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Edité par Engineering Science Reference, 2019
ISBN 10 : 1799814653 ISBN 13 : 9781799814658
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Langue: anglais
Edité par Engineering Science Reference, 2019
ISBN 10 : 1799814653 ISBN 13 : 9781799814658
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Edité par Engineering Science Reference, 2019
ISBN 10 : 1799814653 ISBN 13 : 9781799814658
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Langue: anglais
Edité par Engineering Science Reference, 2019
ISBN 10 : 1799814653 ISBN 13 : 9781799814658
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Ajouter au panierPaperback. Etat : New. 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.
Langue: anglais
Edité par Engineering Science Reference, 2019
ISBN 10 : 1799814645 ISBN 13 : 9781799814641
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
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Edité par Engineering Science Reference, 2019
ISBN 10 : 1799814645 ISBN 13 : 9781799814641
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Langue: anglais
Edité par Engineering Science Reference, 2019
ISBN 10 : 1799814645 ISBN 13 : 9781799814641
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Ajouter au panierEtat : Hervorragend. Zustand: Hervorragend | Seiten: 352 | Sprache: Englisch | Produktart: Bücher | 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.
Langue: anglais
Edité par Engineering Science Reference, 2019
ISBN 10 : 1799814645 ISBN 13 : 9781799814641
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Ajouter au panierPaperback. Etat : New. 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.
Langue: anglais
Edité par Engineering Science Reference, 2019
ISBN 10 : 1799814645 ISBN 13 : 9781799814641
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Ajouter au panierhardcover. Etat : New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Ajouter au panierPAP. Etat : New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Ajouter au panierPAP. Etat : New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Langue: anglais
Edité par Engineering Science Reference, 2019
ISBN 10 : 1799814653 ISBN 13 : 9781799814658
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Ajouter au panierEtat : New. Print on Demand pp. 330.
Langue: anglais
Edité par Engineering Science Reference, 2019
ISBN 10 : 1799814653 ISBN 13 : 9781799814658
Vendeur : Majestic Books, Hounslow, Royaume-Uni
EUR 250,02
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Ajouter au panierEtat : New. Print on Demand pp. 330.
Langue: anglais
Edité par Engineering Science Reference, 2019
ISBN 10 : 1799814653 ISBN 13 : 9781799814658
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EUR 204,11
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Ajouter au panierEtat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents research exploring the theoretical and practical aspects of prediction methods using artificial intelligence and machine learning in the manufacturing field. The book features coverage on a broad range of topics, including data collection, fault to.
Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
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Ajouter au panierHRD. Etat : New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Langue: anglais
Edité par Engineering Science Reference, 2019
ISBN 10 : 1799814653 ISBN 13 : 9781799814658
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Ajouter au panierEtat : New. PRINT ON DEMAND pp. 330.
Langue: anglais
Edité par Engineering Science Reference, 2019
ISBN 10 : 1799814645 ISBN 13 : 9781799814641
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EUR 263,65
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Ajouter au panierGebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides emerging research exploring the theoretical and practical aspects of prediction methods using artificial intelligence and machine learning in the manufacturing field. The book features coverage on a broad range of topics, including data collection,.
Langue: anglais
Edité par Engineering Science Reference, 2019
ISBN 10 : 1799814653 ISBN 13 : 9781799814658
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Ajouter au panierTaschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 'This book explores the theoretical and practical aspects of prediction methods using artificial intelligence and machine learning in the manufacturing field'.
Langue: anglais
Edité par Engineering Science Reference, 2019
ISBN 10 : 1799814645 ISBN 13 : 9781799814641
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Ajouter au panierBuch. Etat : Neu. AI Techniques for Reliability Prediction for Electronic Components | Cherry Bhargava | Buch | Gebunden | Englisch | 2019 | Engineering Science Reference | EAN 9781799814641 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
Langue: anglais
Edité par Engineering Science Reference, 2019
ISBN 10 : 1799814645 ISBN 13 : 9781799814641
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
EUR 328,55
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Ajouter au panierBuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.