Form innovation: investigating the use of generative design tools to encourage creativity in product design

References

• 3DS: 3DExperience Function Driven Generative Design. (2022). Retrieved May 5, 2023, from https://www.3ds.com/cloud/performance-driven-generative-design
   Google Scholar
• Abdelmohsen, S. (2013) Reconfiguring architectural space using generative design and digital fabrication: A project based course. In Proc. of the XVII Conference of the Iberoamerican Society of DigitalGraphics-SIGraDi: Knowledge-Based Design, Editora Edgard Blucher, Ltd.: São Paulo, Brazil, 2013, pp. 391–395. https://doi.org/10.5151/despro-sigradi2013-0074
   Google Scholar
• Achiche, S., Appio, F. P., McAloone, T. C., & DiMinin, A. (2013). Fuzzy decision support for tools selection in the core front end activities of new product development. Research in Engineering Design, 24(1), 1–18. https://doi.org/10.1007/s00163-012-0130-4
   Web of Science ®Google Scholar
• A.I. family. (2022). Retrieved May 5, 2023, from https://www.kartell.com/IT/en/salone-del-mobile-2022/technology-for-sustainability-ai-family/SalonedelMobile2022_6overview
   Google Scholar
• Alcaide Marzal, J., Diego-Mas, J. A., & Acosta-Zazueta, G. (2020). A 3D shape generative method for aesthetic product design. Design Studies, 66, 144–176. https://doi.org/10.1016/j.destud.2019.11.003
   Web of Science ®Google Scholar
• Amabile, T. M. (1996). Creativity in context. Westview Press.
   Google Scholar
• Ang, M. C., Chau, H. H., McKay, A., & de Pennington, A. (2006), “Combining evolutionary algorithms and shape grammars to generate branded product design”, in J. S. Gero (Ed.), 2nd Design Computing and Cognition Conference DCC’06, Springer, Dordrecht, pp. 521–539.
   Google Scholar
• Archer, L. B. (1974). Design awareness and planned creativity in industry: Connaissance du design et la creativite planifiee dans l’industie. Office of Design, Department of Industry, Trade and Commerce, and the Design Council of Great Britain.
   Google Scholar
• Autodesk: Autodesk Fusion 360. (2022). Retrieved May 5, 2023, from. https://www.autodesk.com/solutions/generative-design/manufacturing
   Google Scholar
• Ball, P. (2009). Shapes: Nature’s patterns: A tapestry in three parts. OUP Oxford.
   Google Scholar
• Barbieri, L., & Muzzupappa, M. (2022). Performance-Driven Engineering Design Approaches Based on Generative Design and topology optimization tools: A comparative study. Applied Sciences, 12(4), 2106. https://doi.org/10.3390/app12042106
   Google Scholar
• Becattini, N., Borgianni, Y., Cascini, G., & Rotini, F. (2017). Surprise and design creativity: Investigating the drivers of unexpectedness. International Journal of Design Creativity & Innovation, 5(1–2), 29–47. https://doi.org/10.1080/21650349.2015.1090913
   Web of Science ®Google Scholar
• Bloch, P. H., Brunel, F. F., & Arnold, T. J. (2003). Individual differences in the centrality of visual product aesthetics: Concept and measurement. The Journal of Consumer Research, 29(4), 551–565. https://doi.org/10.1086/346250
   Web of Science ®Google Scholar
• Bose, M., & Dey, A. (2009). Optimal crossover designs. World Scientific Publishing.
   Google Scholar
• Brown, D. C. (2012). Creativity, surprise & design: An introduction and investigation. In A. Duffy, Y. Nagai, & T. Taura (Eds.), DS 73-1 Proceedings of the 2nd International Conference on Design Creativity Glasgow, Scotland (UK). ISBN: 978-1-904670-39-1.
