Skip to main content Accesibility Help
×
×
Home

Spanning the complexity chasm: A research approach to move from simple to complex engineering systems

  • Vimal Viswanathan (a1) and Julie Linsey (a2)
Abstract

A multistudy approach is presented that allows design thinking of complex systems to be studied by triangulating causal controlled lab findings with coded data from more complex products. A case study illustration of this approach is provided. During the conceptual design of engineering systems, designers face many cognitive challenges, including design fixation, errors in their mental models, and the sunk cost effect. These factors need to be mitigated for the generation of effective ideas. Understanding the effects of these challenges in a realistic and complex engineering system is especially difficult due to a variety of factors influencing the results. Studying the design of such systems in a controlled environment is extremely challenging because of the scale and complexity of such systems and the time needed to design the systems. Considering these challenges, a mixed-method approach is presented for studying the design thinking of complex engineering systems. This approach includes a controlled experiment with a simple system and a qualitative cognitive-artifacts study on more complex engineering systems followed by the triangulation of results. The triangulated results provide more generalizable information for complex system design thinking. This method combines the advantages of quantitative and qualitative study methods, making them more powerful while studying complex engineering systems. The proposed method is illustrated further using an illustrative study on the cognitive effects of physical models during the design of engineering systems.

Copyright
Corresponding author
Reprint requests to: Julie Linsey, Woodruff School of Mechanical Engineering, Georgia Institute of Technology, 801 Ferst Drive NW, Atlanta, GA 30332, USA. E-mail: julie.linsey@me.gatech.edu
References
Hide All
Abildso, C., Zizzi, S., Gilleland, D., Thomas, J., & Bonner, D. (2010). A mixed methods evaluation of a 12-week insurance-sponsored weight management program incorporating cognitive-behavioral counseling. Journal of Mixed Methods Research 4(4), 278294.
Altshuller, G., Shulyak, L., & Rodman, S. (1997). 40 Principles: TRIZ Keys to Innovation. Worcester, MA: Technical Innovation Center.
Altshuller, G.S. (1984). Creativity as an Exact Science: The Theory of the Solution of Inventive Problems. Amsterdam: Gordon & Breach.
Arkes, H.R., & Blumer, C. (1985). The psychology of sunk cost. Organizational Behavior and Human Decision Processes 35(1), 124140.
Atman, C.J., Adams, R.S., Cardella, M.E., Turns, J., Mosborg, S., & Saleem, J. (2007). Engineering design processes: a comparison of students and expert practitioners. Journal of Engineering Education 96(4), 359379.
Atman, C.J., Kilgore, D., & McKenna, A. (2008). Characterizing design learning: a mixed-methods study of engineering designers' use of language. Journal of Engineering Education 97(3), 309326.
Auerbach, C.F., & Silverstein, L.B. (2003). Qualitative Data: An Introduction to Coding and Analysis. New York: New York University Press.
Aurigemma, J., Chandrasekharan, S., Nersessian, N.J., & Newstetter, W. (2013). Turning experiments into objects: the cognitive processes involved in the design of a lab-on-a-chip device. Journal of Engineering Education 102(1), 117140.
Blessing, L.T., & Chakrabarti, A. (2009). DRM: A Design Research Methodology. London: Springer.
Boujut, J.F., & Blanco, E. (2003). Intermediary objects as a means to foster co-operation in engineering design. Computer Supported Cooperative Work 12(2), 205219.
Cagan, J., Dinar, M., Shah, J.J., Leifer, L., Linsey, J., Smith, S., & Vargas-Hernandez, N. (2013). Empirical studies of design thinking: past, present, future. Proc. ASME Int. Design Engineering Technical Confs. Computers and Information in Engineering Conf., Paper No. DETC2013-13302, Portland, OR, Aug 4–7.
