from the conferences organized by TANGER Ltd.
In this article an application of datamining algorithms for early detection of the delays in the process is presented. We used data of the real-world process of customer order fulfillment for industrial robots replacement parts in a multi-branch environment extracted from SAP system event log. Four different algorithms were tested: C&RT, boosted tree, random forest and artificial neural network in order to check their ability to detect if the whole process lasts longer than a specified time.
Keywords: BPM, process mining, data mining, machine learning, logistics process© This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.