Condition monitoring system for machine tool auxiliaries
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Author / Producer
Date
2020
Publication Type
Conference Paper
ETH Bibliography
yes
Citations
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Abstract
Failures on machine tools not only occur on main components, but also on auxiliaries like cooling units or oil mist separators, which causes productivity losses similar to failures on main machine components. Due to their separation from the machine’s control network, their health status is in most cases not monitored. In this study, a new approach for online condition monitoring of auxiliary units by the example of an oil mist separator connected to a 5-axis machine tool is presented. The data is analyzed via machine learning principles in order to deduct an adequate condition assessment, encompassing environmental influences.
Permanent link
Publication status
published
External links
Book title
13th CIRP Conference on Intelligent Computation in Manufacturing Engineering
Journal / series
Volume
88
Pages / Article No.
358 - 363
Publisher
Elsevier
Event
13th CIRP Conference on Intelligent Computation in Manufacturing Engineering (CIRP ICME 2019)
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
Manufacturing systems; Condition Monitoring; Machine learning (artificial intelligence); MACHINE TOOLS AND MACHINERY (MANUFACTURING TECHNOLOGY); Machine auxiliaries; Machine Monitoring; Neural Networks
Organisational unit
03641 - Wegener, Konrad (emeritus) / Wegener, Konrad (emeritus)
Notes
Conference lecture held on July 18, 2019
Funding
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