In situations requiring high levels of customization and limited production volumes, additive manufacturing (AM) is a frequently utilized technique with several benefits. To properly configure all the parameters required to produce final goods of the utmost quality, AM calls for qualified designers and experienced operators. This research demonstrates how, in this scenario, artificial intelligence (AI) could significantly enable designers and operators to enhance additive manufacturing. Thus, 48 papers have been selected from the comprehensive collection of research using a systematic literature review to assess the possibilities that AI may bring to AM. This review aims to better understand the current state of AI methodologies that can be applied to optimize AM technologies and the potential future developments and applications of AI algorithms in AM. Through a detailed discussion, it emerges that AI might increase the efficiency of the procedures associated with AM, from simulation optimization to in-process monitoring.

Optimization with artificial intelligence in additive manufacturing: a systematic review / Ciccone F.; Bacciaglia A.; Ceruti A.. - In: JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING. - ISSN 1678-5878. - ELETTRONICO. - 45:6(2023), pp. 303.1-303.22. [10.1007/s40430-023-04200-2]

Optimization with artificial intelligence in additive manufacturing: a systematic review

Ciccone F.
Writing – Original Draft Preparation
;
Bacciaglia A.
Writing – Review & Editing
;
Ceruti A.
Supervision
2023

Abstract

In situations requiring high levels of customization and limited production volumes, additive manufacturing (AM) is a frequently utilized technique with several benefits. To properly configure all the parameters required to produce final goods of the utmost quality, AM calls for qualified designers and experienced operators. This research demonstrates how, in this scenario, artificial intelligence (AI) could significantly enable designers and operators to enhance additive manufacturing. Thus, 48 papers have been selected from the comprehensive collection of research using a systematic literature review to assess the possibilities that AI may bring to AM. This review aims to better understand the current state of AI methodologies that can be applied to optimize AM technologies and the potential future developments and applications of AI algorithms in AM. Through a detailed discussion, it emerges that AI might increase the efficiency of the procedures associated with AM, from simulation optimization to in-process monitoring.
2023
Optimization with artificial intelligence in additive manufacturing: a systematic review / Ciccone F.; Bacciaglia A.; Ceruti A.. - In: JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING. - ISSN 1678-5878. - ELETTRONICO. - 45:6(2023), pp. 303.1-303.22. [10.1007/s40430-023-04200-2]
Ciccone F.; Bacciaglia A.; Ceruti A.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/926595
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