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MAB
Artificial Intelligence and Lean Manufacturing
Kategorie
Beschreibung
036a
XA-CH
037b
eng
087q
978-3-031-04582-0
087q
978-3-031-04584-4
100
Chen, Tin-Chih Toly ¬[VerfasserIn]¬
104a
Wang, Yi-Chi ¬[VerfasserIn]¬
331
Artificial Intelligence and Lean Manufacturing
403
1st ed. 2022.
410
Cham
410
Cham
412
Springer International Publishing
412
Imprint: Springer
425
2022
425
2022
425a
2022
433
1 Online-Ressource(VI, 90 p. 60 illus., 42 illus. in color.)
451b
SpringerBriefs in Applied Sciences and Technology
527
Erscheint auch als (Druck-Ausgabe)ISBN: 978-3-031-04582-0
527
Erscheint auch als (Druck-Ausgabe)ISBN: 978-3-031-04584-4
540a
ISBN 978-3-031-04583-7
700
|TGP
700
|TEC009060
700b
|670
750
Chapter 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.
753
This 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.
012
1800753985
081
Artificial Intelligence and Lean Manufacturing
100
Springer E-Book
125a
Elektronischer Volltext - Campuslizenz
655e
$uhttps://doi.org/10.1007/978-3-031-04583-7
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