Quality Prediction

IMPROVE provides an innovative holistic decision support system (DSS) and a prediction tool for quality monitoring to assist the machine operator. The decision support app includes a visualisation of cause and effect relations to help the operator in maintaining high quality.

Central characteristics of our user support tools:

  • Supporting operators with results from complex data analysis models
  • Predicting the quality by using data-driven models based on machine parameters
  • Developing of cause and effect graphs for a selected quality parameter, representing the complex causal dependencies of a total plant in regard to the quality parameter
  • Preventing scrap and off-spec products due to in-line quality prediction in comparison to expensive off-line lab measurements

For more information, please contact our coordinator Prof. Dr Oliver Niggemann.

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