   Google Scholar
• Buonamici, F., Carfagni, M., Furferi, R., Volpe, Y., & Governi, L. (2020). Generative design: An explorative study. Computer-Aided Design and Applications, 18(1), 144–155. https://doi.org/10.14733/cadaps.2021.144-155
   Google Scholar
• Caetano, I., Santos, L., & Leitão, A. (2020). Computational design in architecture: Defining parametric, generative, and algorithmic design. Frontiers of Architectural Research, 9(2), 287–300. https://doi.org/10.1016/j.foar.2019.12.008
   Web of Science ®Google Scholar
• Caldas, L. G. (2008). Generation of energy-efficient architecture solutions applying GENE_ARCH: An evolution-based generative design system. Advanced Engineering Informatics, 22(1), 59–70. https://doi.org/10.1016/j.aei.2007.08.012
   Web of Science ®Google Scholar
• Cascini, G., Nagai, Y., Georgiev, G. V., Zelaya, J., Becattini, N., Boujut, J. F., & Wodehouse, A. (2022). Perspectives on design creativity and innovation research: 10 years later. International Journal of Design Creativity & Innovation, 10(1), 1–30. https://doi.org/10.1080/21650349.2022.2021480
   Web of Science ®Google Scholar
• Chang, Y.-S., Chien, Y.-H., Lin, H.-C., Yiching, M. C., & Hsieh, H.-H. (2016). Effects of 3D CAD applications on the design creativity of students with different representational abilities. Computers in Human Behavior, 65, 107–113. https://doi.org/10.1016/J.CHB.2016.08.024
   Web of Science ®Google Scholar
• Charyton, C., & Merrill, J. A. (2009). Assessing general creativity and creative engineering design in first year engineering students. Journal of Engineering Education, 98(2), 145–156. https://doi.org/10.1002/j.2168-9830.2009.tb01013.x
   Web of Science ®Google Scholar
• Chaszar, A., & Joyce, S. C. (2016). Generating freedom: Questions of flexibility in digital design and architectural computation. International Journal of Architectural Computing, 14(2), 167–181. https://doi.org/10.1177/1478077116638945
   Web of Science ®Google Scholar
• Chau, H. H., Chen, X., McKay, A., & de Pennington, A. (2004), “Evaluation of a 3D shape grammar implementation”, in J. S. Gero (Ed.), 1st Design Computing and Cognition Conference - DCC’04, Cambridge, MA, pp. 357–376
   Google Scholar
• Chiu, I., & Shu, L. H. (2012). Investigating effects of oppositely related semantic stimuli on design concept creativity. Journal of Engineering Design, 23(4), 271–296. https://doi.org/10.1080/09544828.2011.603298
   Web of Science ®Google Scholar
• Christensen, B. T., & Ball, L. J. (2016). Dimensions of creative evaluation: Distinct design and reasoning strategies for aesthetic, functional and originality judgments. Design Studies, 45, 116–136. https://doi.org/10.1016/j.destud.2015.12.005
   Web of Science ®Google Scholar
• Chulvi, V., Sonseca, Á., Mulet, E., & Chakrabarti, A. (2012). Assessment of the relationships among design methods, design activities, and creativity. Journal of Mechanical Design, 134(11), 111004–1110011. https://doi.org/10.1115/1.4007362
   Web of Science ®Google Scholar
• Cluzel, F., & Yannou, B. (2009), “Efficiency assessment of an evolutive design system of car contours”, in 17th International Conference on Engineering Design - ICED’09, Stanford, CA. CogniCAD: ParaMatters ConiCAD.
