Machine Learning Based Predictive Quality
In steel production, machine learning models explore all possible combinations of how production factors affect quality metrics and defect types. Based on historical defects and all its related process and production data, the data is qualitatively labeled and a defect prediction model is extracted in order to predict future quality defects as early as possible.
For more details on how to reduce production defects and optimize production, visit https://www.psi.de/en/blog/psi-blog/post/how-to-predict-defects-with-machine-learning-acting-instead-of-reacting-part-2/.
In steel production, machine learning models explore all possible combinations of how production factors affect quality metrics and defect types. Based on historical defects and all its related process and production data, the data is qualitatively labeled and a defect prediction model is extracted in order to predict future quality defects as early as possible.
For more details on how to reduce production defects and optimize production, visit https://www.psi.de/en/blog/psi-blog/post/how-to-predict-defects-with-machine-learning-acting-instead-of-reacting-part-2/.
