The synergistic role of additive manufacturing and artificial intelligence for the design of new advanced intelligent systems
Open accessAbstract
Intelligent materials and devices are considered the key to fulfill the strict and challenging requirements given by a large set of applications in numerous fields. The synergistic interplay of additive manufacturing (AM) technologies, specifically 4D‐printing, and artificial intelligence (AI), have widened the design space and accelerated the design phase. 4D‐printing, intended as the combination of 3D‐printing with a fourth dimension (i.e., time), ensures the fabrication of complex topologies with materials that can be selectively triggered to change specific features (e.g., shape, color), whereas the use of smart inks or embedded sensors can bring additional functionalities (e.g., repairing, sensing, actuating) to fulfill the requirements of the targeted application. AI is the tool allowing scientists to train machines for developing human‐like capabilities to discern, predict, and represent the statistically significant behavior of a phenomenon. If applied to the design of smart structures, it can be a powerful and efficient tool capable of reducing the time‐to‐manufacturing, improving the traditional design approach. In this perspective, a viewpoint is provided on how the synergistic use of AI and AM can advance the design of intelligent systems, with successful applications ranging from the robotics to the bioengineering sectors.
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AI and ML can be used to perform quality control checks on manufactured products.
“AI and ML can be used to perform quality control checks on manufactured products [62] .”
From Artificial intelligence, machine learning and deep learning in advanced robotics, a review (2023) · cites this paper as [62]
Cites
Gu, G. X., Chen, C.-T., Richmond, D. J., & Buehler, M. J. (2018) · Materials Horizons · doi:10.1039/c8mh00653a · Cited by 556 · see citing works
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Artificial intelligence, machine learning and deep learning in advanced robotics, a review
Soori, M., Arezoo, B., & Dastres, R. (2023) · Cognitive Robotics · doi:10.1016/j.cogr.2023.04.001 · Cited by 1,131 · see citing works
- Authors
- Milazzo, M., & Libonati, F.
- Affiliations
- University of Pisa (IT)
- University of Genoa (IT)
- Corresponding author
- Libonati, Flavia
- Venue
- Advanced Intelligent Systems
- Publisher
- Wiley
- Published
- 2022-03-19
- Volume
- 4
- Issue
- 6
- ISSN
- 2640-4567 (ISSN-L)
- OpenAlex
- W4220880932
- Cited by
- 43
- References
- 1
- Citations by year
- 2026: 7 · 2025: 15 · 2024: 9 · 2023: 9 · 2022: 3
- FWCI
- 2.40
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Advanced Intelligent Systems (publishedVersion, cc-by)
- CINECA IRIS Institutial research information system (University of Pisa) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- CINECA IRIS Institutial Research Information System (University of Genoa) (submittedVersion, other-oa)
- Funders
- Università degli Studi di Genova
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Additive Manufacturing and 3D Printing Technologies
- Physical Sciences › Engineering › Mechanical Engineering › Advanced Materials and Mechanics
- Physical Sciences › Engineering › Architecture › Architecture and Computational Design
- Keywords
- additive manufacturing, artificial intelligence, 4D printing, smart materials, embedded sensors, shape-changing materials, design space expansion, smart structures, robotics, bioengineering
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