Extracting control variables of casting processes with NMF and rule extraction

•Temperate time series profiles from casting processes via Non-Negative matrix factorization•Rule extraction from NMF results in reduced dimensional data spaces.•Rules evaluate the physical meaning of the temperature profiles.•Interpretable rules assist operators during casting processes. Process monitoring and optimization in an industrial setting is a complex topic, a large amount of data is captured and its measurements are affected by many complex relations. There is, therefore, a growing necessity for methods to reduce its complexity and dimension such that it can be interpreted by humans. In this work we study the extraction of interpretable rules derived from components of a non-negative matrix factorization using real data.