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Control Charts and Machine Learning for Anomaly Detection in Manufacturing - Couverture rigide

Livre 72 sur 90: Springer Series in Reliability Engineering
 
9783030838188: Control Charts and Machine Learning for Anomaly Detection in Manufacturing
Couverture rigide
ISBN 10 : 3030838188 ISBN 13 : 9783030838188
Editeur : Springer Nature Switzerland AG, 2021

Synopsis

This book introduces the latest research on advanced control charts and new machine learning approaches to detect abnormalities in the smart manufacturing process. By approaching anomaly detection using both statistics and machine learning, the book promotes interdisciplinary cooperation between the research communities, to jointly develop new anomaly detection approaches that are more suitable for the 4.0 Industrial Revolution.

The book provides ready-to-use algorithms and parameter sheets, enabling readers to design advanced control charts and machine learning-based approaches for anomaly detection in manufacturing. Case studies are introduced in each chapter to help practitioners easily apply these tools to real-world manufacturing processes.

The book is of interest to researchers, industrial experts, and postgraduate students in the fields of industrial engineering, automation, statistical learning, and manufacturing industries.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

À propos de l'auteur

Dr. Kim Phuc Tran is an Associate Professor of Artificial Intelligence and Data Science at the ENSAIT and the GEMTEX laboratory, University of Lille, France. His research focuses on anomaly detection and applications, decision support systems with artificial intelligence, federated learning, edge computing and applications. He has published more than 44 papers in international refereed journal papers, 5 book chapters, and 2 editorials as well as over 20 papers in conference proceedings.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
Springer Nature Switzerland AG
Date d'édition
2021
Langue
anglais
ISBN 10 
3030838188
ISBN 13 
9783030838188
Reliure
Relié
Nombre de pages
275
Éditeur
Tran Kim Phuc
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