Carlile, P.R. (2002). A pragmatic view of knowledge and boundaries: boundary objects in new product development. Organization Science 13(4), 442455.
Chakrabarti, A., Morgenstern, S., & Knaab, H. (2004). Identification and application of requirements and their impact on the design process: a protocol study. Research in Engineering Design 15(1), 2239.
Christensen, B.T., & Schunn, C.D. (2005). The relationship of analogical distance to analogical function and pre-inventive structure: the case of engineering design. Creative Cognition: Analogy and Incubation 35(1), 2938.
Chrysikou, E.G., & Weisberg, R.W. (2005). Following the wrong footsteps: fixation effects of pictorial examples in a design problem-solving task. Journal of Experimental Psychology: Learning, Memory, and Cognition 31(5), 11341148.
Clark-Carter, D. (1997). Doing Quantitative Psychological Research: From Design to Report. London: Psychology Press/Erlbaum.
Creamer, E.G., & Ghoston, M. (2013). Using a mixed methods content analysis to analyze mission statements from colleges of engineering. Journal of Mixed Methods Research 7(2), 110120.
Crede, E., & Borrego, M. (2013). From ethnography to items: a mixed methods approach to developing a survey to examine graduate engineering student retention. Journal of Mixed Methods Research 7(1), 6280.
Creswell, J.W., & Clark, V.L.P. (2007). Designing and Conducting Mixed Methods Research. Thousand Oaks, CA: Sage.
Dorst, K., & Cross, N. (2001). Creativity in the design process: co-evolution of problem–solution. Design Studies 22(5), 425437.
Fish, J. (2004). Cognitive catalysis: sketches for a time-lagged brain. In Design Representation (Goldschmidt, G., & Porter, W., Eds.), pp. 151184. London: Springer.
Fu, J.-F., Fenton, R.G., & Cleghorn, W.L. (1991). A mixed integer-discrete-continuous programming method and its application to engineering design optimization. Engineering Optimization 17(4), 263280.
Gentner, D., & Stevens, A. (1983). Mental Models. Mahwah, NJ: Erlbaum.
Gero, J.S., & McNeill, T. (1998). An approach to the analysis of design protocols. Design Studies 19(1), 2161.
Goldschmidt, G. (2007). To see eye to eye: the role of visual representations in building shared mental models in design teams. CoDesign 3(1), 4350.
Haller, L., & Cullen, C. (2004). Design Secrets: Products 2: 50 Real-Life Projects Uncovered. Beverly, MA: Rockport.
Hannah, R., Michaelrag, A., & Summers, J. (2008). A proposed taxonomy for physical prototypes: structure and validation. Proc. ASME Int. Design Engineering Technical Conf., Paper No. DETC2008-49976, New York, August 3–6.
Harrison, S., & Minneman, S. (1997). A bike in hand: a study of 3-D objects in design. In Analysing Design Activity (Cross, N., et al. , Eds.), pp. 417436. New York: Wiley.
Holcomb, J.H., & Evans, D.A. (1987). The effect of sunk costs on uncertain decisions in experimental markets. Journal of Behavioral Economics 16(3), 5966.
Horton, G.I., & Radcliffe, D.F. (1995). Nature of rapid proof-of-concept prototyping. Journal of Engineering Design 6(1), 316.
Hsiao, C., Malak, R., Tumer, I.Y., & Doolen, T. (2013). Empirical findings about risk and risk mitigating actions from a legacy archive of a large design organization. Procedia Computer Science 16, 844852.
Hutchins, E., & Lintern, G. (1995). Cognition in the Wild. Cambridge, MA: MIT Press.
IDSA. (2003). Design Secrets: Products. Beverly, MA: Rockport.
Jansson, D., & Smith, S. (1991). Design fixation. Design Studies 12(1), 311.
Johnson, R.B., & Onwuegbuzie, A.J. (2004). Mixed methods research: a research paradigm whose time has come. Educational Researcher 33(7), 1426.
Kahneman, D., & Tversky, A. (1979). Prospect theory: an analysis of decision under risk. Econometrica 47(2), 263291.
Keeney, R.L., & Raiffa, H. (1993). Decisions With Multiple Objectives: Preferences and Value Tradeoffs. Cambridge: Cambridge University Press.
