Using machine learning to aid in the parameter optimisation process for metal-based additive manufacturing

• Published in: Rapid prototyping journal Vol. 26; no. 4; pp. 625 - 637
• Main Authors: Silbernagel, Cassidy, Aremu, Adedeji, Ashcroft, Ian
• Format: Journal Article
• Language: English
• Published: Bradford Emerald Publishing Limited 14.05.2020; Emerald Group Publishing Limited
• Subjects: Additive manufacturing; Algorithms; Artificial intelligence; Clustering; Copper; Lasers; Machine learning; New technology; Optimization; Powder beds; Printers (data processing); Process controls; Process parameters; Rapid prototyping; Workflow; United Kingdom > UK; Laser powder bed fusion; Additive manufacturing; Parameter optimization; Artificial intelligence; 3D printing; Machine learning

Purpose Metal-based additive manufacturing is a relatively new technology used to fabricate metal objects within an entirely digital workflow. However, only a small number of different metals are proven for this process. This is partly due to the need to find a new set of parameters which can be use...