Interpretation and compensation of backlash error data in machine centers for intelligent predictive maintenance using ANNs

It is especially significant for a manufacturing company to select a proper maintenance policy because maintenance impacts not only on economy, reliability and availability but also on personnel safety. This article reports on research in the backlash error data interpretation and compensation for i...

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Bibliographic Details
Published in:Advances in manufacturing 2015-06, Vol.3 (2), p.97-104
Main Authors: Wang, Ke-Sheng, Li, Zhe, Braaten, Jørgen, Yu, Quan
Format: Article
Language:English
Subjects:
Availability
Backlash
Compensation
Control
Economics
Engineering
Errors
Machine tools
Machines
Machining centres
Maintenance
Manufacturing
Mechatronics
Nanotechnology and Microengineering
Predictive maintenance
Processes
Robotics
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Summary:It is especially significant for a manufacturing company to select a proper maintenance policy because maintenance impacts not only on economy, reliability and availability but also on personnel safety. This article reports on research in the backlash error data interpretation and compensation for intelligent predictive maintenance in machine centers based on artificial neural networks (ANNs). The backlash error, measurement system and prediction methods are analyzed in detail. The result indicates that it is possible to predict and compensate for the backlash error in both forward and backward directions in machine centers.
ISSN:2095-3127
2195-3597
DOI:10.1007/s40436-015-0107-4