Continuous Process Monitoring Through Ensemble-Based Anomaly Detection

Springer International Publishing
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Studies in Classification, Data Analysis, and Knowledge Organization, 2019, pp. 289-301
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© Springer Nature Switzerland AG 2019. In many production processes, a complete quality inspection of all products is not feasible due to technological and organizational restrictions. In order to ensure zero-defect products, monitoring process parameters in real time and using them to predict product quality by supervised learning methods is a very established approached. However, this approach requires a joining of process parameters and quality features. In order to guarantee high-quality products even in the absence of traceability, a continuous process monitoring approach based on an anomaly detection ensemble method is beneficial.
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