Journal of the Korean Society of Clothing and Textiles (한국의류학회지)

The Korean Society of Clothing and Textiles (한국의류학회)
권호 표지
DOI QR코드

DOI QR Code

An AI-based Clothing Design Process Applied to an Industry-university Fashion Design Class

  • Hyosun An (Dept. of Fashion Industry, Ewha Womans University) ;
  • Minjung Park (Dept. of Fashion Industry, Ewha Womans University)
  • Received : 2023.04.07
  • Accepted : 2023.08.01
  • Published : 2023.08.31
Download PDF
⟨ Previous Next ⟩

Abstract

This research aims to develop based clothing design process tailored to the industry-university collaborative setting and apply it in a fashion design class. into three distinct phases: designing and organizing our fashion design class, conducting our class at a university, and gathering student feedback. First, we conducted a literature review on employing new technologies in traditional clothing design processes. We consulted with industry professionals from the Samsung C&T Fashion Group to develop an AI-based clothing design process. We then developed in-class learning activities that leveraged fashion brand product databases, a supervised learning AI model, and operating an AI-based Creativity Support Tool (CST). Next, we setup an industry-university fashion design class at a university in South Korea. Finally, we obtained feedback from undergraduate students who participated in the class. The survey results showed a satisfaction level of 4.7 out of 5. The evaluations confirmed that the instructional methods, communication, faculty, and student interactions within the class were both adequate and appropriate. These research findings highlighted that our AI-based clothing design process applied within the fashion design class led to valuable data-driven convergent thinking and technical experience beyond that of traditional clothing design processes.

Keywords

Acknowledgement

The authors sincerely thank the Samsung C&T Fashion Group for their invaluable support and collaboration in developing and conducting the industry-university collaborative class. The authors would like to thank all the students who actively participated in the class, especially Yeeun Kim, Soomin Lee, and Yoonje Cho, for allowing some of their exemplary in-class outcomes in the paper.

