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

doi:10.1007/s40436-015-0107-4

Advances in Manufacturing ›› 2015, Vol. 3 ›› Issue (2): 97-104.doi: 10.1007/s40436-015-0107-4

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

Ke-Sheng Wang^1,2, Zhe Li¹, Jørgen Braaten¹, Quan Yu¹

1 Knowledge Discovery Laboratory, Department of Production and Quality Engineering, Norwegian University of Science and Technology, Trondheim, Norway;
2 Key Laboratory of Intelligent Manufacturing and Robotics, Shanghai University, Shanghai, P. R. China

Received:2015-03-24 Revised:2015-04-15 Online:2015-06-25 Published:2015-05-14
Contact: Ke-Sheng Wang E-mail:kesheng.wang@ntnu.no

Abstract

Abstract: 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.

Key words: Backlash error, Artificial neural network (ANN), Machine centers, Predictive maintenance

Ke-Sheng Wang, Zhe Li, Jørgen Braaten, Quan Yu. Interpretation and compensation of backlash error data in machine centers for intelligent predictive maintenance using ANNs[J]. Advances in Manufacturing, 2015, 3(2): 97-104.

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

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