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008			221217s2022 sz | s |||| 0|eng d
020			_a9783031045837
024	7		_a10.1007/978-3-031-04583-7 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTS155 _b2022 EB
100			_aChen, Tin-Chih Toly _eautor _0(orcid)0000-0002-5608-5176 _1https://orcid.org/0000-0002-5608-5176 _4aut _4http://id.loc.gov/vocabulary/relators/aut _9672118
245	1	0	_aArtificial Intelligence and Lean Manufacturing _cby Tin-Chih Toly Chen, Yi-Chi Wang
250			_a1st edition 2022
264		1	_aCham _bSpringer International Publishing _c2022
300			_a1 recurso en línea (VI, 90 páginas) _b60 ilustraciones, 42 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	1		_aSpringerBriefs in Applied Sciences and Technology _x2191-5318
505	0		_aChapter 1. Basics in Lean Management -- Chapter 2. AI in Manufacturing -- Chapter 3. AI Applications to Kaizen Management -- Chapter 4. AI Applications to Pull Manufacturing and JIT -- Chapter 5. AI Applications to Production Leveling -- Chapter 6. AI Applications to Shop Floor Management: 5S, Kanban, SMED -- Chapter 7. AI Applications to Value Stream Mapping.
520			_aThis book applies artificial intelligence to lean production and shows how to practically combine the advantages of these two disciplines. Lean manufacturing originated in Japan and is a well-known tool for improving manufacturers' competitiveness. Prevalent tools for lean manufacturing include Kanban, Pacemaker, Value Stream Map, 5s, Just-in-Time and Pull Manufacturing. Lean Manufacturing and the Toyota Manufacturing System has been successfully applied to various factories and supply chains around the world. A lean manufacturing system can not only reduce wastes and inventory, but also respond to customer needs more immediately. Artificial intelligence is a subject that has attracted much attention recently. Many researchers and practical developers are working hard to apply artificial intelligence to our daily lives, including in factories. For example, fuzzy rules have been established to optimize machine settings. Bionic algorithms have been proposed to solve production sequencing and scheduling problems. Machine learning technologies are applied to detect possible product quality problems and diagnose the health of a machine. This book will be of interest to production engineers, managers, as well as students and researchers in manufacturing engineering.
988			_aSpringer_Engineering_2022
650		7	_2embne _aInteligencia artificial _xAplicaciones industriales _9413115
650		7	_2embne _9150644 _aGestión de la producción
700	1		_aWang, Yi-Chi _eautor _0(orcid)0000-0003-0861-7526 _1https://orcid.org/0000-0003-0861-7526 _4aut _4http://id.loc.gov/vocabulary/relators/aut _9685689
776	0	8	_iPrinted edition: _z9783031045820
776	0	8	_iPrinted edition: _z9783031045844
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-04583-7 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b12/2022 _dz _eIG _zSI