Datathon Kaufland Solution – LSTM and EDM Models for Predictive Maintenance

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In this paper we propose the use of a combination of LSTM and EDM models to address the issue of anomaly classification and prediction in time series data. Working with sensor data for automated storage and retrieval systems for a German hypermarket chain, we show that predictors based on variance and median methods show sufficient promise in the handling of anomalies.