4.7 Review

Topology optimization for metal additive manufacturing: current trends, challenges, and future outlook

期刊

VIRTUAL AND PHYSICAL PROTOTYPING
卷 18, 期 1, 页码 -

出版社

TAYLOR & FRANCIS LTD
DOI: 10.1080/17452759.2023.2181192

关键词

Metal additive manufacturing; additive manufacturing; topology optimisation; aerospace; automotive; medical

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Metal additive manufacturing is actively researched, focusing on physics, statistical and AI-driven process modeling and optimization, structure-property characterization, design optimization, and equipment enhancements. This review specifically addresses the utilization of topology optimization in metal additive manufacturing, including its applications in aerospace, medical, automotive, and other industries, support structure design for thermal-based powder-bed processes, manufacturing constraints and porous feature generation in topology optimization, as well as the adoption of AI models. Open-source and commercial software for topology optimization and metal additive manufacturing are also explored, with considerations given to future research directions and challenges.
Metal additive manufacturing is gaining immense research attention. Some of these research efforts are associated with physics, statistical, or artificial intelligence-driven process modelling and optimisation, structure-property characterisation, structural design optimisation, or equipment enhancements for cost reduction and faster throughputs. In this review, the focus is drawn on the utilisation of topology optimisation for structural design in metal additive manufacturing. First, the symbiotic relationship between topology optimisation and metal additive manufacturing in aerospace, medical, automotive, and other industries is investigated. Second, support structure design by topology optimisation for thermal-based powder-bed processes is discussed. Third, the introduction of capabilities to limit manufacturing constraints and generate porous features in topology optimisation is examined. Fourth, emerging efforts to adopt artificial intelligence models are examined. Finally, some open-source and commercial software with capabilities for topology optimisation and metal additive manufacturing are explored. This study considers the challenges faced while providing perceptions on future research directions.

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