I work at the Institute for Production Systems at TU Dortmund University and I am doing my doctorate.
I am currently dealing with the detection of anomalies in time series data, with the main area of application coming from screwdriving systems.
Name: Nikolai West
Type: User
Contribution to the 19th ASIM Conference for Simulation in Production and Logistics
Accompanying repository for a comparative study of machine learning approaches for anomaly detection in industrial screw driving data
Multivariate time series forecasting for multi-step prediction of throughput bottlenecks using Long Short-Term Memory networks
A online webtool for bottleneck prediction from the research project PrEPFlow
Repo for anomaly detection in screw driving data from the ProData project
Data-driven approach for diagnostic analysis of dynamic bottlenecks in serial manufacturing systems
Web app to generate synthetic screw driving data for anomaly detection with class imbalances
Utility repo to help loading screw data
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