   Google Scholar
• Cluzel, F., Yannou, B., & Dihlmann, M. (2012). Using evolutionary design to interactively sketch car silhouettes and stimulate designer’s creativity. Engineering Applications of Artificial Intelligence, 25(7), 1413–1424. https://doi.org/10.1016/j.engappai.2012.02.011
   Web of Science ®Google Scholar
• Cohen, J. (1977). Statistical power analysis for the behavioral sciences. Elsevier. https://doi.org/10.1016/C2013-0-10517-X
   Google Scholar
• Crilly, N., Moultrie, J., & Clarkson, P. J. (2004). Seeing things: Consumer response to the visual domain in product design. Design Studies, 25(6), 547–577. https://doi.org/10.1016/j.destud.2004.03.001
   Web of Science ®Google Scholar
• Cropley, D. H., & Kaufman, J. C. (2019). The siren song of aesthetics? Domain differences and creativity in engineering and design, proceed- ings of the institution of mechanical engineers. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 233(2), 451–464. https://doi.org/10.1177/0954406218778311
   Web of Science ®Google Scholar
• Čučaković, A., Jovic, B., & Komnenov, M. (2016). Biomimetic geometry approach to generative design. Periodica Polytechnica Architecture, 47(2), 70–74. https://doi.org/10.3311/PPar.10082
   Google Scholar
• Davis, N., Hsiao, C., Singh, K. Y., Lin, B., & Magerko, B. (2017). Quantifying collaboration with a co-creative drawing agent. Acm Transactions on Interactive Intelligent Systems (Tiis), 7(4), 1–25. https://doi.org/10.1145/3009981
   Web of Science ®Google Scholar
• De Graff, J., & Lawrence, K. A. (2002). Creativity at work: Developing the right practices to make innovation happen. Jossey-Bass, A Wiley Co.
   Google Scholar
• Demirkan, H., & Afacan, Y. (2012). Assessing creativity in design education: Analysis of creativity factors in the first-year design studio. Design Studies, 33(3), 262–278. https://doi.org/10.1016/j.destud.2011.11.005
   Web of Science ®Google Scholar
• Doré, R., Pailhes, J., Fischer, X., & Nadeau, J.-P. (2007). Identification of sensory variables towards the integration of user requirements into preliminary design. International Journal of Industrial Ergonomics, 37(1), 1–11. https://doi.org/10.1016/j.ergon.2006.08.006
   Web of Science ®Google Scholar
• Du Plessis, A., Broeckhoven, C., Yadroitsava, I., Yadroitsev, I., Hands, C. H., Kunju, R., & Bhate, D. (2019). Beautiful and functional: A review of biomimetic design in additive manufacturing. Additive Manufacturing, 27, 408–427. https://doi.org/10.1016/j.addma.2019.03.033
   Web of Science ®Google Scholar
• Ferguson, E. (1994). Engineering and the Mind’s eye. MIT Press.
   Google Scholar
• Fidler, K. (2021). Engineering engineering: A provocation. White paper presented at the Engineering Professors Council 6th July 2021, https://epc.ac.uk/uploads/2021/11/Eng-Eng-final.pdf
   Google Scholar
• Frazer, J. H. (1974). Reptiles. Architectural Design, XLIX(4), 231–241.
   Google Scholar
• Frazer, J. H. (1995). An evolutionary architecture. Architectural Association Publications.
   Google Scholar
• García-García, C., Chulvi, V., & Royo, M. (2017). Knowledge generation for enhancing design creativity through co-creative virtual learning communities. Thinking Skills and Creativity, 24, 12–19. https://doi.org/10.1016/j.tsc.2017.02.009
   Web of Science ®Google Scholar
• Gero, J. S. (2020). Nascent directions for design creativity research. International Journal of Design Creativity & Innovation, 8(3), 144–146. https://doi.org/10.1080/21650349.2020.1767885
   Web of Science ®Google Scholar
• Goldenberg, J., and Mazursky, D. 2002. Creativity in product innovation. Cambridge (United Kingdom): Cambridge University Press.
