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Machine Learning Manufacturing: Quality 4.0 and the Zero Defects Vision
Indigo
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Machine Learning Manufacturing: Quality 4.0 and the Zero Defects Vision
By None
Current price: $159.19
Original price: $199.00


By None
Machine Learning Manufacturing: Quality 4.0 and the Zero Defects Vision
Current price: $159.19
Original price: $199.00
Loading Inventory...
Size: Kobo eBook
*Product information may vary - to confirm product availability, pricing, shipping and return information please contact Indigo
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.
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
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.
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



















