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• W2912672771 abstract "Predictive maintenance is one of the major drivers of Industry 4.0 as it can significantly reduce costs by improving overall equipment effectiveness and extending the remaining useful life of production machines. Most of the potential lies in the brownfield with old equipment where no sensors or connectivity are available. This paper shows how these production machines can be enabled for predictive maintenance by retrofitting with low-cost sensors, an Industrial-Internet-of-Things-architecture and machine learning. An industrial implementation on a heavy lift Electric Monorail System at the BMW Group will be shown." @default.
• W2912672771 created "2019-02-21" @default.
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• W2912672771 date "2018-12-01" @default.
• W2912672771 modified "2023-10-13" @default.
• W2912672771 title "Enabling of Predictive Maintenance in the Brownfield through Low-Cost Sensors, an IIoT-Architecture and Machine Learning" @default.
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• W2912672771 doi "https://doi.org/10.1109/bigdata.2018.8622076" @default.
• W2912672771 hasPublicationYear "2018" @default.
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