   Google Scholar
• Goode, M. R., Dahl, D. W., & Moreau, C. P. (2013). Innovation aesthetics: The relationship between category cues, categorization certainty, and newness perceptions. Journal of Product Innovation Management, 30(2), 192–208. https://doi.org/10.1111/j.1540-5885.2012.00995.x
   Web of Science ®Google Scholar
• Han, J., Forbes, H., & Schaefer, D. (2021). An exploration of how creativity, functionality, and aesthetics are related in design. Research in Engineering Design, 32(3), 289–307. https://doi.org/10.1007/s00163-021-00366-9
   Web of Science ®Google Scholar
• Horn, D., & Salvendy, G. (2009). Measuring consumer perception of product creativity: Impact on satisfaction and purchasability. Human Factors and Ergonomics in Manufacturing & Service Industries, 19(3), 223–240. https://doi.org/10.1002/hfm.20150
   Web of Science ®Google Scholar
• Kim, J., & Maher, M. L. (2023). The effect of AI-based inspiration on human design ideation. International Journal of Design Creativity & Innovation, 11(2), 81–98. https://doi.org/10.1080/21650349.2023.2167124
   Web of Science ®Google Scholar
• Knight, T. W. (1980). The generation of Hepplewhite-style chair-back designs. Environment and Planning B, 7(2), 227–238. https://doi.org/10.1068/b070227
   Google Scholar
• Krish, S. (2011). A practical generative design method. Computer-Aided Design, 43(1), 88–100. https://doi.org/10.1016/j.cad.2010.09.009
   Web of Science ®Google Scholar
• Kroll, E. (2013). Design theory and conceptual design: Contrasting functional decomposition and morphology with parameter analysis. Research in Engineering Design, 24(2), 165–183. https://doi.org/10.1007/s00163-012-0149-6
   Web of Science ®Google Scholar
• Lee, J. H., Gu, N., & Ostwald, M. J. (2015). Creativity and parametric design? Comparing designer’s cognitive approaches with assessed levels of creativity. International Journal of Design Creativity & Innovation, 3(2), 78–94. https://doi.org/10.1080/21650349.2014.931826
   Web of Science ®Google Scholar
• Lo, C. H., Ko, Y. C., & Hsiao, S. W. (2015). A study that applies aesthetic theory and genetic algorithms to product form optimization. Advanced Engineering Informatics, 29(3), 662–679. https://doi.org/10.1016/j.aei.2015.06.004
   Web of Science ®Google Scholar
• Lopez, R., Linsey, J. S., & Smith, S. M. (2011). Characterizing the effect of domain distance in design-by-analogy. In International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 54860, 141–151. https://doi.org/10.1115/DETC2011-48428
   Google Scholar
• Maher, M. L., & Fisher, D. H. (2012). Using AI to evaluate creative designs. In A. Duffy, Y. Nagai, & T. Taura (Eds.), DS 73-1 Proceedings of the 2nd International Conference on Design Creativity 1. Glasgow, Scotland (UK).
   Google Scholar
• McCormack, J. P., Cagan, J., & Vogel, C. M. (2004). Speaking the Buick language: Capturing, understanding, and exploring brand identity with shape grammars. Design Studies, 25(1), 1–29. https://doi.org/10.1016/S0142-694X(03)00023-1
   Web of Science ®Google Scholar
• McCormack, J. P., Dorin, A., & Innocent, T. C. (2005). Generative design: A paradigm for design research. In J. Redmond, D. Durling, & A. de Bono (Eds.), Future ground (Vol. 2, p. 2005). Monash University.
   Google Scholar
• McKnight, M. (2017). Generative design: What it is? How is it being used? Why it’s a game changer. KnE Engineering, 2(2), 176–181. https://doi.org/10.18502/keg.v2i2.612
   Google Scholar
• Mitchell, W. J. 2005. Constructing complexity. In: B. Martens & A. Brown (Eds.), Proc. Int. Computer Aided Architectural Design Futures Conference, Vienna (Austria) (pp. 41,50). Springer Netherlands.
