Predictions for open processes can be calculated using a machine learning model that is integrated into mpmX. When selecting a case that has not been completed, the most likely subsequent steps, including the expected time, are calculated based on context data or previous process steps. Which parameters are taken into account for the prediction of the next process steps can be preconfigured individually.

 

 

 

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You can read here how machine learning / simulation models are integrated into mpmX.