Process Mining in a Manufacturing Company for Predictions and Planning

Simulationcan be used for analysis, prediction and optimization of businessprocesses. Nevertheless, process models often differ from reality.Data mining techniques can be used to improve these models based onobservations of a process and resource behavior from detailed eventlogs. More accurate process models can be used not only for analysisand optimization, but also for prediction and recommendation as well.This paper analyses process models in a manufacturing company and itshistorical performance data. Based on the observation, a simulationmodel can be created and used for analysis, prediction, planning andfor dynamic optimization. Focus of this paper is in different datamining problems that cannot be solved easily by well-known approacheslike Regression Tree.