   Google Scholar
• Mountstephens, J., & Teo, J. (2020). Progress and challenges in generative product design: A review of systems. Computers, 9(4), 80. https://doi.org/10.3390/computers9040080
   Web of Science ®Google Scholar
• MSC Software Corporation: MSC Apex Generative Design. (2022). Retrieved May 5, 2023, from. https://www.mscsoftware.com/product/msc-apex-generative-design
   Google Scholar
• Nordin, A. (2018). Challenges in the industrial implementation of generative design systems: An exploratory study. AI EDAM, 32(1), 16–31. https://doi.org/10.1017/S0890060416000536
   Google Scholar
• Nordin, A., Motte, D., Hopf, A., Bjärnemo, R., & Eckhardt, C.-C. (2010), “Complex product form generation in industrial design: A bookshelf based on voronoi diagrams”, in J. S. Gero (Ed.), 4th Design Computing and Cognition Conference - DCC’10, Springer, Stuttgart, pp. 701–720.
   Google Scholar
• NTopology: nTopology Generative Design. (2022). Retrieved May 5, 2023, from. https://ntopology.com/generative-design-software/
   Google Scholar
• O’Quin, K., & Besemer, S. P. (1989). The development, reliability, and validity of the revised creative product semantic scale. Creativity Research Journal, 2(4), 267–278. https://doi.org/10.1080/10400418909534323
   Google Scholar
• Orsborn, S., Cagan, J., & Boatwright, P. (2008), “Automating the creation of shape grammar rules”, in J. S. Gero & A. K. Goel (Eds.), 3rd Design Computing and Cognition Conference DCC’08, Springer, Stuttgart, pp. 3–22.
   Google Scholar
• Orsborn, S., Cagan, J., Pawlicki, R., & Smith, R. C. (2006). Creating cross-over vehicles: Defining and combining vehicle classes using shape grammars. Artificial Intelligence for Engineering Design, Analysis and Manufacturing - AI EDAM, 20(3), 217–246. https://doi.org/10.1017/S0890060406060185
   Google Scholar
• Osgood, C. E., Suci, G. J., & Tannenbaum, P. H. (1957). The measurement of meaning. University of Illinois press.
   Google Scholar
• Pilagatti, A. N., Atzeni, E., & Salmi, A. (2023). Exploiting the generative design potential to select the best conceptual design of an aerospace component to be produced by additive manufacturing. International Journal of Advanced Manufacturing Technology, 1–16. https://doi.org/10.1007/s00170-023-11259-7
   Web of Science ®Google Scholar
• Plucker, J. A., & Makel, M. C. (2010). Assessment of creativity. In J. Kaufman & R. Sternberg (Eds.), The Cambridge handbook of creativity (pp. 48–73). The Cambridge University Press.
   Google Scholar
• PTC: Parametric Technology Corporation Creo. (2022). Retrieved May 5, 2023, from https://www.ptc.com/en/technologies/cad/generative-design#overview
   Google Scholar
• Pugliese, M. J., & Cagan, J. (2002). Capturing a rebel: Modeling the Harley-Davidson brand through a motorcycle shape grammar. Research in Engineering Design, 13(3), 139–156. https://doi.org/10.1007/s00163-002-0013-1
   Web of Science ®Google Scholar
• Reich, Y., Hatchuel, A., Shai, O., & Subrahmanian, E. (2012). A theoretical analysis of creativity methods in engineering design: Casting an improving ASIT within C-K theory. Journal of Engineering Design, 23(2), 137–158. https://doi.org/10.1080/09544828.2010.493505
   Web of Science ®Google Scholar
• Renner, G., & Ekárt, A. (2003). Genetic algorithms in computer aided design. Computer-Aided Design, 35(8), 709–726. https://doi.org/10.1016/S0010-4485(03)00003-4
   Web of Science ®Google Scholar
• Rhino: Rhinoceros. (2022). Retrieved May 5, 2023, from https://www.rhino3d.com/
   Google Scholar
• Robertson, B. F., & Radcliffe, D. F. (2009). Impact of CAD tools on creative problem solving in engineering design. Computer-Aided Design, 41(3), 136e146. https://doi.org/10.1016/j.cad.2008.06.007
