The human factor in FEM based optimization
Matteo STRANO, Etrugrul KAYA
Abstract. This study explores the impact of human involvement in finite element method (FEM)-based optimization within a structured cooperative learning framework. Using the Numisheet 2025 benchmark as a case study, teams made of graduate engineering students optimized a sheet metal forming process, to enhance material utilization while meeting constraints such as thinning and springback. Despite identical numerical setups and metamodeling tools, substantial variability emerged in solutions, highlighting the influence of human decision-making. The research demonstrates that collaborative approaches integrating human intuition and computational techniques can lead to improved optimization outcomes and offers a foundation for advancing human-centered methodologies in manufacturing optimization.
Keywords
Blank Shape Optimization, Cooperative Learning, Human-Centered Data Science
Published online 5/7/2025, 10 pages
Copyright © 2025 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA
Citation: Matteo STRANO, Etrugrul KAYA, The human factor in FEM based optimization, Materials Research Proceedings, Vol. 54, pp 1587-1596, 2025
DOI: https://doi.org/10.21741/9781644903599-171
The article was published as article 171 of the book Material Forming
Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
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