000			03823cam a2200469 i 4500
999			_c95467 _d95467
005			20260507112810.0
006			m o d
007			cr un|---aucuu
008			260507s2025 sz a o 101 0 eng d
020			_a9783031864889
020			_a9783031864896 _q(electronic bk.)
020			_a3031864891 _q(electronic bk.)
020			_z9783031864889
041			_aeng
072		7	_aTJFM _2bicssc
072		7	_aTEC007000 _2bisacsh
082	0	0	_223
111	2		_aEuropean Symposium on Artificial Intelligence in Manufacturing _n(2nd : _d2024 : _cAthens, Greece)
245	1	0	_aAdvances in artificial intelligence in manufacturing II : _bproceedings of the 2nd European Symposium on Artificial Intelligence in Manufacturing, October 16, 2024, Athens, Greece / _cKosmas Alexopoulos, Sotiris Makris, Panagiotis Stavropoulos, editors.
264		1	_aCham : _bSpringer, _c2025.
300			_a1 online resource (xvi, 288 pages) : _billustrations (some color).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
490	1		_aLecture Notes in Mechanical Engineering, _x2195-4364
500			_aIncludes author index.
505	0		_aPart I AI in Process Level -- 1 Digital Twins of manufacturing processes under Industry 5.0 -- 2 Recurrent Convolutional Neural Network based defect detection in Submerged Arc Welding processes -- 3 On the use of Generative AI to support in-line process monitoring in Zero-Defect Manufacturing -- 4 Laser Metal Deposition (LMD) process monitoring: from 3D visualization of sensor data towards anomaly detection -- 5 An explainable active learning approach for enhanced defect detection in manufacturing, etc.
520			_aThis open access book reports on recent developments of artificial intelligence applications in the manufacturing industry. Gathering contributions to the second European Symposium on Artificial Intelligence in Manufacturing, held on October 16, 2024, in Athens, Greece, it reports on machine learning, deep learning and generative AI models for process monitoring, optimization, and control, flexible and precise industrial robots, human-robot collaboration, data management and information technologies, digital twins, data augmentation and synthetic data. Giving a special emphasis to the integration of artificial intelligence in manufacturing systems, automation and processes, this book offers a timely and practice-oriented guide to a multidisciplinary audience of engineering researchers, system developers, AI scientists and industrial managers.
588	0		_aOnline resource; title from PDF title page (SpringerLink, viewed March 26, 2025).
650		0	_aArtificial intelligence _xIndustrial applications _vCongresses. _0http://id.loc.gov/authorities/subjects/sh2009115959
650		0	_aManufacturing processes _xTechnological innovations _vCongresses.
650		0	_aAutomation. _0http://id.loc.gov/authorities/subjects/sh85010116
650		0	_aIndustrial engineering. _0http://id.loc.gov/authorities/subjects/sh85065864
655		4	_aElectronic books.
700	1		_aAlexopoulos, Kosmas, _eeditor. _0(orcid)0000-0002-3658-6838 _1https://orcid.org/0000-0002-3658-6838
700	1		_aMakris, Sotiris, _eeditor. _0(orcid)0000-0001-9687-5925 _1https://orcid.org/0000-0001-9687-5925
700	1		_aStavropoulos, Panagiotis, _eeditor. _0(orcid)0000-0003-0724-7957 _1https://orcid.org/0000-0003-0724-7957
830		0	_aLecture notes in mechanical engineering, _x2195-4364 _0http://id.loc.gov/authorities/names/no2013039484
856	4	0	_uhttps://directory.doabooks.org/handle/20.500.12854/158439 _yFull text is available at the Directory of Open Access Books. Click here to view.
856	4	0	_uhttps://link.springer.com/book/10.1007/978-3-031-86489-6 _ySpringer Nature
942			_2ddc _cOA