Hostname: page-component-76fb5796d-r6qrq Total loading time: 0 Render date: 2024-04-25T21:39:09.315Z Has data issue: false hasContentIssue false
  • English
  • Français

Applying Engineering Design Ontology for Content Analysis of Team Conceptual Design Activity

Part of: Knowledge-based Engineering

Published online by Cambridge University Press:  26 July 2019

Tomislav Martinec ,
Stanko Škec ,
Jelena Šklebar  and
Mario Štorga
Tomislav Martinec*
Affiliation:
University of Zagreb;
Stanko Škec
Affiliation:
University of Zagreb; Technical University of Denmark (DTU);
Jelena Šklebar
Affiliation:
University of Zagreb;
Mario Štorga
Affiliation:
University of Zagreb; Luleå University of Technology
*
Contact: Martinec, Tomislav, University of Zagreb, FSB, Department of Design, Croatia, tomislav.martinec@fsb.hr

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.

Studies of design activity have been dominantly reporting on different aspects of the design process, rather than the content of designing. The aim of the presented research has been the development and application of an approach for a fine-grain analysis of the design content communicated between designers during the team conceptual design activities. The proposed approach builds on an engineering design ontology as a foundation for the content categorisation. Two teams have been studied using the protocol analysis method. The coded protocols offered fine-grain descriptions of the content communicated at different points in the design session and enabled comparison of teams’ approaches and deriving some generalisable findings. For example, it has been shown that both teams focused primarily on the use of the developed product and the operands within the technical process, in order to generate new technical solutions and initial component design. Moreover, teams exhibit progress from abstract to concrete solutions as the sessions proceeded and focused on the functional requirements towards the end of the sessions.

Keywords

Content analysisTeamworkOntologiesProtocol analysisConceptual design
Type
Article
Information
Proceedings of the Design Society: International Conference on Engineering Design , Volume 1 , Issue 1 , July 2019 , pp. 2467 - 2476
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

