AI Techniques for Reliability Prediction for Electronic Components (Hardcover)

In the industry of manufacturing and design, one major constraint has been enhancing operating performance using less time. As technology continues to advance, manufacturers are looking for better methods in predicting the condition and residual lifetime of electronic devices in order to save repair costs and their reputation. Intelligent systems are a solution for predicting the reliability of these components; however, there is a lack of research on the advancements of this smart technology within the manufacturing industry. AI Techniques for Reliability Prediction for Electronic Components provides emerging research exploring the theoretical and practical aspects of prediction methods using artificial intelligence and machine learning in the manufacturing field. Featuring coverage on a broad range of topics such as data collection, fault tolerance, and health prognostics, this book is ideally designed for reliability engineers, electronic engineers, researchers, scientists, students, and faculty members seeking current research on the advancement of reliability analysis using AI.

General

Imprint:	Business Science Reference
Country of origin:	United States
Release date:	December 2019
Editors:	Cherry Bhargava
Dimensions:	279 x 216mm (L x W)
Format:	Hardcover
Pages:	365
ISBN-13:	978-1-79981-464-1
Categories:	Books > Professional & Technical > Industrial chemistry & manufacturing technologies > Industrial chemistry > Chemical engineering Books > Computing & IT > Applications of computing > Artificial intelligence > Neural networks Promotions
LSN:	1-79981-464-5
Barcode:	9781799814641

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