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portada Industrial AI: Applications with Sustainable Performance
Type
Physical Book
Author
Publisher
Language
Inglés
Pages
162
Format
Hardcover
Dimensions
23.4 x 15.6 x 1.3 cm
Weight
0.44 kg.
ISBN13
9789811521430

Industrial AI: Applications with Sustainable Performance

Jay Lee (Author) · Springer · Hardcover

Industrial AI: Applications with Sustainable Performance - Lee, Jay

Physical Book

£ 187.91

  • Condition: New
Origin: U.S.A. (Import costs included in the price)
It will be shipped from our warehouse between Monday, July 15 and Monday, July 22.
You will receive it anywhere in United Kingdom between 1 and 3 business days after shipment.

Synopsis "Industrial AI: Applications with Sustainable Performance"

This book introduces Industrial AI in multiple dimensions. Industrial AI is a systematic discipline which focuses on developing, validating and deploying various machine learning algorithms for industrial applications with sustainable performance. Combined with the state-of-the-art sensing, communication and big data analytics platforms, a systematic Industrial AI methodology will allow integration of physical systems with computational models. The concept of Industrial AI is in infancy stage and may encompass the collective use of technologies such as Internet of Things, Cyber-Physical Systems and Big Data Analytics under the Industry 4.0 initiative where embedded computing devices, smart objects and the physical environment interact with each other to reach intended goals. A broad range of Industries including automotive, aerospace, healthcare, semiconductors, energy, transportation, mining, construction, and industrial automation could harness the power of Industrial AI to gain insights into the invisible relationship of the operation conditions and further use that insight to optimize their uptime, productivity and efficiency of their operations. In terms of predictive maintenance, Industrial AI can detect incipient changes in the system and predict the remains useful life and further to optimize maintenance tasks to avoid disruption to operations.

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