Ahmed, S. and Štorga, M. (2009), “Merged ontology for engineering design: Contrasting empirical and theoretical approaches to develop engineering ontologies”, Artificial Intelligence for Engineering Design, Analysis and Manufacturing, Vol. 23 No. 4, pp. 391–407. https://doi.org/10.1017/S0890060409000146Google Scholar
Andreasen, M.M., Hansen, C.T. and Cash, P. (2015), Conceptual Design: Interpretations, Mindset and Models, Conceptual Design: Interpretations, Mindset and Models, Springer. https://doi.org/10.1007/978-3-319-19839-2Google Scholar
Cash, P. and Štorga, M. (2015), “Multifaceted assessment of ideation: using networks to link ideation and design activity”, Journal of Engineering Design, Vol. 26 No. 10-12, pp. 391–415. https://doi.org/10.1080/09544828.2015.1070813Google Scholar
Chiu, M.-L. (2002), “An organizational view of design communication in design collaboration”, Design Studies, Vol. 23 No. 2, pp. 187–210. https://doi.org/10.1016/S0142-694X(01)00019-9Google Scholar
Cross, N. (2001), “Design cognition: results from protocol and other empirical studies of design activity”, In: Newstatter, W. and McCracken, M. (Eds.), Design Knowing and Learning: Cognition in Design Education, Elsevier, pp. 79–103.Google Scholar
Danielescu, A., Dinar, M., MacLellan, C., Shah, J. and Langley, P. (2012), “The Structure of Creative Design: What Problem Maps Can Tell Us About Problem Formulation and Creative Designers”, ASME 2012 International Design Engineering Technical Conferences (IDETC) & Computers and Information in Engineering Conference (CIE), Chicago, IL, USA, August 12-15, 2012, pp. 437–446. https://doi.org/10.1115/DETC2012-70325.Google Scholar
Dorst, K. and Dijkhuis, J. (1995), “Comparing paradigms for describing design activity”, Design Studies, Vol. 16 No. 2, pp. 261–274. https://doi.org/10.1016/0142-694X(94)00012-3Google Scholar
Ensici, A. and Badke-Schaub, P. (2011), “Information behavior in multidisciplinary design teams”, 18th International Conference on Engineering Design (ICED 11), , Denmark, August 15-19, pp. 414–423.Google Scholar
Frankenberger, E. and Auer, P. (1997), “Standardized observation of team-work in design”, Research in Engineering Design, Vol. 9 No. 1, pp. 1–9. https://doi.org/10.1007/BF01607053Google Scholar
Gero, J.S. and Song, T. (2017), “The Decomposition/Recomposition Design Behavior of Student and Professional Engineers”, 2017 ASEE Annual Conference & Exposition, Columbus, OH, USA, June 25-28.Google Scholar
Goldschmidt, G. (2014), Linkography: Unfolding the Design Process, The MIT Press, Cambridge, MA.Google Scholar
Goldschmidt, G. (2016), “Linkographic Evidence for Concurrent Divergent and Convergent Thinking in Creative Design”, Creativity Research Journal, Vol. 28 No. 2, pp. 115–122. https://doi.org/10.1080/10400419.2016.1162497Google Scholar
Hubka, V. and Eder, E. (1992), Engineering Design: General Procedural Model of Engineering Design, Heurista, Zürich.Google Scholar
Huet, G., Culley, S.J., McMahon, C.A. and Fortin, C. (2007), “Making sense of engineering design review activities”, Artificial Intelligence for Engineering Design, Analysis and Manufacturing, Vol. 21 No. 3, pp. 243–266. https://doi.org/10.1017/S0890060407000261Google Scholar
Kan, J.W.T. and Gero, J.S. (2017), Quantitative Methods for Studying Design Protocols, Quantitative Methods for Studying Design Protocols, Springer. https://doi.org/10.1007/978-94-024-0984-0Google Scholar
Kleinsmann, M.S. (2006), Understanding Collaborative Design, PhD Thesis, TU Delft.Google Scholar
Kuusela, H. and Paul, P. (2000), “A comparison of concurrent and retrospective verbal protocol analysis”, American Journal of Psychology, Vol. 113 No. 3, pp. 387–404. https://doi.org/10.2307/1423365Google Scholar
Li, Z. and Ramani, K. (2007), “Ontology-based design information extraction and retrieval”, Artificial Intelligence for Engineering Design, Analysis and Manufacturing, Vol. 21 No. 2, pp. 137–154. https://doi.org/10.1017/S0890060407070199Google Scholar
Liikkanen, L.A. and Perttula, M. (2009), “Exploring problem decomposition in conceptual design among novice designers”, Design Studies, Vol. 30 No. 1, pp. 38–59. https://doi.org/10.1016/j.destud.2008.07.003Google Scholar
Martinec, T., Škec, S., Savšek, T. and Perišić, M.M. (2017), “Work Sampling for the production development: A case study of a supplier in European Automotive Industry”, Advances in Production Engineering and Management, Vol. 12 No. 4, pp. 375–387. https://doi.org/10.14743/apem2017.4.265Google Scholar
Pourmohamadi, M. and Gero, J.S. (2011), “LINKOgrapher: An Analysis Tool to Study Design Protocols Based on FBS Coding Scheme”, 18th International Conference on Engineering Design (ICED 11), Lyngby/Copenhagen, Denmark, August 15-19, pp. 294–303.Google Scholar
Sim, S.K. and Duffy, A.H.B. (2003), “Towards an ontology of generic engineering design activities”, Research in Engineering Design, Vol. 14 No. 4, pp. 200–223. https://doi.org/10.1007/s00163-003-0037-1Google Scholar
Sonalkar, N., Mabogunje, A. and Leifer, L. (2013), “Developing a visual representation to characterize moment-to-moment concept generation in design teams”, International Journal of Design Creativity and Innovation, Vol. 1 No. 2, pp. 93–108. https://doi.org/10.1080/21650349.2013.773117Google Scholar
Stempfle, J. and Badke-Schaub, P. (2002), “Thinking in design teams - An analysis of team communication”, Design Studies, Vol. 23 No. 5, pp. 473–496. https://doi.org/10.1016/S0142-694X(02)00004-2Google Scholar
Škec, S., Cash, P. and Štorga, M. (2017), “A dynamic approach to real-time performance measurement in design projects”, Journal of Engineering Design, Vol. 28 No. 4, pp. 255–286. https://doi.org/10.1080/09544828.2017.1303665Google Scholar
Toh, C.A. and Miller, S.R. (2015), “How engineering teams select design concepts: A view through the lens of creativity”, Design Studies, Vol. 38, pp. 111–138. https://doi.org/10.1016/j.destud.2015.03.001Google Scholar
Valkenburg, A.C. (2000), The Reflective Practice in Product Design Teams, PhD Thesis, TU Delft.Google Scholar
Vuletic, T., Duffy, A., Hay, L., McTeague, C., Pidgeon, L. and Grealy, M. (2018), “The challenges in computer supported conceptual engineering design”, Computers in Industry, Vol. 95, pp. 22–37. https://doi.org/10.1016/j.compind.2017.11.003Google Scholar
Wasiak, J., Hicks, B., Newnes, L., Dong, A. and Burrow, L. (2010), “Understanding engineering email: The development of a taxonomy for identifying and classifying engineering work”, Research in Engineering Design, Vol. 21 No. 4, pp. 43–64. https://doi.org/10.1007/s00163-009-0075-4Google Scholar
Wynn, D.C. and Eckert, C.M. (2017), “Perspectives on iteration in design and development”, Research in Engineering Design, Vol. 28 No. 2, pp. 153–184. https://doi.org/10.1007/s00163-016-0226-3Google Scholar
Yang, M.C. (2009), “Observations on concept generation and sketching in engineering design”, Research in Engineering Design, Vol. 20 No. 1, pp. 1–11. https://doi.org/10.1007/s00163-008-0055-0Google Scholar
Ziv-Av, A. and Reich, Y. (2005), “SOS - Subjective objective system for generating optimal product concepts”, Design Studies, Vol. 26 No. 5, pp. 509–533. https://doi.org/10.1016/j.destud.2004.12.001Google Scholar