Joint Master Thesis RWTH PADS / INFORM GmbH Process Mining in Aviation: The Sky is the Limit!
Aviation is a dynamic field in which a large variety of service providers cooperates in order to facilitate various products and services that together constitute to the aerial transportation of people and goods. The vast amount of different stakeholders active in aviation, leads aviation to comprise of a large body of complex, intertwined and interacting processes. As indicated by Violeta Bulc, EU Commissioner for Transport and Karima Delli, Chair of the European Parliament's Committee on Transport and Tourism, with the expected forecast of 11 million flights throughout Europe, it is of utmost importance that the traffic system is able to cope with the ever-increasing volume of traffic. At the same time, due to the current state of these traffic systems, alongside the large amount of expected flights, roughly 50.000 passengers is expected to face delays on a daily basis, leading to a large amount of unforeseen costs. (1)
In order to overcome the aforementioned challenges and expected delays in aviation, a proper synchronization and orchestration of the different aviation processes is of major importance. Due to the inherent intertwining of the different processes, a small bottleneck in one of these processes typically causes tremendous delays in other processes, hampering the overall efficiency of the aerial passenger- and/or goods handling process. Hence, a clear understanding of the different processes active within aviation, as well as adequate counter measures when bottlenecks and other deficiencies are expected to occur, are key to streamline the overall aviation performance.
The different information systems, used by the different stakeholders active within the aviation industry, allow us to track, often in great detail, the execution of the different processes at play. As such, these information systems allow us to obtain valuable traces of event data. Recent developments in the research field of process mining, which represents a large body of data driven analysis techniques on the basis of such event data, allows us to gain detailed insights in the execution of these processes. The advantage of deriving insights in processes based on operational data relates to the fact that we observe what actually happened, i.e. as captured by the data. However, the current state of the field of research is still rather "a-posteriori", i.e. one is able to exploit all kinds of tools and techniques that allow us to investigate in great detail what happened during the execution of a process, what went wrong and why this is the case.
In this MS.c. thesis project, which is a joint project of INFORM GmbH, which provides information systems for aviation world-wide, and the RWTH PADS chair, the student is asked to investigate the application of process mining, in the context of aviation data. Initially, a complex data set needs to be analysed, describing the arrival and departures of different flights. Based on the analysis, the student, in cooperation with the supervision team (both from RWTH and INFORM), the relevant aviation-specific problems will be identified, investigated and solved in a generic fashion.
This is a unique opportunity to work on real data and get in direct exposure in industry. Moreover, it is very likely that the tools and techniques developed in the context of this MS.c. thesis work will be adopted in practice!
Knowledge of basic computer science concepts, good programming skills (Java/Python) and an interest in theoretical and practical aspects of process mining (i.e. conformance checking) recommended.
- Process Mining Book
- Coursera Process Mining Course
- Paper: Replaying History on Process Models for Conformance Checking and Performance Analysis
- PDF: Replaying History on Process Models for Conformance Checking and Performance Analysis
- Paper (PDF): PM^2: a Process Mining Project Methodology
Prof.dr.ir. Wil van der Aalst
Sebastiaan van Zelst
Send an e-mail to Sebastiaan van Zelst. Make sure to include detailed information about your background and scores for completed courses.