References

  1. Alipour, L., Faizi, M., Moradi, A. M., & Akrami, G. (2018). A review of design fixation: Research directions and key factors. International Journal of Design Creativity and Innovation, 6(1-2), 22-35. https://doi.org/10.1080/21650349.2017.1320232 
  2. An, H., Lee, K. Y., Choi, Y., & Park, M. (2023). Conceptual framework of hybrid style in fashion image datasets for machine learning. Fashion and Textiles, 10(1), 1-18. https://doi. org/10.1186/s40691-023-00338-8 
  3. An, H., & Park, M. (2021). A case study on an artificial intelligence fashion curation practice subject through industrialacademic project-based learning. Fashion & Textile Research Journal, 23(3), 337-346. https://doi.org/10.5805/SFTI.2021.23.3.337 
  4. Arthur, R. (2018, January 15). Artificial intelligence empowers designers in IBM, Tommy Hilfiger and FIT collaboration. Forbes. https://www.forbes.com/sites/rachelarthur/2018/01/15/ai-ibm-tommy-hilfiger 
  5. Barnes, T., Pashby, I., & Gibbons, A. (2002). Effective university-industry interaction: A multi-case evaluation of collaborative R&D projects. European Management Journal, 20 (3), 272-285. https://doi.org/10.1016/S0263-2373(02)00044-0 
  6. Butcher, J., & Jeffrey, P. (2007). A view from the coal face: UK research student perceptions of successful and unsuccessful collaborative projects. Research Policy, 36(8), 1239-1250. https://doi.org/10.1016/j.respol.2007.04.009 
  7. Bye, E. (2010). A direction for clothing and textile design research. Clothing and Textiles Research Journal, 28(3), 205-217. https://doi.org/10.1177/0887302X10371505 
  8. Bye, E. K., & DeLong, M. R. (1994). A visual sensory evaluation of the results of two pattern grading methods. Clothing and Textiles Research Journal, 12(4), 1-7. https://doi.org/10.1177/0887302X9401200401 
  9. Campbell, J. (2022, December 28). In Hong Kong, designers try out new assistant: AI fashion maven AiDA. Reuters. https://www.reuters.com/technology/hong-kong-designers-try-out-new-assistant-ai-fashion-maven-aida-2022-12-27/
  10. Centra, J. A. (1977). Student ratings of instruction and their relationship to student learning. American Educational Research Journal, 14(1), 17-24. https://doi.org/10.3102/00028312014001017 
  11. Centra, J. A. (2005). The development of the student instructional report II. Educational Testing Service. (Original work published 1998) 
  12. Christel, D. A. (2016). The efficacy of problem-based learning of plus-size design in the fashion curriculum. International Journal of Fashion Design, Technology and Education, 9(1), 1-8. https://doi.org/10.1080/17543266.2015.1094518 
  13. Chung, E. H., & Choi, J. M. (2022). Directions for AI-based tools to support designers' work process. Archives of Design Research, 35(4), 269-282. https://doi.org/10.15187/adr.2022.11.35.4.269 
  14. Colson, E. (2013, November 7-9). Using human and machine processing in recommendation systems [Paper presentation]. AAAI Conference on Human Computation and Crowdsourcing, California, United States. https://doi.org/10.1609/hcomp.v1i1.13100 
  15. Crilly, N. (2015). Fixation and creativity in concept development: The attitudes and practices of expert designers. Design Studies, 38, 54-91. https://doi.org/10.1016/j.destud.20 15.01.002 
  16. Crilly, N., & Cardoso, C. (2017). Where next for research on fixation, inspiration and creativity in design? Design Studies, 50, 1-38. https://doi.org/10.1016/j.destud.2017.02.001 
  17. Dudley, J. J., & Kristensson, P. O. (2018). A review of user interface design for interactive machine learning. ACM Transactions on Interactive Intelligent Systems (TiiS), 8(2), 1-37. https://doi.org/10.1145/3185517 
  18. Frich, J., MacDonald Vermeulen, L., Remy, C., Biskjaer, M. M., & Dalsgaard, P. (2019, May 4-9). Mapping the landscape of creativity support tools in HCI [Paper presentation]. CHI Conference on Human Factors in Computing Systems. Glasgow, Scotland, United Kingdom. https://doi.org/10.1145/3290605.3300619 
  19. Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education, The Center for Curriculum Redesign.
  20. Jansson, D. G., & Smith, S. M. (1991). Design fixation. Design Studies, 12(1), 3-11. https://doi.org/10.1016/0142-694X(91)90003-F 
  21. Jeon, Y., Jin, S., Shih, P. C., & Han, K. (2021, May 8-13). FashionQ: An AI-driven creativity support tool for facilitating ideation in fashion design. CHI Conference on Human Factors in Computing Systems, Yokohama, Japan. https://doi.org/10.1145/3411764.3445093 
  22. Jeong, W.-J., & Kim, S.-I. (2018). A study on the role of designer in the 4th industrial revolution: Focusing on design process and AI based design software. Journal of Digital Convergence, 16(8), 279-285. https://doi.org/10.14400/JD C.2018.16.8.279 
  23. Kim, H. S., Jun, S., Choi, S., & Kim, S. (2020). Development and application of education program on understanding artificial intelligence and social impact. The Journal of Korean Association of Computer Education, 23(2), 21-29. https://doi.org/10.32431/kace.2020.23.2.003 
