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Smart lasers for manufacturing of the future

Smart lasers for manufacturing of the future
Smart lasers for manufacturing of the future
Lasers have become ubiquitous across industry and have transformed the manufacturing of components across almost all size scales, from the welding of ships, to the fabrication of micro-sized components. The Artificial Intelligence (AI) revolution has now begun, and no industry will be left untouched. The synergy of laser manufacturing processes, a market projected to grow annually by 8.9% to £23 billion in 2025, with state-of-the-art AI will completely transform the laser processing industry within the next decade. As commercial laser power is sufficient for the majority of manufacturing processes, future growth in this area is anticipated to arise predominantly from the introduction of capabilities such as process monitoring, autonomous control and data services which can be provided remotely via internet connection across the globe.

We are currently exploring the capability of neural networks for the monitoring and correction of laser-based manufacturing in real-time, via computer vision. We will show our latest results for the real-time monitoring of laser and sample parameters, as well as the capability for autonomous completion of manufacturing processes that have high variability. We envisage this technology will play a part in the smart factories of the future connected globally via the internet.
Xie, Yunhui
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Heath, Daniel
d53c269d-90d2-41e6-aa63-a03f8f014d21
Grant-Jacob, James
c5d144d8-3c43-4195-8e80-edd96bfda91b
MacKay, Benita, Scout
318d298f-5b38-43d7-b30d-8cd07f69acd4
McDonnell, Michael, David Tom
bc7b6423-bd77-424d-81e7-4e5448e926cb
Praeger, Matthew
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Eason, Robert
e38684c3-d18c-41b9-a4aa-def67283b020
Mills, Benjamin
05f1886e-96ef-420f-b856-4115f4ab36d0
Xie, Yunhui
f2c3b0e4-8650-4e04-80e5-04505f45bdd6
Heath, Daniel
d53c269d-90d2-41e6-aa63-a03f8f014d21
Grant-Jacob, James
c5d144d8-3c43-4195-8e80-edd96bfda91b
MacKay, Benita, Scout
318d298f-5b38-43d7-b30d-8cd07f69acd4
McDonnell, Michael, David Tom
bc7b6423-bd77-424d-81e7-4e5448e926cb
Praeger, Matthew
84575f28-4530-4f89-9355-9c5b6acc6cac
Eason, Robert
e38684c3-d18c-41b9-a4aa-def67283b020
Mills, Benjamin
05f1886e-96ef-420f-b856-4115f4ab36d0

Xie, Yunhui, Heath, Daniel, Grant-Jacob, James, MacKay, Benita, Scout, McDonnell, Michael, David Tom, Praeger, Matthew, Eason, Robert and Mills, Benjamin (2019) Smart lasers for manufacturing of the future. FEPS IoT Showcase. 05 Apr 2019.

Record type: Conference or Workshop Item (Other)

Abstract

Lasers have become ubiquitous across industry and have transformed the manufacturing of components across almost all size scales, from the welding of ships, to the fabrication of micro-sized components. The Artificial Intelligence (AI) revolution has now begun, and no industry will be left untouched. The synergy of laser manufacturing processes, a market projected to grow annually by 8.9% to £23 billion in 2025, with state-of-the-art AI will completely transform the laser processing industry within the next decade. As commercial laser power is sufficient for the majority of manufacturing processes, future growth in this area is anticipated to arise predominantly from the introduction of capabilities such as process monitoring, autonomous control and data services which can be provided remotely via internet connection across the globe.

We are currently exploring the capability of neural networks for the monitoring and correction of laser-based manufacturing in real-time, via computer vision. We will show our latest results for the real-time monitoring of laser and sample parameters, as well as the capability for autonomous completion of manufacturing processes that have high variability. We envisage this technology will play a part in the smart factories of the future connected globally via the internet.

Full text not available from this repository.

More information

Submitted date: 2019
Published date: 5 April 2019
Venue - Dates: FEPS IoT Showcase, 2019-04-05 - 2019-04-05

Identifiers

Local EPrints ID: 430269
URI: https://eprints.soton.ac.uk/id/eprint/430269
PURE UUID: 93852fd6-64c3-4010-aef3-058d7e6aaa91
ORCID for James Grant-Jacob: ORCID iD orcid.org/0000-0002-4270-4247
ORCID for Benita, Scout MacKay: ORCID iD orcid.org/0000-0003-2050-8912
ORCID for Robert Eason: ORCID iD orcid.org/0000-0001-9704-2204
ORCID for Benjamin Mills: ORCID iD orcid.org/0000-0002-1784-1012

Catalogue record

Date deposited: 23 Apr 2019 16:30
Last modified: 11 May 2019 00:37

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