth International Conference on Advanced Cognitive Technologies and Applications (COGNITIVE 2020), Nice, France, pp. 25–29 (2020)

    Google Scholar 

  2. Anderl, R.: Industrie 4.0-advanced engineering of smart products and smart production. In: Proceedings of International Seminar on High Technology, vol. 19 (2014)

    Google Scholar 

  3. Azevedo, M.: Knowledge-based engineering supported by the digital twin: the case of the power transformer at Efacec. Master’s thesis, Faculty of Engineering of the University of Porto (2020)

    Google Scholar 

  4. Bartevyan, L.: Industry 4.0 - Summary report (2015)

    Google Scholar 

  5. Cooper, D., LaRocca, G.: Knowledge-based techniques for developing engineering applications in the 21st century. In: 7th AIAA ATIO Conference 2nd CEIAT International Conference on Innovation and Integration in Aero Sciences, 17th LTA Systems Technology Conference; Followed by 2nd TEOS Forum. Aviation Technology, Integration, and Operations (ATIO) Conferences, American Institute of Aeronautics and Astronautics, September 2007. https://doi.org/10.2514/6.2007-7711

  6. Curran, R., Verhagen, W.J., Van Tooren, M.J., Van Der Laan, T.H.: A multidisciplinary implementation methodology for knowledge based engineering: KNOMAD. Expert Syst. Appl. 37, 7336–7350 (2010). https://doi.org/10.1016/j.eswa.2010.04.027

    Article  Google Scholar 

  7. Gawer, A., Cusumano, M.A.: Platform Leadership: How Intel, Microsoft, and Cisco Drive Industry Innovation, vol. 5. Harvard Business School Press, Boston (2002)

    Google Scholar 

  8. Girard, J., Girard, J.: Defining knowledge management: toward an applied compendium. Online J. Appl. Knowl. Manag. 3(1), 1–20 (2015)

    Google Scholar 

  9. Hein, A., et al.: Digital platform ecosystems. Electron. Mark. 30(1), 87–98 (2020). https://doi.org/10.1007/s12525-019-00377-4

    Article  Google Scholar 

  10. Lu, J., Zheng, X., Gharaei, A., Kalaboukas, K., Kiritsis, D.: Cognitive twins for supporting decision-makings of internet of things systems. In: Wang, L., Majstorovic, V.D., Mourtzis, D., Carpanzano, E., Moroni, G., Galantucci, L.M. (eds.) Proceedings of 5th International Conference on the Industry 4.0 Model for Advanced Manufacturing. LNME, pp. 105–115. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-46212-3_7

    Chapter  Google Scholar 

  11. Pagoropoulos, A., Maier, A., McAloone, T.C.: Assessing transformational change from institutionalising digital capabilities on implementation and development of Product-Service Systems: Learnings from the maritime industry. J. Clean. Prod. 166, 369–380 (2017). https://doi.org/10.1016/j.jclepro.2017.08.019

    Article  Google Scholar 

  12. Pauli, T., Fielt, E., Matzner, M.: Digital Industrial Platforms. Bus. Inf. Syst. Eng. 63(2), 181–190 (2021). https://doi.org/10.1007/s12599-020-00681-w

    Article  Google Scholar 

  13. Rebentisch, E., Rhodes, D.H., Soares, A.L., Zimmerman, R., Tavares, S.: The digital twin as an enabler of digital transformation: a sociotechnical perspective. In: 2021 IEEE 19th International Conference on Industrial Informatics (INDIN), pp. 1–6. Institute of Electrical and Electronics Engineers (IEEE), October 2021. https://doi.org/10.1109/indin45523.2021.9557455

  14. Reddy, E.J., Sridhar, C.N.V., Rangadu, V.P.: Knowledge based engineering: notion, approaches and future trends. Am. J. Intell. Syst. 5(1), 1–17 (2015). https://doi.org/10.5923/j.ajis.20150501.01

  15. Rocca, G.L.: Knowledge based engineering: between AI and CAD. Review of a language based technology to support engineering design. Adv. Eng. Inform. 26(2), 159–179 (2012). https://doi.org/10.1016/j.aei.2012.02.002

  16. Rosenfeld, L.W.: Solid modeling and knowledge-based engineering. In: Handbook of Solid Modeling, pp. 91–911. McGraw-Hill, Inc., USA, June 1995

    Google Scholar 

  17. Sandberg, M., Boart, P., Larsson, T.: Functional product life-cycle simulation model for cost estimation in conceptual design of jet engine components. Concurr. Eng. 13(4), 331–342 (2005). https://doi.org/10.1177/1063293X05060136

    Article  Google Scholar 

  18. Schreiber, G., et al.: Knowledge Engineering and Management. The MIT Press (1999). https://doi.org/10.7551/mitpress/4073.001.0001

  19. Tao, F., et al.: Digital twin and its potential application exploration. Jisuanji Jicheng Zhizao Xitong/Comput. Integr. Manuf. Syst. CIMS 24(1), 1–18 (2018). https://doi.org/10.13196/j.cims.2018.01.001

  20. Tiwana, A.: Evolutionary competition in platform ecosystems. Inf. Syst. Res., 266–281 (2015). https://doi.org/10.1287/isre.2015.0573

  21. Yin, R.K.: Case Study Research: Design and Methods. SAGE Publications Inc, Thousand Oaks (2008)

    Google Scholar 

  22. Zack, M.H.: Developing a knowledge strategy. Calif. Manage. Rev. 41(3), 125–145 (1999). https://doi.org/10.2307/41166000

    Article  Google Scholar 

  23. Zheng, X., Lu, J., Kiritsis, D.: The emergence of cognitive digital twin: vision, challenges and opportunities. Int. J. Prod. Res. (2021). https://doi.org/10.1080/00207543.2021.2014591

    Article  Google Scholar 

  24. Zhuang, C., Liu, J., Xiong, H.: Digital twin-based smart production management and control framework for the complex product assembly shop-floor. Int. J. Adv. Manuf. Technol. 96(1–4), 1149–1163 (2018). https://doi.org/10.1007/s00170-018-1617-6

    Article  Google Scholar 

  25. Zhuang, C., Liu, J., Xiong, H., Ding, X., Liu, S., Wen, G.: Connotation, architecture and trends of product digital twin. Comput. Integr. Manuf. Syst 23(4), 53–768 (2017). https://doi.org/10.13196/j.cims.2017.04.010

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Acknowledgments

The project TRF4p0-Transformer4.0 leading to this work is co-financed by the ERDF, through COMPETE-POCI and by the Foundation for Science and Technology under the MIT Portugal Program under POCI-01-0247-FEDER-045926. The second author was additionally funded by the Ph.D. Grant UI/BD/152565/2022 from the Portuguese funding agency, FCT-Fundação para a Ciência e a Tecnologia.

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Correspondence to Sthefan Berwanger , Henrique Diogo Silva , António Lucas Soares or Cristiano Coutinho .

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Berwanger, S., Silva, H.D., Soares, A.L., Coutinho, C. (2024). Knowledge-Based Engineering Design Supported by a Digital Twin Platform. In: Danjou, C., Harik, R., Nyffenegger, F., Rivest, L., Bouras, A. (eds) Product Lifecycle Management. Leveraging Digital Twins, Circular Economy, and Knowledge Management for Sustainable Innovation. PLM 2023. IFIP Advances in Information and Communication Technology, vol 701. Springer, Cham. https://doi.org/10.1007/978-3-031-62578-7_23

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  • DOI: https://doi.org/10.1007/978-3-031-62578-7_23

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