Decomposing Temperature Time Series with Non-Negative Matrix Factorization

@article{Weiderer2019DecomposingTT,
  title={Decomposing Temperature Time Series with Non-Negative Matrix Factorization},
  author={Peter Weiderer and Ana Maria Tom{\'e} and Elmar Wolfgang Lang},
  journal={CoRR},
  year={2019},
  volume={abs/1904.02217}
}
During the fabrication of casting parts sensor data is typically automatically recorded and accumulated for process monitoring and defect diagnosis. As casting is a thermal process with many interacting process parameters, root cause analysis tends to be tedious and ineffective. We show how a decomposition based on non-negative matrix factorization (NMF), which is guided by a knowledge-based initialization strategy, is able to extract physical meaningful sources from temperature time series… CONTINUE READING
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