  24. Kim, S., Kim, S., & Kim, H. (2019, August 8-9). Analysis of international educational trends and learning tools for artificial intelligence education [Paper presentation]. The Korean Association of Computer Education, Anyang, Korea. 
  25. Koon, J., & Murray, H. G. (1995). Using multiple outcomes to validate student ratings of overall teacher effectiveness. The Journal of Higher Education, 66(1), 61-81. https://doi.org/10.1080/00221546.1995.11774757 
  26. Laamanen, T. K., & Seitamaa-Hakkarainen, P. (2014). Interview study of professional designers' ideation approaches. The Design Journal, 17(2), 194-217. https://doi.org/10.275 2/175630614X13915240575988  https://doi.org/10.2752/175630614X13915240575988
  27. LaBat, K. L., & Sokolowski, S. L. (1999). A three-stage design process applied to an industry-university textile product design project. Clothing and Textiles Research Journal, 17(1), 11-20. https://doi.org/10.1177/0887302X990170010 
  28. Lamb, J. M., & Kallal, M. J. (1992). A conceptual framework for apparel design. Clothing and Textiles Research Journal, 10(2), 42-47. https://doi.org/10.1177/0887302X9201000207 
  29. Lee, E. (2020). A comparative analysis of contents related to artificial intelligence in national and international K-12 curriculum. The Journal of Korean Association of Computer Education, 23(1), 37-44. https://doi.org/10.32431/kace.2020.23.1.003 
  30. Lee, W. (2020). Fashion design education using deep dream generator in intelligence information society. Journal of the Korean Society of Design Culture, 26(2), 429-446. https://doi.org/10.18208/ksdc.2020.26.2.429 
  31. Liu, Z., Luo, P., Qiu, S., Wang, X., & Tang, X. (2016, June 27-30). Deepfashion: Powering robust clothes recognition and retrieval with rich annotations [Paper presentation]. IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, United States. https://doi.org/10.1109/CVPR.2016.124 
  32. Marsh, H. W. (1984). Students' evaluations of university teaching: Dimensionality, reliability, validity, potential baises, and utility. Journal of Educational Psychology, 76(5), 707-754. https://doi.org/10.1037/0022-0663.76.5.707 
  33. Merryman, L., & Lu, S. (2021). Are fashion majors ready for the era of data science? A study on the fashion undergraduate curriculums in US institutions. International Journal of Fashion Design, Technology and Education, 14(2), 139-150. https://doi.org/10.1080/17543266.2021.1884752 
  34. Nakakoji, K. (2006, November 10-11). Meanings of tools, support, and uses for creative design processes [Paper presentation]. International Design Research Symposium, Seoul, Korea. 
  35. Parsons, J. L., & Campbell, J. R. (2004). Digital apparel design process: Placing a new technology into a framework for the creative design process. Clothing and Textiles Research Journal, 22(1-2), 88-98. https://doi.org/10.1177/0887302X040220011 
  36. Perkmann, M., Tartari, V., McKelvey, M., Autio, E., Brostrom, A., D'este, P., Fini, R., Geuna, A., Grimaldi, R., Hughes, A., Krabel, S., Kitson, M., Llerena, P., Lissoni, F., Salter, A., & Sobrero, M. (2013). Academic engagement and commercialisation: A review of the literature on university-industry relations. Research Policy, 42(2), 423-442. https://doi.org/10.1016/j.respol.2012.09.007 
  37. Regan, C. L., Kincade, D. H., & Sheldon, G. (1998). Applicability of the engineering design process theory in the apparel design process. Clothing and Textiles Research Journal, 16(1), 36-46. https://doi.org/10.1177/0887302X9801600105 
  38. Rietze, A. (2016, September 2). Project Muse: Fashion inspired by you, designed by code. Google. https://blog.google/arou nd-the-globe/google-europe/project-muze-fashion-inspired-by-you/
  39. Seo, Y., & Shin, K.-S. (2019). Hierarchical convolutional neural networks for fashion image classification. Expert Systems with Applications, 116, 328-339. https://doi.org/10.1016/j.eswa.2018.09.022 
  40. Shahrubudin, N., Lee, T. C., & Ramlan, R. (2019). An overview on 3D printing technology: Technological, materials, and applications. Procedia Manufacturing, 35, 1286-1296. https://doi.org/10.1016/j.promfg.2019.06.089 
  41. Tyler, D. J. (2011). Digital printing technology for textiles and apparel. Computer Technology for Textiles and Apparel, 259-282. https://doi.org/10.1533/9780857093608.3.259 
  42. Yan, H., Zhang, H., Liu, L., Zhou, D., Xu, X., Zhang, Z., & Yan, S. (2022). Toward intelligent design: An AI-based fashion designer using generative adversarial networks aided by sketch and rendering generators. IEEE Transactions on Multimedia. 25, 2323-2338. https://doi.org/10.1109/TMM. 2022.3146010 
  43. Zhao, L., Li, M., & Sun, P. (2021). Neo-fashion: A data-driven fashion trend forecasting system using catwalk analysis. Clothing and Textiles Research Journal, 0887302X211004 299. https://doi.org/10.1177/0887302X211004299