Master Thesis MSTR-2016-89

BibliographyWiriyarattanakul, Thatchanok: Combination usage of process mining and adaptive case management.
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Master Thesis No. 89 (2016).
109 pages, english.

Process mining performs well on structured processes like BPM. In recent years, Adaptive Case Management (ACM) was introduced to support knowledge workers by giving them the permission to define processes on the fly in unpredictable situations. By doing so, processes seem to be unstructured and hard to be enhanced. The goal of this thesis is to analyze how process mining can improve and benefit unstructured processes and to develop a prototype for a potential application. The scenario analysis focuses on (1) supporting knowledge workers with process mining, (2) transiting from unstructured to structured processes through process mining, and (3) compliance regulations in unstructured processes through process mining. One scenario is selected based on the analysis for implementing a prototype. Due to the importance of compliance regulations and rare researches on compliance regulations in unstructured processes, the scenario (3) is selected and an approach of compliance checking for unstructured processes using process mining is proposed. The prototype of the approach leverages process mining to discover hidden structured in unstructured processes and implements compliance checking functionalities consisting of graphical rule definition, rule creation and rule checking on a log in Oryx platform. The prototype visualizes violating paths on the process model and reports all violating process instances. The evaluation proves that the prototype is indeed capable of compliance checking with a large real-life data log.

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Department(s)University of Stuttgart, Institute of Architecture of Application Systems
Superviser(s)Leymann, Prof. Frank; Kötter, Falko
Entry dateJune 19, 2019
   Publ. Institute   Publ. Computer Science