Hostname: page-component-76fb5796d-25wd4 Total loading time: 0 Render date: 2024-04-26T10:59:32.975Z Has data issue: false hasContentIssue false
  • English
  • Français

Connecting Functional and Geometrical Representations to Support the Evaluation of Design Alternatives for Aerospace Components

Part of: Design Methods and Tools

Published online by Cambridge University Press:  26 July 2019

Jakob R. Müller ,
Massimo Panarotto  and
Ola Isaksson

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Novel product concepts are often down-selected in favour of the incremental development of available designs. This can be attributed to the fact that for the development of a new product, simulations and analysis based on high-fidelity CAD models are required, which are expensive to create. To solve this problem, the use of a function model (FM) as intermediate step between ideation and embodiment is suggested.

The approach has been examined in a case study with an aerospace company for the development of a turbine rear assembly, using multiple workshops and interviews with practitioners from the company. A multitude of novel solutions, even extending the functionality of the legacy design, were captured. The FM approach proved to support the representation, analysis, and configuration of 102 different concepts. Although supported by the FM model, the embodiment still showed to be a bottle neck for further development. The subsequent interviews with practitioners showed that the benefits of the approach were seen, but experienced as too complex.

Further work will concern a more systematic connection between the FM and CAD model, in order to automate of the embodiment process.

Keywords

Functional modellingDesign engineeringProduct modelling / modelsComputer Aided Design (CAD)
Type
Article
Information
Proceedings of the Design Society: International Conference on Engineering Design , Volume 1 , Issue 1 , July 2019 , pp. 1423 - 1432
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s) 2019

