With Operator Training Simulators operators in the control room of process plants can train their skills also in face of potentially hazardous scenarios. Knowledge-graph-based scenario generation can provide semantic descriptions of training scenarios, including faults, operating phases, and learning-related tasks, such as to practice fault diagnosis or decision-making. However, these descriptions must be made executable in a training environment so that operators can receive tasks, observe process behavior, interact with the simulation, and provide responses during scenario execution.

Goals and Tasks

The goal of this thesis is to design and prototypically implement an operator training interface that connects semantic scenario descriptions with an FMU-based simulation environment, e.g., in the form of a web-based application. The focus lies on demonstrating how selected task types can be represented, executed, and evaluated in a simplified training runtime setting.

• Research on operator training simulators, HMI concepts, and task-based training interfaces.
• Develop a concept for representing, displaying, and executing training tasks during simulation.
• Implement a prototype interface for live visualization of simulations and enabling of operator interaction.
• Demonstrate the approach using different task types, e.g., deviation detection and faulty component selection.

Disclaimer: The scope of this thesis can be adjusted depending on whether the student aims for a Bachelor's or Master's thesis. A Master's thesis could focus more on modeling and generalizing task execution, while a Bachelor's thesis could focus more on the implementation of 1-2 specific task types.

Interests and Useful Prior Knowledge

• Interest in modeling and translating abstract scenario descriptions into executable interactions
• Programming experience and enthusiasm for software development
• Experience with Python, FMUs, or web-based interfaces is advantageous