New
Machine Learning in Manufacturing,
Edition 1
Quality 4.0 and the Zero Defects Vision
By Carlos A. Escobar and Ruben Morales-Menendez
Publication Date:
22 Mar 2024
Description
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.
Key Features
- Provides an understanding of the most relevant challenges posed to the application of Artificial Intelligence (AI) in manufacturing
- Includes analytical developments and applications and merges a quality vision with machine learning algorithms
- Features structured and unstructured data case studies to illustrate how to develop intelligent monitoring systems with the capacity to replace manual and visual tasks
About the author
By Carlos A. Escobar, Research scientist, School of Engineering and Sciences, Tecnologico de Monterrey, Mexico and Ruben Morales-Menendez, Dean of Graduate Studies, School of Engineering and Sciences, Tecnologico de Monterrey, Mexico
Table of Contents
1. Introduction
2. The technologies
3. The data
4. Binary classification
5. Machine learning
6. Feature engineering
7. Classifier development
8. Learning quality control
9. Case studies; structured and unstructured data
10. Conclusion and call to action
2. The technologies
3. The data
4. Binary classification
5. Machine learning
6. Feature engineering
7. Classifier development
8. Learning quality control
9. Case studies; structured and unstructured data
10. Conclusion and call to action
Title details
ISBN:
9780323990295
Page Count: 246
Retail Price (USD)
:
9780367422721; 9783030668488; 9780367230081
Audience
Professional engineers, managers, and directors, Graduate students, the book will also include details for obtaining a green, black, and master black belt certification, can be used also by certifications institutions
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