References

Aberdeen, T. (2013), Yin, R. K. (2009), “Case study research: Design and methods”, (4th ed.). Sage, Thousand Oaks, CA. The Canadian Journal of Action Research, Vol. 14 No. 1, pp. 69–71.Google Scholar
Al-Ashaab, A., et al. (2013), “The transformation of product development process into lean environment using set-based concurrent engineering: A case study from an aerospace industry”, Concurrent Engineering, Vol. 21 No. 4, pp. 268–285. http://doi.org/10.1177/1063293X13495220.Google Scholar
Schachinger, P. and Johannesson, H. (2000), “Computer modelling of design specifications”, Journal of engineering design. Taylor & Francis, Vol. 11 No. 4, pp. 317–329. http://doi.org/10.1080/0954482001000935.Google Scholar
Avison, D.E., Lau, F., Myers, M.D. and Nielsen, P.A. (1999), “Action Research”, Communication of the ACM, Vol. 42 No. 1, pp. 94–97. http://doi.org/10.1177/1476750308097028.Google Scholar
Bertoni, M. and Bertoni, A. (2016), “Models for value-driven engineering design”, Proceedings of International Design Conference, DESIGN, DS 84, pp. 1195–1204.Google Scholar
Blessing, L. T. M. and Chakrabarti, A. (2002), “DRM, a design research methodology”, Proceedings of Les Sciences de la Conception. Springer. http://doi.org/10.1007/978-1-84882-587-1.Google Scholar
Boujut, J. F. and Léon, J. C. (2005), Design Process Improvement: A Review of Current Practice. http://doi.org/10.1007/978-1-84628-061-0.Google Scholar
Brun, J., Masson, P. Le and Weil, B. (2018), “Getting Inspiration or Creating Inspiration?”, The Role of Knowledge Structures in Idea Generation, in Design 2018, pp. 1793–1804. https://doi.org/10.21278/idc.2018.0196.Google Scholar
Eckert, C. M., et al. (2017), “On the integration of product and process models in engineering design”, Design Science. http://doi.org/10.1017/dsj.2017.2.Google Scholar
Eisenbart, B., Gericke, K., Blessing, L. and McAloone, T. C. (2017), “A DSM-based framework for integrated function modelling: concept, application and evaluation”, Research in Engineering Design. Springer, London, Vol. 28 No. 1, pp. 25–51. http://doi.org/10.1007/s00163-016-0228-1.Google Scholar
Gero, J. S. and Kan, J. W. T. (2016), Experimental Design Research. http://doi.org/10.1007/978-3-319-33781-4.Google Scholar
Gero, J.S. and Kannengiesser, U. (2004), “The situated function-behaviour-structure framework”, Design Studies, Vol. 25 No. 4, pp. 373–391. http://doi.org/10.1016/j.destud.2003.10.010.Google Scholar
Heikkinen, T., Johansson, J. and Elgh, F. (2018), “Review of CAD-model capabilities and restrictions for multidisciplinary use”, Computer-Aided Design and Applications, Vol. 4360 No. January, pp. 1–11. http://doi.org/10.1080/16864360.2017.1419639.Google Scholar
Helms, B. and Shea, K. (2012), “Computational Synthesis of Product Architectures Based on Object-Oriented Graph Grammars”, Journal of Mechanical Design, Vol. 134 No. 2, p. 021008. http://doi.org/10.1115/1.4005592.Google Scholar
Isaksson, O., Bertoni, A., Levandowski, C. E., Müller, J. R., Wiklund, D. and Johannesson, H. (2016), “Virtual contextual validation of technologies and methods for product development”, in Proceedings of International Design Conference, DESIGN, pp. 669–678.Google Scholar
Jin, Y. and Li, W. (2007), “Design Concept Generation: A Hierarchical Coevolutionary Approach”, Journal of Mechanical Design, Vol. 129 No. 10, p. 1012. http://doi.org/10.1115/1.2757190.Google Scholar
Lawson, B. and Samson, D. (2001), “Developing Innovation Capability in Organisations: a Dynamic Capabilities Approach”, International Journal of Innovation Management, Vol. 05 No. 03, pp. 377–400. http://doi.org/10.1142/S1363919601000427.Google Scholar
Levandowski, C.E., Raudberget, D. and Johannesson, H. (2014), “Set-Based Concurrent Engineering for early phases in platform development”, Advances in Transdisciplinary Engineering, pp. 564–576. http://doi.org/10.3233/978-1-61499-440-4-564.Google Scholar
Miles, M. B., Huberman, A. M. and Saldana, J. (2014), Qualitative Data Analysis: A Methods Sourcebook. 3rd edn. Sage Publ Inc. http://doi.org/10.1016/0149-7189(96)88232-2.Google Scholar
Pahl, G., Beitz, W., Feldhusen, J. and Grote, K.-H. (2013), Konstruktionslehre: Grundlagen Erfolgreicher Produkteentwicklung; Methoden und Anwendung. 8th edn. Springer, Berlin Heidelberg.Google Scholar
Rigger, E. and Vosgien, T. (2018), “Design Automation State of Practice - Potential and Opportunities”, Design 2018, pp. 441–452. https://doi.org/10.21278/idc.2018.0537.Google Scholar
Sandberg, M., Tyapin, I., Kokkolaras, M., Isaksson, O., Aidanpää, J.O. and Larsson, T. (2011), “A Knowledge-based master-model approach with application to rotating machinery design”, Concurrent Engineering Research and Applications, Vol. 19 No. 4, pp. 295–305. http://doi.org/10.1177/1063293X11424511.Google Scholar
Schachinger, P. and Johannesson, H.H. (2000), “Computer modelling of design specifications”, Journal of engineering design. Taylor & Francis, Vol. 11 No. 4, pp. 317–329. http://doi.org/10.1080/0954482001000935.Google Scholar
Shea, K., Aish, R. and Gourtovaia, M. (2005), “Towards integrated performance-driven generative design tools”, Automation in Construction, Vol. 14 No. 2 SPEC. ISS., pp. 253–264. http://doi.org/10.1016/j.autcon.2004.07.002.Google Scholar
Sobek Ii, D.K., Ward, A.C. and Liker, J.K. (1999), “Toyota's principles of set-based concurrent engineering”, MIT Sloan Management Review, Vol. 40 No. 2, pp. 67–83. doi: 3432.Google Scholar
Suh, N.P. (1990), The principles of design, Oxford University Press, New York.Google Scholar
Thomke, S. (2001), “Enlightened Experimentation : The New Imperative for Innovation”, Harvard Business Review, Vol. 79 No. 2, pp. 66–75. http://doi.org/10.4324/9780203895023.Google Scholar
Verhagen, W. J. C., Bermell-Garcia, P., van Dijk, R. E. C. and Curran, R. (2012), “A critical review of Knowledge-Based Engineering: An identification of research challenges”, Advanced Engineering Informatics. Elsevier Ltd, Vol. 26 No. 1, pp. 5–15. http://doi.org/10.1016/j.aei.2011.06.004.Google Scholar
Woodbury, R.F. and Burrow, A.L. (2006), “Whither design space?, AIE EDAM: Artificial Intelligence for Engineering Design”, Analysis, and Manufacturing, Vol. 20, pp. 63–82. http://doi.org/10.10170S0890060406060057.Google Scholar
Wyatt, D. F., Eckert, C. M. and Clarkson, P. J. (2009), “Design of Product Architectures in Incrementally Developed Complex Products”, in International Conference on Engineering Design ICED 09, pp. 167–178.Google Scholar