Abstract
This chapter addresses the development and application of predictive
maintenance concepts for several types of assets, following two
approaches: (1) detection and prediction of failures based on (realtime)
monitoring the health or condition of the systems, and (2)
prediction of failures (prognostics) using physical failure models and
monitoring of loads or usage. Firstly, several challenges in the field
of predictive maintenance are presented. These challenges will be
addressed by the methods and tools discussed in the remainder of
the chapter. Both the structural health monitoring methods and the
prognostic concepts presented are based on a thorough understanding
of the system and physical failure behaviour. After discussing the
approaches for monitoring and prognostics, a series of decision support
tools is presented. As a large number of methods and techniques are
available, the selection of the most suitable method, as well as the critical
parts in a system, is a challenging task. The presented tools assist in this
selection process. Finally, the practical implementation of the presented
approaches is discussed by showing a number of case studies in different
sectors of industry.
maintenance concepts for several types of assets, following two
approaches: (1) detection and prediction of failures based on (realtime)
monitoring the health or condition of the systems, and (2)
prediction of failures (prognostics) using physical failure models and
monitoring of loads or usage. Firstly, several challenges in the field
of predictive maintenance are presented. These challenges will be
addressed by the methods and tools discussed in the remainder of
the chapter. Both the structural health monitoring methods and the
prognostic concepts presented are based on a thorough understanding
of the system and physical failure behaviour. After discussing the
approaches for monitoring and prognostics, a series of decision support
tools is presented. As a large number of methods and techniques are
available, the selection of the most suitable method, as well as the critical
parts in a system, is a challenging task. The presented tools assist in this
selection process. Finally, the practical implementation of the presented
approaches is discussed by showing a number of case studies in different
sectors of industry.
Original language | English |
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Title of host publication | Predictive Maintenance in Dynamic Systems |
Subtitle of host publication | Advanced Methods, Decision Support Tools and Real-World Applications |
Editors | Edwin Lughofer, Moamar Sayed-Mouchaweh |
Publisher | Springer |
Chapter | 11 |
Pages | 313-353 |
Number of pages | 41 |
ISBN (Electronic) | 978-3-030-05645-2 |
ISBN (Print) | 978-3-030-05644-5 |
DOIs | |
Publication status | Published - 2019 |