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Machine Learning for Additive Manufacturing

Research output: Contribution to journalLiterature reviewpeer-review

Published
<mark>Journal publication date</mark>19/07/2021
<mark>Journal</mark>Encyclopedia
Issue number3
Volume1
Number of pages13
Pages (from-to)576-588
Publication StatusPublished
<mark>Original language</mark>English

Abstract

Additive manufacturing (AM) is the name given to a family of manufacturing processes where materials are joined to make parts from 3D modelling data, generally in a layer-upon-layer manner. AM is rapidly increasing in industrial adoption for the manufacture of end-use parts, which is therefore pushing for the maturation of design, process, and production techniques. Machine learning (ML) is a branch of artificial intelligence concerned with training programs to self-improve and has applications in a wide range of areas, such as computer vision, prediction, and information retrieval. Many of the problems facing AM can be categorised into one or more of these application areas. Studies have shown ML techniques to be effective in improving AM design, process, and production but there are limited industrial case studies to support further development of these techniques.