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Implications from Legacy Device Environments on the Conceptional Design of Machine Learning Models in Manufacturing.
- Published in:
- Journal of Manufacturing & Materials Processing, 2024, v. 8, n. 1, p. 15, doi. 10.3390/jmmp8010015
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- Article
Towards Material-Batch-Aware Tool Condition Monitoring.
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- Journal of Manufacturing & Materials Processing, 2021, v. 5, n. 4, p. 103, doi. 10.3390/jmmp5040103
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- Article
Advances in Machine Learning Detecting Changeover Processes in Cyber Physical Production Systems.
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- Journal of Manufacturing & Materials Processing, 2020, v. 4, n. 4, p. 1, doi. 10.3390/jmmp4040108
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- Article
ADVANCED CASCADED SCHEDULING FOR HIGHLY AUTONOMOUS PRODUCTION CELLS WITH MATERIAL FLOW AND TOOL LIFETIME CONSIDERATION USING AGVS.
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- Journal of Machine Engineering, 2023, v. 23, n. 3, p. 69, doi. 10.36897/jme/171749
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- Article
A Series Production Data Set for Five-Axis CNC Milling.
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- Data (2306-5729), 2024, v. 9, n. 5, p. 66, doi. 10.3390/data9050066
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- Article
Assessing the Influence of Sensor-Induced Noise on Machine-Learning-Based Changeover Detection in CNC Machines.
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- Sensors (14248220), 2024, v. 24, n. 2, p. 330, doi. 10.3390/s24020330
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- Article
Evaluation of the Influence of Machine Tools on the Accuracy of Indoor Positioning Systems.
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- Sensors (14248220), 2022, v. 22, n. 24, p. 10015, doi. 10.3390/s222410015
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- Article
Enhanced Changeover Detection in Industry 4.0 Environments with Machine Learning.
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- Sensors (14248220), 2021, v. 21, n. 17, p. 5896, doi. 10.3390/s21175896
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- Article