Final published version, 985 KB, PDF document
Available under license: CC BY: Creative Commons Attribution 4.0 International License
Final published version
Licence: CC BY: Creative Commons Attribution 4.0 International License
Research output: Contribution to Journal/Magazine › Literature review › peer-review
Research output: Contribution to Journal/Magazine › Literature review › peer-review
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TY - JOUR
T1 - Machine Learning for Additive Manufacturing
AU - Grierson, Dean
AU - Rennie, Allan
AU - Quayle, Stephen
PY - 2021/7/19
Y1 - 2021/7/19
N2 - 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.
AB - 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.
KW - machine learning
KW - supervised learning
KW - unsupervised learning
KW - reinforcement learning
KW - additive manufacturing
KW - design for additive manufacturing
KW - additive manufacturing process
KW - additive manufacturing monitoring
U2 - 10.3390/encyclopedia1030048
DO - 10.3390/encyclopedia1030048
M3 - Literature review
VL - 1
SP - 576
EP - 588
JO - Encyclopedia
JF - Encyclopedia
SN - 2309-3366
IS - 3
ER -