   Web of Science ®Google Scholar
• Salone Del Mobile, M., (2022). Retrieved May 5, 2023, from https://www.salonemilano.it/en/prodotti/kartell/ai-stooloverview
   Google Scholar
• Sarkar, P., & Chakrabarti, A. (2011). Assessing design creativity. Design Studies, 32(4), 348–383. https://doi.org/10.1016/j.destud.2011.01.002
   Web of Science ®Google Scholar
• Sbrugnera Sotomayor, N. A., Caiazzo, F., & Alfieri, V. (2021). Enhancing design for additive manufacturing workflow: Optimization, design and simulation tools. Applied Sciences, 11(14), 6628. https://doi.org/10.3390/app11146628
   Google Scholar
• Shah, J. J., Smith, S. M., & Vargas-Hernandez, N. (2003). Metrics for measuring ideation effectiveness. Design Studies, 24(2), 111–134. https://doi.org/10.1016/s0142-694x(02)00034-0
   Google Scholar
• Singh, V., & Gu, N. (2012). Towards an integrated generative design framework. Design Studies, 33(2), 185–207. https://doi.org/10.1016/j.destud.2011.06.001
   Web of Science ®Google Scholar
• Srinivasan, V., Song, B., Luo, J., Subburaj, K., Elara, M. R., Blessing, L., & Wood, K. (2018). Does analogical distance affect performance of ideation? Journal of Mechanical Design, 140(7), 9. https://doi.org/10.1115/1.4040165
   Web of Science ®Google Scholar
• Starkey, E. M., Menold, J., & Miller, S. R. (2019). When are designers willing to take risks? How concept creativity and prototype fidelity influence perceived risk. Journal of Mechanical Design, 141(3), 8. https://doi.org/10.1115/1.40423.39
   Web of Science ®Google Scholar
• Sternberg, R. J., & Lubart, T. I. (1999). The concept of creativity: Prospects and paradigms. In J. S. Robert (Ed.), Handbook of creativity (pp. 3–15). Cambridge University Press.
   Google Scholar
• Stiny, G., & Gips, J. (1978). Algorithmic aesthetics. University of California Press.
   Google Scholar
• Sun, H., & Ma, L. (2020). Generative design by using exploration approaches of reinforcement learning in density-based structural topology optimization. Designs, 4(2), 10. https://doi.org/10.3390/designs4020010
   Google Scholar
• Sun, Y., Münster, S., Köhler, T., & Sommer, C. M. (2020). Understanding the industrial designer’s self-perception of ideation. International Journal of Design Creativity & Innovation, 8(4), 240–271. https://doi.org/10.1080/21650349.2020.1813632
   Web of Science ®Google Scholar
• Ulrich, K. T., & Eppinger, S. D. (2011). Product design and development. McGraw-Hill.
   Google Scholar
• Vlah, D., Žavbi, R., & Vukašinović, N. (2020). Evaluation of topology optimization and generative design tools as support for conceptual design. In Proc. Of the design society: Design conf (Vol. 1, pp. 451–460). Cambridge University Press. https://doi.org/10.1017/dsd.2020.165
   Google Scholar
• Wang, K., & Nickerson, J. V. (2017). A literature review on individual creativity support systems. Computers in Human Behavior, 74, 139–151. https://doi.org/10.1016/J.CHB.2017.04.035
   Web of Science ®Google Scholar
• Williams, C. (2013). Origins of form: The shape of natural and man-made things—why they came to Be the way they are and how they change. Architectural Book Publishing.
   Google Scholar
• Wu, J., Quian, X., & Wang, M. Y. (2019). Advances in generative design. Computer-Aided Design, 116, 102733. https://doi.org/10.1016/j.cad.2019.102733
   Web of Science ®Google Scholar
• Yilmaz, S., Daly, S. R., Christian, J. L., Seifert, C. M., & Gonzalez, R. (2014). Can experienced designers learn from new tools? A case study of idea generation in a professional engineering team. International Journal of Design Creativity & Innovation, 2(2), 82–96. https://doi.org/10.1080/21650349.2013.832016
   Google Scholar