Kelley, T. (2001). Prototyping is the shorthand of innovation. Design Management Journal 12(3), 3542.
Kempton, W. (1986). Two theories of home heat control. Cognitive Science 10(1), 7590.
Kiriyama, T., & Yamamoto, T. (1998). Strategic knowledge acquisition: a case study of learning through prototyping. Knowledge-Based Systems 11(7–8), 399404.
Kirk, R.E. (1982). Experimental Design. Monterey, CA: Brooks/Cole.
Kurtoglu, T., Campbell, M.I., Arnold, C.B., Stone, R.B., & Mcadams, D.A. (2009). A component taxonomy as a framework for computational design synthesis. Journal of Computing and Information Science in Engineering 9, 011007.
Lemons, G., Carberry, A., Swan, C., Jarvin, L., & Rogers, C. (2010). The benefits of model building in teaching engineering design. Design Studies 31(3), 288309.
Lidwell, W., Holden, K., & Butler, J. (2003). Universal Principles of Design. Beverly, MA: Rockport.
Linsey, J., Clauss, E.F., Kurtoglu, T., Murphy, J.T., Wood, K.L., & Markman, A.B. (2011). An experimental study of group idea generation techniques: understanding the roles of idea representation and viewing methods. ASME Transactions: Journal of Mechanical Design 133(3), 031008.
Linsey, J.S., Tseng, I., Fu, K., Cagan, J., Wood, K.L., & Schunn, C. (2010). A study of design fixation, its mitigation and perception in engineering design faculty. ASME Transactions: Journal of Mechanical Design 132(4), 041003.
McKim, R.H. (1972). Experiences in Visual Thinking. Boston: PWS.
McMillan, J.H., & Schumacher, S. (2014). Research in Education: Evidence-Based Inquiry. Essex: Pearson Education.
MITRE Systems Enginering Process Office. (2005). Perspectives on complex-system engineering. Collaborations 3(2). Accessed on September 16, 2013, at http://necsi.edu/necsi/mitrecoll3.2.pdf
Nelson, B.A., Wilson, J.O., Rosen, D., & Yen, J. (2009). Refined metrics for measuring ideation effectiveness. Design Studies 30(6), 737743.
Nersessian, N.J. (1995). Opening the black box: cognitive science and history of science. OSIRIS: Constructing Knowledge in the History of Science 10, 194211.
Ott, L., & Longnecker, M. (2008). An Introduction to Statistical Methods and Data Analysis. Belmont, CA: Brooks/Cole.
Otto, K.N., & Wood, K.L. (2001). Product Design: Techniques in Reverse Engineering and New Product Development. New York: Prentice Hall.
Pahl, G., & Beitz, W. (2003). Engineering Design: A Systematic Approach. London: Springer.
Paton, B., & Dorst, K. (2011). Briefing and reframing: a situated practice. Design Studies 32(6), 573587.
Petre, M. (2004). How expert engineering teams use disciplines of innovation. Design Studies 25(5), 477493.
Purcell, A., & Gero, J. (1992). Effects of examples on the results of a design activity. Knowledge-Based Systems 5(1), 8291.
Purcell, A.T., & Gero, J.S. (1996). Design and other types of fixation. Design Studies 17(4), 363383.
Saunders, M.N., Seepersad, C.C., & Hölttä-Otto, K. (2009). The characteristics of innovative, mechanical products. ASME Transactions: Journal of Mechanical Design 133(2), 021009.
Schon, D.A., & Wiggins, G. (1992). Kinds of seeing and their functions in designing. Design Studies 13(2), 135156.
Shah, J.J., Kulkarni, S.V., & Vargas-Hernandez, N. (2000). Evaluation of idea generation methods for conceptual design: effectiveness metrics and design of experiments. ASME Transactions: Journal of Mechanical Design 122(4), 377384.
Shah, J.J., Smith, S.M., & Vargas-Hernandez, N. (2003 a). Metrics for measuring ideation effectiveness. Design Studies 24(2), 111134.
Shah, J.J., Smith, S.M., Vargas-Hernandez, N., Gerkens, D.R., & Wulan, M. (2003 b). Empirical studies of design ideation: alignment of design experiments with lab experiments. Proc. ASME Int. Design Engineering Technical Confs., Paper No. DETC2003/DTM-48679, Chicago, September 2–6.
Sheldon, D.F. (2006). Design review 2005/2006—the ever increasing maturity of design research papers and case studies. Journal of Engineering Design 17(6), 481486.
