From concept to manufacturing: evaluating vision-language models for engineering design
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| Publicat a: | The Artificial Intelligence Review vol. 58, no. 9 (Sep 2025), p. 288 |
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| Autor principal: | |
| Altres autors: | , , , , , |
| Publicat: |
Springer Nature B.V.
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| Matèries: | |
| Accés en línia: | Citation/Abstract Full Text Full Text - PDF |
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| 003 | UK-CbPIL | ||
| 022 | |a 0269-2821 | ||
| 022 | |a 1573-7462 | ||
| 024 | 7 | |a 10.1007/s10462-025-11290-y |2 doi | |
| 035 | |a 3226019174 | ||
| 045 | 2 | |b d20250901 |b d20250930 | |
| 084 | |a 68693 |2 nlm | ||
| 100 | 1 | |a Picard, Cyril |u Massachusetts Institute of Technology, Department of Mechanical Engineering, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786) | |
| 245 | 1 | |a From concept to manufacturing: evaluating vision-language models for engineering design | |
| 260 | |b Springer Nature B.V. |c Sep 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Engineering design is undergoing a transformative shift with the advent of AI, marking a new era in how we approach product, system, and service planning. Large language models have demonstrated impressive capabilities in enabling this shift. Yet, with text as their only input modality, they cannot leverage the large body of visual artifacts that engineers have used for centuries and are accustomed to. This gap is addressed with the release of multimodal vision-language models (VLMs), such as GPT-4V, enabling AI to impact many more types of tasks. Our work presents a comprehensive evaluation of VLMs across a spectrum of engineering design tasks, categorized into four main areas: Conceptual Design, System-Level and Detailed Design, Manufacturing and Inspection, and Engineering Education Tasks. Specifically in this paper, we assess the capabilities of two VLMs, GPT-4V and LLaVA 1.6 34B, in design tasks such as sketch similarity analysis, CAD generation, topology optimization, manufacturability assessment, and engineering textbook problems. Through this structured evaluation, we not only explore VLMs’ proficiency in handling complex design challenges but also identify their limitations in complex engineering design applications. Our research establishes a foundation for future assessments of vision language models. It also contributes a set of benchmark testing datasets, with more than 1000 queries, for ongoing advancements and applications in this field. | |
| 610 | 4 | |a OpenAI | |
| 653 | |a Language | ||
| 653 | |a Vision | ||
| 653 | |a Datasets | ||
| 653 | |a Engineering drawings | ||
| 653 | |a Large language models | ||
| 653 | |a Design engineering | ||
| 653 | |a Engineering education | ||
| 653 | |a Optimization | ||
| 653 | |a Medical research | ||
| 653 | |a Benchmarks | ||
| 653 | |a Natural language processing | ||
| 653 | |a Manufacturability | ||
| 653 | |a Manufacturing | ||
| 653 | |a Automation | ||
| 653 | |a Conceptual design | ||
| 653 | |a Topology optimization | ||
| 653 | |a Cognition & reasoning | ||
| 653 | |a Skills | ||
| 653 | |a Artifacts | ||
| 653 | |a Models | ||
| 653 | |a Engineering | ||
| 653 | |a Competence | ||
| 653 | |a Research design | ||
| 653 | |a Tasks | ||
| 653 | |a Language planning | ||
| 653 | |a Language shift | ||
| 653 | |a Language modeling | ||
| 653 | |a Research applications | ||
| 653 | |a Educational systems | ||
| 653 | |a Evaluation | ||
| 700 | 1 | |a Edwards, Kristen M. |u Massachusetts Institute of Technology, Department of Mechanical Engineering, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786) | |
| 700 | 1 | |a Doris, Anna C. |u Massachusetts Institute of Technology, Department of Mechanical Engineering, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786) | |
| 700 | 1 | |a Man, Brandon |u Massachusetts Institute of Technology, Department of Mechanical Engineering, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786) | |
| 700 | 1 | |a Giannone, Giorgio |u Massachusetts Institute of Technology, Department of Mechanical Engineering, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786); Technical University of Denmark, Department of Applied Mathematics and Computer Science, Lyngby, Denmark (GRID:grid.5170.3) (ISNI:0000 0001 2181 8870) | |
| 700 | 1 | |a Alam, Md Ferdous |u Massachusetts Institute of Technology, Department of Mechanical Engineering, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786) | |
| 700 | 1 | |a Ahmed, Faez |u Massachusetts Institute of Technology, Department of Mechanical Engineering, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786) | |
| 773 | 0 | |t The Artificial Intelligence Review |g vol. 58, no. 9 (Sep 2025), p. 288 | |
| 786 | 0 | |d ProQuest |t ABI/INFORM Global | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3226019174/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3226019174/fulltext/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3226019174/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |