£115.87

Springer Control Charts and Machine Learning for Anomaly Detection

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Description

Bridge the gap between statistical methods and modern data science with this comprehensive guide from Springer. Control Charts and Machine Learning for Anomaly Detection in Manufacturing provides an in-depth look at the latest research in detecting abnormalities within smart manufacturing environments. As the industry moves toward the 4.0 Industrial Revolution, this book offers the necessary tools to manage complex production processes. By combining traditional statistical control charts with new machine learning approaches, this text encourages interdisciplinary cooperation between research communities. It is designed to help professionals and researchers develop detection methods that are better suited for modern, automated manufacturing systems. Readers will find practical value through the inclusion of ready-to-use algorithms and parameter sheets, making it easier to implement advanced detection strategies in real-world settings.

Key Features

Integrates advanced control charts with new machine learning approaches to improve detection accuracy in smart manufacturing.

Promotes interdisciplinary cooperation by combining statistical methods and machine learning research for better results.

Designed specifically to meet the needs of the 4.0 Industrial Revolution in modern manufacturing environments.

Includes ready-to-use algorithms to help readers implement advanced detection strategies quickly.

Provides practical parameter sheets to assist in the design of machine learning-based anomaly detection approaches.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
31 August 2022
Listed Since
03 August 2022

Barcode

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