An Introduction to Predictive Maintenance

An Introduction to Predictive Maintenance

Author: R. Keith Mobley

Publisher: Elsevier

Published: 2002-10-24

Total Pages: 451

ISBN-13: 0080478697

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This second edition of An Introduction to Predictive Maintenance helps plant, process, maintenance and reliability managers and engineers to develop and implement a comprehensive maintenance management program, providing proven strategies for regularly monitoring critical process equipment and systems, predicting machine failures, and scheduling maintenance accordingly. Since the publication of the first edition in 1990, there have been many changes in both technology and methodology, including financial implications, the role of a maintenance organization, predictive maintenance techniques, various analyses, and maintenance of the program itself. This revision includes a complete update of the applicable chapters from the first edition as well as six additional chapters outlining the most recent information available. Having already been implemented and maintained successfully in hundreds of manufacturing and process plants worldwide, the practices detailed in this second edition of An Introduction to Predictive Maintenance will save plants and corporations, as well as U.S. industry as a whole, billions of dollars by minimizing unexpected equipment failures and its resultant high maintenance cost while increasing productivity. - A comprehensive introduction to a system of monitoring critical industrial equipment - Optimize the availability of process machinery and greatly reduce the cost of maintenance - Provides the means to improve product quality, productivity and profitability of manufacturing and production plants


Preventive Maintenance

Preventive Maintenance

Author: Joseph D. Patton

Publisher:

Published: 1983

Total Pages: 192

ISBN-13: 9780876646397

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Sets out principles of the preventive and predictive maintenance of durable equipment. Explains how to balance the costs of down time and maintenance, designing and implementing a program, the importance of personnel motivation, safety and quality benefits, and other aspects. No date is noted for the first edition; the second adds new technology and management concepts. Annotation copyright by Book News, Inc., Portland, OR


Predictive Maintenance in Dynamic Systems

Predictive Maintenance in Dynamic Systems

Author: Edwin Lughofer

Publisher: Springer

Published: 2019-02-28

Total Pages: 564

ISBN-13: 3030056457

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This book provides a complete picture of several decision support tools for predictive maintenance. These include embedding early anomaly/fault detection, diagnosis and reasoning, remaining useful life prediction (fault prognostics), quality prediction and self-reaction, as well as optimization, control and self-healing techniques. It shows recent applications of these techniques within various types of industrial (production/utilities/equipment/plants/smart devices, etc.) systems addressing several challenges in Industry 4.0 and different tasks dealing with Big Data Streams, Internet of Things, specific infrastructures and tools, high system dynamics and non-stationary environments . Applications discussed include production and manufacturing systems, renewable energy production and management, maritime systems, power plants and turbines, conditioning systems, compressor valves, induction motors, flight simulators, railway infrastructures, mobile robots, cyber security and Internet of Things. The contributors go beyond state of the art by placing a specific focus on dynamic systems, where it is of utmost importance to update system and maintenance models on the fly to maintain their predictive power.


Industrial Maintenance

Industrial Maintenance

Author: Denis Green

Publisher: American Technical Publications

Published: 2010

Total Pages: 0

ISBN-13: 9780826936417

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With an emphasis on maintenance personnel versatility, Industrial Maintenance is a comprehensive source of fundamental system operation, maintenance, and troubleshooting information. This edition builds on industry-proven content and offers expanded coverage in the areas of energy efficiency and auditing, waste reduction, safety standards, advanced multimeter functions and procedures, building automation systems, and indoor air quality. Real-world maintenance problems and solutions are depicted throughout the textbook, along with equipment operating principles, maintenance management procedures, and troubleshooting scenarios for common systems.The workbook features typical troubleshooting and diagnostic activities encountered in the field. Activities reinforce knowledge of maintenance concepts and help learners develop troubleshooting skills.


