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Externalizing tacit overview knowledge: A model-based approach to supporting design teams

Published online by Cambridge University Press:  06 August 2007

Tomás Flanagan ,
Claudia Eckert  and
P. John Clarkson
Tomás Flanagan
Affiliation:
Engineering Design Centre, Department of Engineering, University of Cambridge, Cambridge, United Kingdom
Claudia Eckert
Affiliation:
Engineering Design Centre, Department of Engineering, University of Cambridge, Cambridge, United Kingdom
P. John Clarkson
Affiliation:
Engineering Design Centre, Department of Engineering, University of Cambridge, Cambridge, United Kingdom
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Abstract

Successful realization of large-scale product development programs is challenging because of complex product and process dependencies and complicated team interactions. Proficient teamwork is underpinned by knowledge of the manner in which tasks performed by different design participants fit together to create an effective whole. Based on an extensive industrial case study with a diesel engine company, this paper first argues that the overview and experience of senior designers play an important part in supporting teamwork by coordinating activities and facilitating proactive communication across large project teams. As experts move on and novices or contractors are hired, problems are likely to occur as tacit overview knowledge is lost. If informal, overview-driven processes break down, the risk of costly oversights will increase, and greater management overhead will be required to realize successful product designs. Existing process models provide a means to express the connectivity between tasks and components thus to compensate partially for the loss of tacit overview. This paper proposes the use of design confidence, a metric that reflects the designer's belief in the maturity of a particular design parameter at a given point in the process, to address the limitations of existing models. The applicability of confidence-based design models in providing overview, as well as their shortcomings, will be demonstrated through the example of a diesel engine design process. Confidence can be used to make overview knowledge explicit and convey additional information about the design artifact, thereby informing communication and negotiation between teams.

Keywords

CommunicationDesign ConfidenceExperienceManagementNegotiationOverviewProcess ModelingTeamwork
Type
Research Article
Information
AI EDAM , Volume 21 , Issue 3 , August 2007 , pp. 227 - 242
Copyright
Copyright © Cambridge University Press 2007

