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Recent advances in information technology systems have enabled organizations to store tremendous amounts of business process data. Process mining offers a range of algorithms and methods to analyze and extract metadata for these processes. This paper presents a novel approach to the hybridization of process mining techniques with business process modelling and simulation methods. We present a generic automated end-to-end simulation framework that produces unbiased simulation models using system event logs. A conceptual model and various meta-data are derived from the logs and used to generate the simulation model. We demonstrate the efficacy of our framework using a business process event log, achieving reduction in waiting times using resource reallocation. The intrinsic idea behind our framework is to enable managers to develop simulation models for their business in a simple way using actual business process event logs and to support the investigation of possible scenarios to improve their business performance.
Mesabbah, M. & McKeever, S. (2018). Presenting a hybrid processing mining framework for automated simulation model generation. Winter Simulation Conference (WSC), Gothenburg, Sweden, pg. 1370-1381. doi: 10.1109/WSC.2018.8632467.