Artificial Intelligence for Control in Laser-Based Additive Manufacturing: A Systematic Review

• Tipo: Artigo em Revista Científica Internacional
• Data: 2025

Autores

Sousa, J (Autor) Outra; Brandau, B (Autor) Outra; Darabi, R (Autor) Outra; Armando Jorge Sousa (Autor) FEUP; Brueckner, F (Autor) Outra; Ana Reis (Autor) FEUP; reis, lp (Autor) FEUP

Revista

Título: IEEE Access

Vol. 13

ISSN: 2169-3536

Editora: IEEE

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 0 Citações

Outras Informações

ID Authenticus: P-018-1M1

DOI: 10.1109/access.2025.3537859

Abstract (EN): Laser-based additive manufacturing (LAM) offers the ability to produce near-net-shape metal parts with unparalleled energy efficiency and flexibility in both geometry and material selection. Despite advantages, these processes are inherently, as they are characterized by multiphysics interactions, multiscale phenomena, and highly dynamic behaviors, making their modeling and optimization particularly challenging. Artificial intelligence (AI) has emerged as a promising tool for enhancing the monitoring and control of additive manufacturing. This paper presents a systematic review of AI applications for real-time control of laser-based manufacturing processes, analyzing 16 relevant articles sourced from Scopus, IEEE Xplore, and Web of Science databases. The primary objective of this work is to contribute to the advancement of autonomous manufacturing systems capable of self-monitoring and self-correction, ensuring optimal part quality, enhanced efficiency, and reduced human intervention. Our findings indicate that 62.5 % of the 16 analyzed studies have deployed AI-driven controllers in real-world scenarios, with over 56 % using AI for control strategies, such as Reinforcement Learning. Furthermore, 62.5 % of the studies employed AI for process modeling or monitoring, which was integral to the development or data pipelines of the controllers. By defining a groundwork for future developments, this review not only highlights current advancements but also hints future innovations that will likely include AI-based controllers.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 16