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References

REFERENCES

Ahmed, S., Wallace, K.M., & Blessing, L.T.M. (2003). Understanding the differences between how novice and experienced designers approach design tasks. Research in Engineering Design 14(1), 1–11.CrossRefGoogle Scholar
Ahmed, S. (2005). Encouraging reuse of design knowledge: a method to index knowledge. Design Studies 26(6).CrossRefGoogle Scholar
Aurisicchio, M., & Wallace, K.M. (2004). Information requests and consequent searches in aerospace design. Design 2004, 8th International Design Conf., pp. 105–110, Dubrovnik, Croatia.Google Scholar
Bédard, J., & Chi, M.T.H. (1992). Expertise, current directions. Psychological Science 1, 135–139.Google Scholar
Bly, S.A. (1988). A use of drawing surfaces in different collaborative settings. Proc. Computer Supported Cooperative Work ’88, pp. 250–256, Portland, OR. New York: ACM Press.Google Scholar
Bolger, F. (1995). Cognitive expertise research and knowledge engineering, Knowledge Engineering Review 10, 3–19.CrossRefGoogle Scholar
Browning, T.R. (2001). Applying the design structure matrix to system decomposition and integration problems: a review and new directions. IEEE Transactions on Engineering Management 48(3), 292–306.CrossRefGoogle Scholar
Browning, T.R., & Ramasesh, R.V. (2005). Modeling the product development process: a survey of the literature (Working Paper). Fort Worth, TX: Texas Christian University, Neeley School of Business.Google Scholar
Bucciarelli, L.L. (1994). Designing Engineers. Cambridge, MA: MIT Press.Google Scholar
Bucciarelli, L.L. (2002). Between thought and object in engineering design. Design Studies 23(3), 219–231.CrossRefGoogle Scholar
Clancy, W.J. (1997). Situated Cognition. Cambridge: Cambridge University Press.Google Scholar
Clarkson, P.J., & Eckert, C.M. (2004). Design Process Improvement—A Review of Current Practice. New York: Springer.Google Scholar
Clarkson, P.J., & Hamilton, J.R. (2000). Signposting: a parameter-driven task-based model of the design process. Research in Engineering Design 10(1), 18–38.CrossRefGoogle Scholar
Cooper, R.G. (1994). Third-generation new product processes. Journal of Product Innovation Management 11(1), 3–14.CrossRefGoogle Scholar
Cross, N. (2004). Expertise in design: an overview. Design Studies 25(5), 427–441.CrossRefGoogle Scholar
Cross, N., Christiaans, H., & Dorst, K., Eds. (1996). Analysing Design Activity. Chichester: Wiley.Google Scholar
Dym, C.L. (1994). Engineering Design: A Synthesis of Views. Cambridge: Cambridge University Press.Google Scholar
Eckert, C.M., & Clarkson, P.J. (2003). The reality of design process planning. ICED03, 14th Int. Conf. Engineering Design, Stockholm.Google Scholar
Eckert, C.M., Clarkson, P.J., & Stacey, M. (2001). Information flow in engineering companies: problems and their causes. ICED ‘01, 13th Int. Conf. Engineering Design, Glasgow.Google Scholar
Eckert, C.M., Clarkson, J., & Zanker, W. (2004). Change and customisation in complex engineering domains. Research in Engineering Design 15(1), 1–21.CrossRefGoogle Scholar
Eckert, C.M., & Stacey, M.K. (2000). Sources of inspiration: a language of design. Design Studies 21(5), 523–538.CrossRefGoogle Scholar
Eckert, C.M., Stacey, M.K., & Earl, C.F. (2005). References to past designs. Proc. Studying Designers '05, Aix-en-Provence, France. Sydney: Key Centre for Design Computing and Cognition, University of Sydney.Google Scholar
Eckes, G. (2001). The Six Sigma Revolution: How General Electric and Others Turned Process Into Profits. New York: Wiley.Google Scholar
Ellis, R., & McClure, G. (2004). Science and engineering careers outlook: are we looking at the future in the right light? IEEE–USA Today's Engineer Online. Accessed April 2004 at http://www.todaysengineer.org/2002/Aug/trends.aspGoogle Scholar
Ericsson, K.A., & Smith, J. (1991). Empirical study of expertise: prospects and limits. In Towards a General Theory of Expertise (Ericsson, K.A., & Smith, J., Eds.), pp. 1–38. Cambridge: Cambridge University Press.Google Scholar
Evans, J.H. (1959). Basic design concepts. Naval Engineers Journal November.Google Scholar
Feltovich, P.J., Spiro, R.J., & Coulson, R.L. (1997). Issues of expert flexibility in contexts characterized by complexity and change. In Expertise in Context: Human and Machine (Feltovich, P.J., Ford, K.M., & Hoffman, R.R., Eds.), pp. 43–65. Menlo Park, CA/Cambridge, MA: AAAI Press/MIT Press.Google Scholar
Flanagan, T., Eckert, C.M., & Clarkson, P.J. (2003). Parameter trails. ICED03, 14th Int. Conf. Engineering Design, pp. 71–73, Stockholm, Sweden.Google Scholar
Flattery, M. (2005). Workflow systems. Tessella Support Services Technical Report April.Google Scholar
Gibson, G., Davis-Blake, A., Dickson, K., & Mentel, B. (2003). Workforce demographics among project engineering professionals—crisis ahead? Journal of Management in Engineering 19(4), 173–182.CrossRefGoogle Scholar
Henderson, K. (1999). On line and on paper. In Visual Representations, Visual Culture, and Computer Graphics in Design Engineering. Cambridge, MA: MIT Press.Google Scholar
