Fuzzy Logic Dynamics and Machine Prediction for Failure Analysis

Nonfiction, Science & Nature, Technology, Machinery, Computers, Advanced Computing, Artificial Intelligence, General Computing
Cover of the book Fuzzy Logic Dynamics and Machine Prediction for Failure Analysis by Tawanda Mushiri, Charles Mbowhwa, IGI Global
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Author: Tawanda Mushiri, Charles Mbowhwa ISBN: 9781522532460
Publisher: IGI Global Publication: January 12, 2018
Imprint: Engineering Science Reference Language: English
Author: Tawanda Mushiri, Charles Mbowhwa
ISBN: 9781522532460
Publisher: IGI Global
Publication: January 12, 2018
Imprint: Engineering Science Reference
Language: English

In the fast pace of the modern world it is important, more than ever, for factories to know how and why their machines are failing and what can be done to prevent it. As such, it is imperative that new research is conducted to make sure that factories can operate as efficiently as possible. Fuzzy Logic Dynamics and Machine Prediction for Failure Analysis is an essential reference source for the newest research on the risk assessment matrix, ladder logic, and computerized maintenance management systems (CMMS). Featuring widespread coverage across a variety of related viewpoints and topics, such as the Ishikawa diagram, machinery failure analysis and troubleshooting, model reference adaptive control systems, and proportional–integral–derivative (PID) controllers, this book is ideally designed for professionals, upper-level students, and academics seeking current research on the implementation of fuzzy logic in machine prediction failure.

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In the fast pace of the modern world it is important, more than ever, for factories to know how and why their machines are failing and what can be done to prevent it. As such, it is imperative that new research is conducted to make sure that factories can operate as efficiently as possible. Fuzzy Logic Dynamics and Machine Prediction for Failure Analysis is an essential reference source for the newest research on the risk assessment matrix, ladder logic, and computerized maintenance management systems (CMMS). Featuring widespread coverage across a variety of related viewpoints and topics, such as the Ishikawa diagram, machinery failure analysis and troubleshooting, model reference adaptive control systems, and proportional–integral–derivative (PID) controllers, this book is ideally designed for professionals, upper-level students, and academics seeking current research on the implementation of fuzzy logic in machine prediction failure.

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