Sushkov, V., Mars, N.J., & Wognum, P. (1995). Introduction to TIPS: a theory for creative design. Artificial Intelligence in Engineering 9(3), 177189.
Suwa, M., & Tversky, B. (1996). What architects see in their sketches: implications for design tools. Proc. Conf. Companion on Human Factors in Computing Systems: Common Ground, pp. 191192. New York: ACM.
Tabachnick, B.G., & Fidell, L.S. (2007). Experimental Designs Using ANOVA. Belmont, CA: Thomson/Brooks/Cole.
Tashakkori, A., & Teddlie, C. (1998). Mixed Methodology: Combining Qualitative and Quantitative Approaches. Thousand Oaks, CA: Sage.
Teegavarapu, S., & Summers, J.D. (2008). Case study method for design research. Proc. ASME 2008 Int. Design Engineering Technical Conf., Computers and Information in Engineering Conf., Paper No. DETC2008-49980, New York, August 3–6.
Tseng, I., Moss, J., Cagan, J., & Kotovsky, K. (2008). The role of timing and analogical similarity in the stimulation of idea generation in design. Design Studies 29(3), 203221.
Veisz, D., Joshi, S., & Summers, J.d. (2012). Computer-aided design versus sketching: an exploratory case study. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 26(3), 317335.
Viswanathan, V., & Linsey, J. (2013 a). Design fixation and its mitigation: a study on the role of expertise. ASME Transactions: Journal of Mechanical Design 135(5), 051008.
Viswanathan, V., & Linsey, J. (2013 b). Role of sunk cost in engineering idea generation: an experimental investigation. ASME Transactions: Journal of Mechanical Design 135(12), 121002.
Viswanathan, V.K., Esposito, N., & Linsey, J. (2012). Training tomorrow's designers: a study on design fixation. Proc. ASEE Annual Conf., Paper No. 2012-4925, San Antonio, TX, June 1013.
Viswanathan, V.K., & Linsey, J. (2012). Physical models and design thinking: a study of functionality, novelty and variety of ideas. ASME Transactions: Journal of Mechanical Design 134(9), 091004.
Viswanathan, V.K., & Linsey, J.S. (2009). Enhancing student innovation: physical models in the idea generation process. Proc. ASEE/IEEE Frontiers in Education Conf., Paper No. 978-1-4244-4714-5/09, San Antonio, TX, October 18–21.
Viswanathan, V.K., & Linsey, J.S. (2010). Physical models in idea generation—hindrance or help? Proc. Int. Conf. Design Theory and Methodology, Paper No. DETC2010-28327, Montreal, August 15–18.
Viswanathan, V.K., & Linsey, J.S. (2011 a). Design fixation in physical modeling: an investigation on the role of sunk cost. Proc. Int. Conf. Design Theory and Methodology, Paper No. DETC2011-47862, Washington, DC, August 29–31.
Viswanathan, V.K., & Linsey, J.S. (2011 b). Understanding physical models in design cognition: a triangulation of qualitative and laboratory studies. Proc. ASEE/IEEE Frontiers in Education Conf., Paper No. 978-1-61284-469-5/11, Rapid City, SD, October 12–16.
Ward, A., Liker, J.K., Cristiano, J.J., & Sobek, D.K. (1995). The second Toyota paradox: how delaying decisions can make better cars faster. Sloan Management Review 36, 43.
Westmoreland, S.N. (2012). Design thinking: cognitive patterns in engineering design documentation. PhD Thesis. University of Maryland, College Park.
Wong, Y.Y. (1992). Rough and ready prototypes: lessons from graphic design. Proc. Posters and Short Talks of the 1992 SIGCHI Conf. Human Factors in Computing Systems, Paper No. 1125094, pp. 83–84.
Yang, M.C. (2005). A study of prototypes, design activity, and design outcome. Design Studies 26(6), 649669.
Youmans, R.J. (2011). The effects of physical prototyping and group work on the reduction of design fixation. Design Studies 32(2), 115138.
Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

AI EDAM
  • ISSN: 0890-0604
  • EISSN: 1469-1760
  • URL: /core/journals/ai-edam
Please enter your name
Please enter a valid email address
Who would you like to send this to? *
×

Keywords

Metrics

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed