Hostname: page-component-586b7cd67f-vdxz6 Total loading time: 0 Render date: 2024-11-22T17:36:23.801Z Has data issue: false hasContentIssue false

ENHANCING ENGINEERING CREATIVITY WITH AUTOMATED FORMULATION OF ELEMENTARY SOLUTION PRINCIPLES

Published online by Cambridge University Press:  19 June 2023

Pavel Livotov*
Affiliation:
Offenburg University of Applied Sciences
*
Livotov, Pavel, Offenburg University of Applied Sciences, Germany, [email protected]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Several researchers have reported on the effectiveness of knowledge-based inventive stimuli, known in the Theory of Inventive Problem Solving (TRIZ), in enhancing engineering creativity, but few authors have focused on the comparative analysis of structured ideation in engineering design in terms of quantitative and qualitative outcomes. Previous studies have mainly concentrated on the investigation of exemplary selected single stimuli rather than on a critical assessment of the relationship between the structured application of inventive stimuli and their contribution to engineering design. The paper describes a method for the automated formulation of elementary creative stimuli for product or process design at different levels of abstraction and in different engineering domains. The experimental study evaluates the impact of structured automated idea generation on inventive thinking in engineering design and compares it with previous experimental studies in educational and industrial settings. The outlook highlights the benefits of using automated ideation in the context of AI-assisted invention and innovation.

Type
Article
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2023. Published by Cambridge University Press

References

Altshuller, G.S. (1984), Creativity as an exact science: the theory of the solution of inventive problems, Gordon and Breach Science Publishers, New York, ISSN 0275-5807.CrossRefGoogle Scholar
Belski, I., Skiadopoulos, A., Aranda-Mena, G., Cascini, G., Russo, D. (2019), “Engineering Creativity: The Influence of General Knowledge and Thinking Heuristics”, In: Chechurin, L., Collan, M. (eds), Advances in Systematic Creativity, Palgrave Macmillan, Cham, pp. 245263. https://doi.org/10.1007/978-3-319-78075-7_15.CrossRefGoogle Scholar
Borgianni, Y., Fiorineschi, L., Frillici, F., Rotini, F. (2021), “The process for individuating TRIZ Inventive Principles: Deterministic, stochastic or domain-oriented?”, Design Science, 7, E12. https://dx.doi.org/10.1017/dsj.2021.12 (2021).CrossRefGoogle Scholar
Sekaran, Chandra, Livotov, A.P., Mas'udah, P. (2019), “Classification of TRIZ Inventive Principles and Sub-principles for Process Engineering Problems”. In: Benmoussa, R., De Guio, R., Dubois, S., Koziołek, S. (eds.), New Opportunities for Innovation Breakthroughs for Developing Countries and Emerging Economies, IFIP Advances in Information and Communication Technology, vol. 572, pp. 314327. Springer, Cham. https://doi.org/10.1007/978-3-030-32497-1_26.Google Scholar
Diehl, M., Stroebe, W. (1991), “Productivity loss in idea-generating groups: Tracking down the blocking effect”, Journal of Personality and Social Psychology, vol. 61, No. 3, pp. 392403.CrossRefGoogle Scholar
Georgiev, G.V., Sumitani, N., Taura, T. (2016), “Methodology for creating new scenes through the use of thematic relations for innovative designs”, International Journal of Design Creativity and Innovation, vol. 5:12, pp. 78–94, https://doi.org/10.1080/21650349.2015.1119658.Google Scholar
Han, J., Shi, F., Chen, L., Childs, P.R.N. (2018), “A computational tool for creative idea generation based on analogical reasoning and ontology”, Artificial Intelligence for Engineering Design, Analysis and Manufacturing, vol. 32, pp. 462477, https://doi.org/10.1017/S0890060418000082.CrossRefGoogle Scholar
Han, J., Sarica, S., Shi, F., Luo, J. (2021), “Semantic networks for engineering design: a survey”, Proceedings of the Design Society, 1, 26212630. https://dx.doi.org/10.1017/pds.2021.523.CrossRefGoogle Scholar
Livotov, P., Chandra Sekaran, A.P., Mas'udah, (2019a), “Lower Abstraction Level of TRIZ Inventive Principles Improves Ideation Productivity of Engineering Students”. In: Benmoussa, R., De Guio, R., Dubois, S., Koziołek, S. (eds.) New Opportunities for Innovation Breakthroughs for Developing Countries and Emerging Economies, IFIP Advances in Information and Communication Technology, vol 572, pp. 526538. Springer, Cham. https://doi.org/10.1007/978-3-030-32497-1_41 (2019).Google Scholar
Livotov, P., Chandra Sekaran, A.P., Mas'udah, Law, R., Reay, D., Sarsenova, A. and Sayyareh, S. (2019b), “Eco-innovation in Process Engineering: Contradictions, Inventive Principles and Methods”, Thermal Science and Engineering Progress, Vol. 9, pp. 5265, https://doi.org/10.1016/j.tsep.2018.10.012.CrossRefGoogle Scholar
Petrov, V. (2018), Universal Inventive Principles TRIZ: Inventive principles for all fields, Kindle Edition, ASIN: B07CRRY99N, 226 p.Google Scholar
Russo, D., Spreafico, C. (2016), “TRIZ 40 Inventive principles classification through FBS ontology”, Procedia Engineering, 131, pp. 737746, https://doi.org/10.1016/j.proeng.2015.12.367.CrossRefGoogle Scholar
Saliminamin, S., Becattini, N. & Cascini, G. (2019), “Sources of creativity stimulation for designing the next generation of technical systems: correlations with R&D designers’ performance”, Research in Engineering Design, vol. 30, pp. 133153. https://doi.org/10.1007/s00163-018-0299-2CrossRefGoogle Scholar
Sarica, S., Song, B., Luo, J., Wood, K.L. (2021), “Idea generation with Technology Semantic Network”, Artificial Intelligence for Engineering Design, Analysis and Manufacturing, vol. 35, pp. 265283, https:// doi.org/10.1017/S0890060421000020.CrossRefGoogle Scholar
Shah, J. J., Vargas-Hernandez, N., Smith, S.M. (2003), “Metrics for measuring ideation effectiveness”, Design Studies, 24(2), pp. 111134.CrossRefGoogle Scholar
VDI (2016), VDI Standard 4521. Inventive problem solving with TRIZ. Fundamentals, terms and definitions, Beuth Publishers, Duesseldorf, Germany.Google Scholar