Fuzzy Logic Dynamics and Machine Prediction for Failure Analysis
Nonfiction, Science & Nature, Technology, Machinery, Computers, Advanced Computing, Artificial Intelligence, General Computing
| 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.
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.
