Hostname: page-component-77c89778f8-5wvtr Total loading time: 0 Render date: 2024-07-19T07:32:22.691Z Has data issue: false hasContentIssue false
  • English
  • Français

THE CHALLENGING COMBINATION OF AGILITY AND CONVERGENCE IN HYBRID PRODUCT DEVELOPMENT PROCESSES: AN EMPIRICAL ANALYSIS OF STANFORD'S ME310 PROCESS MODEL

Published online by Cambridge University Press:  27 July 2021

Frank Koppenhagen ,
Tim Blümel ,
Tobias Held ,
Christoph Wecht  and
Paul Davin Kollmer
Frank Koppenhagen*
Affiliation:
Hamburg University of Applied Sciences
Tim Blümel
Affiliation:
University of Stuttgart
Tobias Held
Affiliation:
Hamburg University of Applied Sciences
Christoph Wecht
Affiliation:
New Design University St. Pölten
Paul Davin Kollmer
Affiliation:
University of Hamburg
*
Koppenhagen, Frank, Hochschule für Angewandte Wissenschaften Hamburg, Maschinenbau und Produktion, Germany, frank.koppenhagen@haw-hamburg.de

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.

Combining agility and convergence in the development of physical products is a major challenge. Rooted in a design thinking approach, Stanford's ME310 process model attempts to resolve the conflicting priorities of these two design principles. To investigate how successful Stanford's hybrid process model is in doing so, we have used a qualitative case study approach. Our paper begins by outlining this process model's fundamental principles in terms of engineering design methodology. Subsequently, we present the results of our empirical analysis, which tracks the coevolution of problem and solution space by meticulously examining all prototype paths in ten of Stanford's ME310 student projects. We have discovered that convergence during solution finding does not correspond to the process model's theoretical specifications. Even in the phase of the final prototype, both the technical concept and the underlying problem formulation changed frequently. Further research should focus on combining the prototype-based ME310 approach with methods from systems engineering which allow for a more comprehensive theoretical exploration of the solution space. This could lead to improved convergence during solution development.

Keywords

Design engineeringDesign methodologyCase studyDesign thinkingAgile product development
Type
Article
Information
Proceedings of the Design Society , Volume 1: ICED21 , August 2021 , pp. 2991 - 3000
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), 2021. Published by Cambridge University Press

References

Brereton, M. and McGarry, B. (2000), “An Observational Study of How Objects Support Engineering Design Thinking and Communication: Implications for the design of tangible media”, In: Turner, T. and Szwillus, G. (Eds.), Proceedings of the SIGCHI conference on Human Factors in Computing Systems, The Hague, The Netherlands, 01.-06.04.2000, pp. 217–224. https://doi.org/10.1145/332040.332434CrossRefGoogle Scholar
Brown, T. (2008), “Design Thinking”, Harvard Business Review, Vol. 86 No. 6, pp. 84–92.Google ScholarPubMed
Bushnell, T., Steber, S., Matta, A., Cutkosky, M. and Leifer, L. (2013), “Using a “Dark Horse” Prototype to manage innovative Teams”, In: Fernandes, A.A., Natal Jorge, R.M., Patrício, L. and Medeiros, A. (Eds.), 3rd Int. Conf. on Integration of Design, Engineering & Management for Innovation, Polo, Portugal, 04.-06.09.2013. https://doi.org/10.13140/2.1.2361.7602CrossRefGoogle Scholar
Cooper, R.G. and Sommer, A.F. (2016), “The Agile-Stage-Gate Hybrid Model: A Promising New Approach and a New Research Opportunity”, Journal of Product Innovation Management, Vol. 33 No. 5, pp. 513–526. https://doi.org/10.1111/jpim.12314CrossRefGoogle Scholar
Domingo, L., Moore, D., Sirkin, D., Toye, G., Leifer, L. and Cutkosky, M. (2020), “Strategic Prototyping to learn in Stanford Universitýs ME310 Design Innovation Course”, In: Marjanović, D., Storga, M., Pavković, N. and Bojčetić, N. (Eds.), DS 102: Proceedings of the DESIGN 2020 16th International Design Conference, held online, 26.-29.10.2020, Cambridge University Press, Cambridge, UK, pp. 1687–1696. https://doi.org/10.1017/dsd.2020.176Google Scholar
Dorst, K. and Cross, N. (2001), “Creativity in the design process: co-evolution of problem–solution”, Design Studies, Vol. 22 No. 5, pp. 425–437. https://doi.org/10.1016/S0142-694X(01)00009-6CrossRefGoogle Scholar
Gericke, K., Beinke, C., Gemmer, P. and Blessing, L. (2010), “Entwicklungsmethodik nach Pahl Beitz und Design Thinking. Vergleich und Einordnung”, In: Krause, D., Paetzold, K. and Wartzack, S. (Eds.), DFX 2010: Proceedings of the 21st Symposium on Design for X, Buchholz, Hamburg, Deutschland, 23.-24.09.2010, pp. 117–130.Google Scholar
Haberfellner, R., Weck, O.L. de Fricke, E. and Vössner, S. (2019), Systems Engineering: Fundamentals and Applications, Springer Nature, Cham, Switzerland. https://doi.org/10.1007/978-3-030-13431-0CrossRefGoogle Scholar
Kenyon, D., Cutkowsky, M. and Leifer, L. (n.d.), ME310 ABC Course Reader, Stanford University, Stanford, California, USA.Google Scholar
Koppenhagen, F. (2004), Systematische Ableitung modularer Produktarchitekturen: Komplexitätsreduzierung in der Konzeptphase, Shaker, Aachen.Google Scholar
Leifer, L.J. and Steinert, M. (2011), “Dancing with ambiguity: Causality behavior, design thinking, and triple-loop-learning”, Information Knowledge Systems Management, Vol. 10 No. 1-4, pp. 151–173. https://doi.org/10.3233/IKS-2012-0191CrossRefGoogle Scholar
Luchs, M.G., Swan, K.S. and Griffin, A. (Eds.) (2016), Design thinking: New product development essentials from the PDMA, Wiley, Hoboken, New Jersey.Google Scholar
Pahl, G., Beitz, W., Feldhusen, J. and Grote, K.-H. (2007), Engineering design: A systematic approach, 3. ed., Springer, London.10.1007/978-1-84628-319-2CrossRefGoogle Scholar
Rittel, H.W.J. and Webber, M.M. (1973), “Dilemmas in a General Theory of Planning”, Policy Sciences, Vol. 4 No. 2, pp. 155–169.10.1007/BF01405730CrossRefGoogle Scholar
Schüttoff, M., Herrmann, T., Roth, D. and Binz, H. (2019), “Analyse und Beurteilung der unterschiedlichen Einsatzzwecke und Anwendungsgrenzen von Design Thinking”, In: Binz, H., Bertsche, B., Bauer, W. and Riedel, O. (Eds.), Stuttgarter Symposium für Produktentwicklung SSP 2019: Agilität und kognitives Engineering, Stuttgart, 16.05.2019, pp. 193–202.Google Scholar
Sobek, D.K. II, Ward, A.C. and Liker, J.K. (1999), “Toyotás Principles of Set-Based Concurrent Engineering”, Sloan Management Review, Vol. 40 No. 2, pp. 67–83.Google Scholar
Viswanathan, V.K. and Linsey, J.S. (2012), “Physical Models and Design Thinking: A Study of Functionality, Novelty and Variety of Ideas”, Journal of Mechanical Design, Vol. 134 No. 9, pp. 1–13. https://doi.org/10.1115/1.4007148CrossRefGoogle Scholar