Control Charts and Machine Learning for Anomaly Detection in Manufacturing (Hardcover, 1st ed. 2022)

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.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Springer Series in Reliability Engineering
Release date:	August 2021
First published:	2022
Editors:	Kim Phuc Tran
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	269
Edition:	1st ed. 2022
ISBN-13:	978-3-03-083818-8
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Professional & Technical > Technology: general issues > Engineering: general Books > Professional & Technical > Mechanical engineering & materials > Production engineering > General Books > Professional & Technical > Energy technology & engineering > Electrical engineering > General Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning Promotions
LSN:	3-03-083818-8
Barcode:	9783030838188

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