Uptime

Uptime

Author: John D. Campbell

Publisher: CRC Press

Published: 2015-08-18

Total Pages: 526

ISBN-13: 1482252384

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Uptime describes the combination of activities that deliver fewer breakdowns, improved productive capacity, lower costs, and better environmental performance. The bestselling second edition of Uptime has been used as a textbook on maintenance management in several postsecondary institutions and by many companies as the model framework for their mai


Practical Machinery Vibration Analysis and Predictive Maintenance

Practical Machinery Vibration Analysis and Predictive Maintenance

Author: Cornelius Scheffer

Publisher: Elsevier

Published: 2004-07-16

Total Pages: 263

ISBN-13: 0080480225

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Machinery Vibration Analysis and Predictive Maintenance provides a detailed examination of the detection, location and diagnosis of faults in rotating and reciprocating machinery using vibration analysis. The basics and underlying physics of vibration signals are first examined. The acquisition and processing of signals is then reviewed followed by a discussion of machinery fault diagnosis using vibration analysis. Hereafter the important issue of rectifying faults that have been identified using vibration analysis is covered. The book also covers the other techniques of predictive maintenance such as oil and particle analysis, ultrasound and infrared thermography. The latest approaches and equipment used together with the latest techniques in vibration analysis emerging from current research are also highlighted. - Understand the basics of vibration measurement - Apply vibration analysis for different machinery faults - Diagnose machinery-related problems with vibration analysis techniques


Maintenance Planning and Scheduling Handbook

Maintenance Planning and Scheduling Handbook

Author: Richard (Doc) Palmer

Publisher: McGraw Hill Professional

Published: 2006-01-04

Total Pages: 861

ISBN-13: 007150155X

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Many readers already regard the Maintenance Planning and Scheduling Handbook as the chief authority for establishing effective maintenance planning and scheduling in the real world. The second edition adds new sections and further develops many existing discussions to make the handbook more comprehensive and helpful. In addition to practical observations and tips on such topics as creating a weekly schedule, staging parts and tools, and daily scheduling, this second edition features a greatly expanded CMMS appendix which includes discussion of critical cautions for implementation, patches, major upgrades, testing, training, and interfaces with other company software. Readers will also find a timely appendix devoted to judging the potential benefits and risks of outsourcing plant work. A new appendix provides guidance on the "people side" of maintenance planning and work execution. The second edition also has added a detailed aids and barriers analysis that improves the appendix on setting up a planning group. The new edition also features "cause maps" illustrating problems with a priority systems and schedule compliance. These improvements and more continue to make the Maintenance Planning and Scheduling Handbook a maintenance classic.


Predictive Analytics with Microsoft Azure Machine Learning

Predictive Analytics with Microsoft Azure Machine Learning

Author: Valentine Fontama

Publisher: Apress

Published: 2014-11-25

Total Pages: 178

ISBN-13: 148420445X

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Data Science and Machine Learning are in high demand, as customers are increasingly looking for ways to glean insights from all their data. More customers now realize that Business Intelligence is not enough as the volume, speed and complexity of data now defy traditional analytics tools. While Business Intelligence addresses descriptive and diagnostic analysis, Data Science unlocks new opportunities through predictive and prescriptive analysis. The purpose of this book is to provide a gentle and instructionally organized introduction to the field of data science and machine learning, with a focus on building and deploying predictive models. The book also provides a thorough overview of the Microsoft Azure Machine Learning service using task oriented descriptions and concrete end-to-end examples, sufficient to ensure the reader can immediately begin using this important new service. It describes all aspects of the service from data ingress to applying machine learning and evaluating the resulting model, to deploying the resulting model as a machine learning web service. Finally, this book attempts to have minimal dependencies, so that you can fairly easily pick and choose chapters to read. When dependencies do exist, they are listed at the start and end of the chapter. The simplicity of this new service from Microsoft will help to take Data Science and Machine Learning to a much broader audience than existing products in this space. Learn how you can quickly build and deploy sophisticated predictive models as machine learning web services with the new Azure Machine Learning service from Microsoft.


Predictive Maintenance in Smart Factories

Predictive Maintenance in Smart Factories

Author: Tania Cerquitelli

Publisher: Springer Nature

Published: 2021-08-26

Total Pages: 239

ISBN-13: 9811629404

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This book presents the outcome of the European project "SERENA", involving fourteen partners as international academics, technological companies, and industrial factories, addressing the design and development of a plug-n-play end-to-end cloud architecture, and enabling predictive maintenance of industrial equipment to be easily exploitable by small and medium manufacturing companies with a very limited data analytics experience. Perspectives and new opportunities to address open issues on predictive maintenance conclude the book with some interesting suggestions of future research directions to continue the growth of the manufacturing intelligence.