Approach to the Condition Description of Technical Components |
Prediction of remaining useful life based on discretely recorded component states using mobile sensor technology
| Journal | Industrie 4.0 Management |
| Issue | Volume 37, 2021, Edition 2, Pages 35-38 |
| Open Access | https://doi.org/10.30844/I40M_21-2_S35-38 |
| Bibliography | Share | Cite | Download |
Abstract
This article describes a predictive maintenance approach in which a flexible sensor toolkit records and a prediction model monitors the component wear within technical systems. The condition of the components is not determined continuously, but based on time-discrete measurements. The prediction model predicts the presumable remaining useful life of the components based on the recorded data. A machine learning tool is trained with historical wear curves and used to generate the prediction. The training data is collected through statistical tests in which the influencing variables and characteristic curves of different types of wear are identified.
Keywords
load cycles, machine learning, prediction model, predictive maintenance, remaining useful life, wear
Bibliography
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