Horowitz, J. (1967). Critical Path Scheduling: Management Control Through CPM and PERT. Malabar, FL: Krieger Publishing.Google Scholar
Jarratt, T. (2004). A model-based approach to support the management of engineering change. PhD Thesis. University of Cambridge, Engineering Department.Google Scholar
Jarratt, T., Eckert, C.M., Clarkson, P.J., & Stacey, M.K. (2004). Providing an overview during the design of complex products: the development of a product linkage modelling method. In Design Computation and Cognition. DCC'04. Cambridge, MA: MIT Press.Google Scholar
Jarratt, T., Eckert, C.M., Weeks, R., & Clarkson, P.J. (2003). Environmental legislation as a driver of design. ICED03, Int. Conf. Engineering Design, Stockholm.Google Scholar
Keller, R., Flanagan, T., Eckert, C.M., & Clarkson, P.J. (2006). Two sides of the story: visualising products and processes in engineering design. 10th Int. Conf. Information Visualisation, London.CrossRefGoogle Scholar
Kerzner, H. (1992). Project Management: A Systems Approach to Planning, Scheduling, and Controlling, 4th ed.New York: Van Nostrand Reinhold.Google Scholar
Marca, D.A., & McGowan, C.L. (1993). IDEF0—SADT Business Process and Enterprise Modelling. New York: McGraw–Hill.Google Scholar
Martin, M.V., & Ishii, K. (2002). Design for variety: developing standardized and modularized product platform architectures. Research in Engineering Design 13(4), 213–235.CrossRefGoogle Scholar
McMahon, C.A., Sims Williams, J.H., & Brown, K.N. (1993). A transformation model for the integration of design computing. Int. Conf. Engineering Design, pp. 1586–1593, The Hague.Google Scholar
Melo, A.F., (2002). A state-action model for design process planning. PhD Thesis. University of Cambridge, Engineering Department.Google Scholar
Melo, A.F., & Clarkson, P.J. (2001). Design process planning using a state–action model. 13th Int. Conf. Engineering Design (ICED 01), Glasgow.Google Scholar
Minneman, S.L. (1991). The social construction of a technical reality: empirical studies of group engineering design practice. PhD Thesis. Stanford University.Google Scholar
O'Donovan, B. (2004). Modelling and simulation of engineering design processes. PhD Thesis. University of Cambridge, Engineering Department.Google Scholar
Pahl, G., & Beitz, W. (1996). Engineering Design (Wallace, K.M., Blessing, L.T.M. & Bauert, F., Eds.), 2nd ed.London: Springer.CrossRefGoogle Scholar
PMI. (2000). A Guide to the Project Management Body of Knowledge. Accessed at www.pmi.orgGoogle Scholar
Shigley, J.E., & Mischke, C.R. (1989). Mechanical Engineering Design. New York: McGraw–Hill.Google Scholar
Smith, P.G., & Reinertsen, D.G. (1998). Developing Products in Half the Time. New Rules, New Tools, 2nd ed.New York: Wiley.Google Scholar
Stacey, M.K., & Eckert, C.M. (2003). Against ambiguity. Computer Supported Cooperative Work: The Journal of Collaborative Computing 12(2), 153–183.CrossRefGoogle Scholar
Stacey, M.K., Eckert, C.M., & Wiley, J. (2002). Expertise and creativity in knitwear design. International Journal of New Product Development and Innovation 4(1), 49–64.Google Scholar
Star, S.L. (1989). The structure of ill-structured solutions: boundary objects and heterogeneous distributed problem solving. In Distributed Artificial Intelligence (Gasser, L. & Huhns, M., Eds.), Vol. II. London: Pitman.Google Scholar
Steward, D.V. (1981). The design structure system: a method for managing the design of complex systems. IEEE Transactions on Engineering Management 28(3), 71–74.CrossRefGoogle Scholar
Suchman, L.A. (1987). Plans and Situated Actions. Cambridge: Cambridge University Press.Google Scholar
Suh, N.P. (2001). Axiomatic Design: Advances and Applications. New York: Oxford University Press.Google Scholar
Tang, J.C. (1989). Listing, drawing, and gesturing in design: a study of the use of shared workspaces by design teams. PhD Thesis. Stanford University, Department of Mechanical Engineering (Xerox Palo Alto Research Center Report SSL-89-3).Google Scholar
Tang, J.C. (1991). Findings from observational studies of collaborative work. International Journal of Man–Machine Studies 34, 143–160.CrossRefGoogle Scholar
Tang, J.C., & Leifer, L. (1988). A framework for understanding the workspace activity of design teams. Proc. Computer Supported Cooperative Work ’88, pp. 226–232, Portland, OR. New York: ACM Press.Google Scholar
Valkenburg, R., & Dorst, K. (1998). The reflective practice of design teams. Design Studies 19(3), 249–271.CrossRefGoogle Scholar
Visser, W. (1990). More or less following a plan during design: opportunistic deviations in specification. International Journal of Man–Machine Studies 33, 247–278.CrossRefGoogle ScholarPubMed
Visser, W. (1994). The organisation of design activities: opportunistic, with hierarchical episodes. Interacting with Computers 6, 235–274.CrossRefGoogle Scholar
Wynn, D., & Clarkson, P.J. (2004). Models of designing. In Design Process Improvement—A Review of Current Practice (Clarkson, P.J., & Eckert, C.M., Eds.), pp. 34–59. New York: Springer.Google Scholar
Wynn, D., Clarkson, P.J., & Eckert, C.M. (2005). A model-based approach to improve planning practice in collaborative aerospace design. ASME DTM 05.Google Scholar