A tool for mining discrete event simulation model

Mining a discrete event simulation model from data has always been a big challenge, which is related to the problem of system inference in systems theory. D2FD (Data to Fuzzy-DEVS model) method can be used to discover a discrete event simulation model. This method not only provides a way of data mining but also integrates process mining with the modularity, frequency, timing aspects and event data. This paper presents a mature tool applying D2FD method. This tool is implemented as an available and dedicated plug-in within the open-source process mining toolkit ProM. The simulation tool SimStudio is embedded in this plug-in and it can simulate Fuzzy-DEVS atomic and coupled model. Two case studies of real life processes, taken from Rabobank Group ICT and Dutch Employee Insurance Agency, are analyzed to evaluate this tool.