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M. Borkowski, W. Fdhila, M. Nardelli, S. Rinderle-Ma, S. Schulte:
"Event-based Failure Prediction in Distributed Business Processes";
Report for CoRR - Computing Research Repository; Report No. arXiv:1712.08342, 2017; 20 pages.

Traditionally, research in Business Process Management has put a strong focus on centralized and intra-organizational processes. However, today's business processes are increasingly distributed, deviating from a centralized layout, and therefore calling for novel methodologies of detecting and responding to unforeseen events, such as errors occurring during process runtime. In this article, we demonstrate how to employ event-based failure prediction in business processes. This approach allows to make use of the best of both traditional Business Process Management Systems and event-based systems. Our approach employs machine learning techniques and considers various types of events. We evaluate our solution using two business process data sets, including one from a real-world event log, and show that we are able to detect errors and predict failures with high accuracy.

failure prediction, event-based systems, business process management, machine learning

Project Head Stefan Schulte:
Cloud-based Rapid Elastic MAnufacturing