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Machine Learning for Additive Manufacturing

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Machine Learning for Additive Manufacturing. / Grierson, Dean; Rennie, Allan; Quayle, Stephen.

In: Encyclopedia, Vol. 1, No. 3, 19.07.2021, p. 576-588.

Research output: Contribution to journalLiterature reviewpeer-review

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@article{8f74b1d40b5842949042069f4a73d63a,
title = "Machine Learning for Additive Manufacturing",
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.",
keywords = "machine learning, supervised learning, unsupervised learning, reinforcement learning, additive manufacturing, design for additive manufacturing, additive manufacturing process, additive manufacturing monitoring",
author = "Dean Grierson and Allan Rennie and Stephen Quayle",
year = "2021",
month = jul,
day = "19",
doi = "10.3390/encyclopedia1030048",
language = "English",
volume = "1",
pages = "576--588",
journal = "Encyclopedia",
issn = "2309-3366",
publisher = "MDPI Multidisciplinary Digital Publishing Institute",
number = "3",

}

RIS

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 -