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Exploring the opportunities of Process Mining and Machine Learning for the Creation of a Digital Twin of an Organization

Informationen zur Arbeit

Abschlussarbeitstyp: Bachelor, Master
Betreuer: Clemens SchreiberAndreas Oberweis
Forschungsgruppe: Betriebliche Informationssysteme
Partner: Bee360Miele
Archivierungsnummer: 4807
Abschlussarbeitsstatus: Offen
Beginn: 01. Dezember 2021
Abgabe: unbekannt

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A Digital Twin of an Organization (DTO) expands the existing concept of digital twins ( The increasing interconnectedness of in-house IT, cloud systems, and IoT allows organizations to gather and integrate data from a wide variety of digital endpoints to create a digital representation of their organization and its interfacing ecosystem—from the first supplier to the last customer. Increasing interconnectedness, along with the benefits of digital twins, led to a surge in adoption of DTOs during the past five years towards its preliminary peak. It does not seem to have stopped here.

There exist two main challenges when it comes to the creation of a DTO [1]: (1) the definition of the organizational boundaries, i.e., regarding customers, suppliers and employees and (2) the human and organizational behaviour, which changes over time and cannot be easily predicted. Process Mining and Machine Learning techniques can help to find solutions to these challenges and provide a realistic replication of an organization. The task of this thesis is to explore the requirements and opportunities of these techniques and to implement a prototype, similar to the one described in [2].

To show that the DTO can actually serve as operative support, you will work with the example of Miele, a globally active manufacturer of domestic appliances. The foundation for the creation of the DTO is provided by Miele’s global IT Management platform Bee360. Bee360 provides the basis for corporate process documentation and integrates various tools like GitLab, Jira, Confluence, and SAP. An intermediate target will be to describe requirements for the creation of an enhanced DTO based on Bee360.

Relevant Literature:

[1] van der Aalst, W.M.P., Hinz, O. & Weinhardt, C. (2021). Resilient Digital Twins. Bus Inf Syst Eng 63, 615–619.

[2] Park, G., & Van Der Aalst, W. M. Realizing A Digital Twin of An Organization Using Action-oriented Process Mining (2001). In 3rd International Conference on Process Mining (ICPM) (pp. 104-111), IEEE.

[3] M. Camargo, M. Dumas, L. Garc ́ıa-Ba ̃nuelos, I. Mahdy, and M. Yerokhin (2021). Discovering business process simulation models in the presence of multitasking and availability constraints. Data and Knowledge Engineering, 134.

[4] van der Aalst, W. M. (2021). Concurrency and objects matter! Disentangling the fabric of real operational processes to create digital twins. In International Colloquium on Theoretical Aspects of Computing (pp. 3-17).