Machine learning in manufacturing quality 4.0 and the zero defects vision
1. Introduction2. The technologies3. The data4. Binary classification5. Machine learning6. Feature engineering7. Classifier development8. Learning quality control9. Case studies; structured and unstructured data10. Conclusion and call to action
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| Format: | UnknownFormat |
| Sprache: | eng |
| Veröffentlicht: |
Amsterdam, London, Cambridge, MA
Elsevier
2024
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| Online Zugang: | Cover |
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| Zusammenfassung: | 1. Introduction2. The technologies3. The data4. Binary classification5. Machine learning6. Feature engineering7. Classifier development8. Learning quality control9. Case studies; structured and unstructured data10. Conclusion and call to action Machine Learning in Manufacturing: Quality 4.0 and the Zero Defects Vision reviews process monitoring based on machine learning algorithms and the technologies of the fourth industrial revolution and proposes Learning Quality Control (LQC), the evolution of Statistical Quality Control (SQC). This book identifies 10 big data issues in manufacturing and addresses them using an ad-hoc, 5-step problem-solving strategy that increases the likelihood of successfully deploying this Quality 4.0 initiative. With two case studies using structured and unstructured data, this book explains how to successfully deploy AI in manufacturing and how to move quality standards forward by developing virtually defect-free processes. This book enables engineers to identify Quality 4.0 applications and manufacturing companies to successfully implement Quality 4.0 practices |
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| Beschreibung: | Literaturverzeichnis: Seite 211-224 |
| Beschreibung: | x, 236 Seiten Illustrationen, Diagramme |
| ISBN: | 9780323990295 978-0-323-99029-5 |