Theses

Topics

Below you will find the subject areas and specific problem statements for which you can write Bachelor's or Master's theses with our department.

General topics for which we conduct thesis work include:

• Intelligent Automation / Hyperautomation
• Business Process Simulation (BPS)
• Sustainability in BPM
• Resource Allocation in Business Processes
• Explaining Activity Dependencies.
   

Concrete Topic Suggestions

Leveraging Process Engines for Business Process Sustainability Analyses (Bachelor Thesis)

The enactment of business processes can have a negative impact on the environment, meaning that environmental impacts of business processes need to be analysed. One existing framework, the SOPA framework, uses lifecycle assessments (LCA) to incorporate this impact. However, the analyses happen on a level that abstracts from real-world process executions. During run-time, process engines used to execute processes can be used to a) track run-time data and b) require user input on certain activities so that the environmental impact analyses can be made more exact. Relevant for this is an understanding of the base units used in LCA, which can be used for refinement of the analyses.
Goal: Extend a business process engine so that additional data relevant for environmental impact analyses can be put in/tracked during execution time. Evaluate this with an example.
 

Proactive Human Interfaces for Intelligent Process Automation

Business process engines that are augmented by AI promise highly autonomous process orchestration. However, human process participants are still integral to the processes executed. Consequently, the human-machine interface must include functionalities for the system to proactively contact human actors, e.g., to ask for recontextualization, to escalate decisions in unknown situations, or to create awareness of abnormal situations.
Goal: Identify requirements for the human interface of intelligent process automation systems. Conceptualize how these requirements can be implemented and create a prototype.
 

Model-driven Multi-Source Discovery of Simulation Models

Business process simulation is a key method for predictive process improvement. The more precise a simulation model reflects (potential) reality, the more valuable insights can be derived from it. To this end, information from multiple sources, such as process mining tools, databases, and human knowledge must be considered. This presents a challenge to simulation experts, who then need to manually integrate different tools and their data formats. Visual models promise to make simulation model discovery pipelines tangible and automatable, addressing this challenge.
Goal: Develop a user-friendly mechanism to generalize the integration of different tools for the discovery and parameterization of business process simulation models. Evaluate the developed artifact.
 

Analysis and categorization of existing public event logs

Event logs capture the actual workflows within a company, identifying deviations, recognizing bottlenecks, and pinpointing inefficient activities. As an objective data source, they are often used for evaluating proposed approaches and ideas within the community. They enable scientists and practitioners to empirically study business processes, develop new models, and suggest improvements. However, a problem arises as event logs are often distributed across various websites and formats, lacking a central overview. Finding the appropriate dataset for a specific analysis or evaluation in business process management is time-consuming and challenging.
Objective/Task: Compile an overview of available data in the BPM area and explain which datasets suit the different application areas. Find an appropriate grouping that maps process datasets to BPM-related research questions.
 

Case Study: Documentation of a Knowledge-Intensive Process

To test and experiment with ideas and newly developed approaches in the BPM area, we need real-use case scenarios that illustrate challenges and allow the testing of developed techniques. This thesis focuses on documenting a business process, with the domain being freely chosen. In addition to creating a process model, the focus is on defining dependencies between activities and the contextual influence on the process. Furthermore, an extended event log will be generated, e.g., through simulation of the process model, containing attributes that capture the contextual information.
Objective/Task: Provide a use case where all activity dependencies are specified and the contextual influence is clearly defined. A process model should be designed, and an event log generated.
 

Analysis of Temporal and Existential Dependencies in Fragment-Based Case Management (Master Thesis)

In today's dynamic business environment, processes must continually adapt to changing conditions, regulations, and evolving circumstances. The modification of process behavior is referred to as Business Process Redesign (BPR). Business process models serve as the foundation for BPR, but they only show a subset of dependencies since they are created with a specific modeling goal in mind. To ensure a correct changing operation of a relation, it has been proven that hidden, implicit dependencies can be revealed by adding so-called existential dependencies to the process model. In conjunction with temporal dependencies, they define various types of relationships between activities. The translation into temporal and existential dependencies has been demonstrated for the Business Process Model and Notation (BPMN), an imperative modeling language. For semi-structured processes that exhibit a high degree of flexibility but still possess imperative structures, the fragment-based Case Management (fCM) modeling approach can be used. To utilize fCM process models for BPR, a translation into temporal and existential dependencies must be established. Furthermore, we want to investigate to what extent it is possible to identify fragments based on temporal and existential dependencies. This is a purely conceptual thesis. Programming knowledge not required.
Objective/Task: Find a translation from a given fCM process model into temporal and existential dependencies. Additionally, investigate how fragments can be identified based on temporal and existential dependencies and explore the underlying principles.
 

MT: Analysis of N-ary Activity Relationships Based on Temporal and Existential Dependencies (Master Thesis)

To model business processes characterized by a high degree of flexibility, known as knowledge-intensive processes (KiPs), declarative modeling languages have been developed. In contrast to imperative languages that focus on the execution sequence of activities, declarative languages represent the process based on conditions. The temporal sequence of activities takes a back seat, often requiring knowledge workers to decide which activity to perform. In addition to DECLARE and DCR-Graphs, there is an approach that models the temporal and existential dependencies between activities. A type of relation is defined by the combination of temporal and existential dependence. However, these relationships between activities have always been defined as binary relations. If we examine a simple XOR relationship between three activities A, B, and C, where C and B are in an exclusive relationship, a dependency between the three activities can be identified: Once A is executed, either B or C is executed immediately afterward. Such a type of dependency cannot yet be explicitly represented. The aim of this master's thesis is to discover regularities in activity relations and identify patterns. When are more than two activities related, what n-ary relations exist, and how can they be represented?
Objective/Task: Develop a conceptual approach for representing n-ary relationships between activities. Find regularities in the combination of binary relations and provide an overview of n-ary relation types. Utilize the approach of temporal and existential dependencies for this purpose.
 

Identification of the Contextual Origin and Vulnerability of Activity Relations based on LLMs and NLP (Bachelor Thesis)

Business processes must continually adapt to changing conditions, norms, and a dynamic environment. Methods and techniques are provided by the field of Business Process Redesign (BPR). Using process models, process behavior can be adjusted by modifying relations between activities. However, to perform a change operation, it must be ensured that the respective relation can be changed, i.e., violated. The vulnerability level of an activity relationship is often defined by the context, including the origin and motivation. For instance, a natural law cannot be changed, while a law or a best practice can, but with different consequences. This bachelor thesis topic aims to explore the potential of Large Language Models (LLMs) and Natural Language Processing (NLP) in extracting significant information regarding the origin and vulnerability of activity relations from text sources. The goal is to provide an overview of methods and tools that could assist in this task and to develop initial conceptual approaches.
Objective/Task: Conduct a literature review and present relevant approaches in the areas of LLM/NLP and Business Process Management that can be utilized for gathering information regarding the origin and vulnerability of an activity relation. Explore the potential of LLMs and NLP in this context. Additionally, develop initial conceptual approaches.