FROM CONCEPT TO CREATION: LEVERAGING ARTIFICIAL INTELLIGENCE IN MECHANICAL DESIGN AND IDEATION

11th International Scientific Conference Research and Development of Mechanical Elements and Systems IRMES (2025) [pp. III-XI]  

AUTHOR(S) / АУТОР(И): Jasmin KALJUN , Andrej CUPAR, Klavdija KOPŠE KALJUN

Download Full Pdf   

DOI: 10.46793/IRMES25.plA2K

ABSTRACT / САЖЕТАК:

This paper explores the integration of artificial intelligence (AI) into mechanical design workflows, with a focus on improving ideation, creativity and iterative development. Traditional design processes, limited by sequential workflows, time-consuming iterations and reliance on intuition, are increasingly unable to cope with the complexity and pace of modern product development. To overcome these limitations, an AI-driven design framework is proposed that consists of four interconnected components: generative design algorithms, surrogate modelling and performance prediction, data-driven decision support, and a human-AI interaction layer. The framework is validated through two case studies: the generative design of an ergonomic armrest optimised for additive manufacturing and biomechanical performance, and an educational study investigating the impact of AI-assisted sketching (Vizcom) on student creativity in sustainable product design. The results show that iteration was accelerated, design diversity improved, and user engagement increased. In addition to presenting the technical results, the paper builds on the author’s previous research on intelligent ergonomic and aesthetic guidance systems and provides a long-term perspective on the development of AI-powered design tools. The discussion emphasises the need for human-centred AI, robust data infrastructures and ethical accountability. The paper concludes with an outlook on future directions in adaptive AI learning, training and responsible implementation in technical practise.

KEYWORDS / КЉУЧНЕ РЕЧИ:

AI-driven design; generative design; design iteration; human-AI collaboration; ergonomic optimization

ACKNOWLEDGEMENT / ПРОЈЕКАТ:

The authors acknowledge the financial support from the Slovenian Research and Innovation Agency (Research Core Funding No. P2-0063).

REFERENCES / ЛИТЕРАТУРА:

  • Wynn, C., Eckert, C.M.: Perspectives on iteration in design and development. Res Eng Des, 28 (2), pp. 153–184, 2017
  • Young, M.T.: Intuition and Ineffability: Tacit Knowledge and Engineering Design. Philosophy of Engineering and Technology, 31, pp. 53–67, 2018
  • Sheng, I.L.S.: Improving Product Ideation Among Engineering Undergraduates Using TRIZ and Design Thinking. 2023 IEEE 12th International Conference on Engineering Education, ICEED 2023, pp. 41–43, 9798350307429, 2023
  • Wang, Q. et al.: Conceptual Design Method for Mechanical Products Based on Historical 3D Model Design Knowledge. Mechanisms and Machine Science, 155 MMS, pp. 377–396, 978-981-97-0922-9, 2024
  • Saadi, J.I., Yang, M.C.: Generative Design: Reframing the Role of the Designer in Early-Stage Design Process. Journal of Mechanical Design, 145 (4), 2023
  • Yoo, S. et al.: Integrating Deep Learning into CAD/CAE System: Generative Design and Evaluation of 3D Conceptual Wheel. Structural and Multidisciplinary Optimization, 64 (4), 2725–2747, 2020
  • Song, B. et al.: Human-AI collaboration by design. Proceedings of the Design Society, 4, pp. 2247–2256, 2024
  • Brey, P., Dainow, B.: Ethics by design for artificial intelligence. AI and Ethics 2023 4:4, 4 (4), pp. 1265–1277, 0123456789, 2023
  • Kaljun, J., Dolšak, B.: Ergonomic design knowledge built in the intelligent decision support system. Int J Ind Ergon, 42 (1), pp. 162–171, 2012
  • Kaljun, J., Dolšak, B.: Improving products’ ergonomic value using intelligent decision support system. StrojniskiVestnik/Journal of Mechanical Engineering, 58 (4), pp. 271–280, 2012
  • Kaljun, et al.: Intelligent support used for providing a pleasant user experience. 2014 37th International Convention on Information and Communication Technology, Electronics and Microelectronics, MIPRO 2014 – Proceedings, pp. 1083–1087, 9789532330816, 2014
  • Kaljun, et al.: Aesthetics as parameter of intelligent design support. DS 70: Proceedings of DESIGN 2012, the 12th International Design Conference, Dubrovnik, Croatia, pp. 1293–1300, 2012
  • Bremer, F. et al.: Analyzing iterations in mechanical design processes – A method for data acquisition in meso-level studies. Procedia CIRP, 100, pp. 756– 761, 2021
  • Dugan, E., Daly, S.R.: Investigation of Mechanical Engineering Students’ Perceptions of Design Process Models. Proceedings of  the  ASME  Design Engineering Technical Conference, 9780791886267, 2022
  • Gerschütz, B. et al.: Digital Engineering Methods in Practical Use during Mechatronic Design Designs 2023, Vol. 7, Page 93, 7 (4), pp. 93, 2023
  • Young, M.T.: Intuition and Ineffability: Tacit Knowledge and Engineering Design. Philosophy of Engineering and Technology, 31, pp. 53–67, 2018
  • Lockhart, E.N.S.: Creativity in the age of AI: the human condition and the limits of machine generation. J Cult Cogn Sci, 2024
  • Koul, P.: A Review of Generative Design Using Machine Learning for Additive Manufacturing. Advances in Mechanical and Materials Engineering, 41, pp. 145–159, 2024
  • Shi, L. et al.: Deep Learning-Based Multifidelity Surrogate Modeling for High-Dimensional Reliability Prediction. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 10 (3), 2024
  • Abdeen, H. et al.: Multi-objective optimization in rule-based design space exploration. ASE 2014 – Proceedings of the 29th ACM/IEEE International Conference on Automated Software Engineering, pp. 289–300 9781450330138, 2014
  • Figoli, F.A. et al.: AI in the design process: training the human-ai collaboration. DS 117: Proceedings of the 24th International Conference on Engineering and Product Design Education (E&PDE 2022), London South Bank University in London, UK. 8th – 9th September 2022, 978-1-912254-16-3, 2022
  • Ethics By Design and Ethics of Use Approaches for Artificial Intelligence. 2021
  • Kaljun, K.K., Kaljun, J.: Enhancing Creativity in Sustainable Product Design: The Impact of Generative AI Tools at the Conceptual Stage. 47th ICT and Electronics Convention, MIPRO 2024 – Proceedings, pp. 451–456, 9798350382495, 2024