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Artificial Intelligence and Lean Manufacturing
Kategorie Beschreibung
036aXA-CH
037beng
087q978-3-031-04582-0
087q978-3-031-04584-4
100 Chen, Tin-Chih Toly ¬[VerfasserIn]¬
104aWang, 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
425a2022
433 1 Online-Ressource(VI, 90 p. 60 illus., 42 illus. in color.)
451bSpringerBriefs 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
540aISBN 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
125aElektronischer Volltext - Campuslizenz
655e$uhttps://doi.org/10.1007/978-3-031-04583-7
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