| CPC G05B 13/0265 (2013.01) [D21F 11/00 (2013.01); G05B 23/024 (2013.01)] | 25 Claims |

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1. A method for monitoring a process and/or identifying source(s) of process disturbances or quality defects comprising:
creating a machine learning (ML) model of the process, which ML model utilizes measurements from the process as inputs to the ML model and forms model outputs, and classifying the inputs to groups,
calculating an explanation value of machine learning for each input indicating contribution of the input to the model output/s, and calculating a sum of indication values for each group, the indication values relating to the explanation value of machine learning,
monitoring the calculated sums, each sum indicating status of the group in question, and
controlling, optimizing and/or troubleshooting the process based on the status of one of more of the groups.
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