Big-data-driven anomaly detection in industry (4.0): An approach and a case study

  title={Big-data-driven anomaly detection in industry (4.0): An approach and a case study},
  author={Ljiljana Stojanovic and Marko Dinic and Nenad Stojanovic and Aleksandar Stojadinovic},
  journal={2016 IEEE International Conference on Big Data (Big Data)},
In this paper we present a novel approach for data-driven Quality Management in industry processes that enables a multidimensional analysis of the anomalies that can appear and their real-time detection in the running system. The approach revolutionizes the way how quality control (and esp. anomaly detection) will be realized in production processes influenced by many parameters that can be in complex nonlinear correlations. It consists of two main steps: learning the normal behavior of the… CONTINUE READING


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