Master Thesis - Process Mining and Simulation: A Match made in Heaven!

Contact

Prof. Dr. Wil van der Aalst

Name

Wil van der Aalst

Chairholder

Phone

work
+49 241 80 21900

Email

E-Mail
 

Description

Event data are collected everywhere: in logistics, manufacturing, finance, healthcare, customer relationship management, e-learning, e-government, and many other domains. The events found in these domains typically refer to activities executed by resources at particular times and for particular cases. Process mining provides a novel set of tools to exploit such data.

Event data can be used to discover the real processes, to detect deviations from normative processes, and to analyze bottlenecks and waste. However, process mining tends to be backward-looking. Fortunately, simulation can be used to explore different design alternatives and to anticipate performance problems. Through simulation experiments various “what if” questions can be answered and redesign alternatives can be compared with respect to key performance indicators. However, making a good simulation model may be very time consuming and models may be outdated by the time they are ready. Therefore, process mining and simulation could complement each other well.

This Master thesis aims to look at the interplay between process mining an simulation. How can simulation be used to make process mining more forward looking? How can process mining be used to monitor running simulations. The project will include the selection of an existing simulation engine and the development of building bridges between the selected simulation software and process mining tools like ProM.

Prerequisites

Good programming skills and knowledge of basic computer science concepts. An interest in process mining and simulation.

Pointers

Supervisor

Prof. Wil van der Aalst

Advisor

TBD

For more Information

Send an e-mail to . Make sure to include some information about your background and scores for completed courses.