Master’s Thesis - Leveraging AI for Simulation Model Development

AFRY provides engineering, design, digital and advisory services. We are devoted experts in industry, energy and infrastructure sectors, creating impact for generations to come. AFRY has Nordic roots with a global reach.

Background

Discrete Event Simulation (DES) is widely used to analyze, design, and optimize complex industrial systems. Developing simulation models often requires considerable effort for data preparation, model construction, validation, experimentation, and documentation.

Recent advances in Artificial Intelligence (AI) have created new opportunities to support simulation engineers throughout the modeling process. AI-based tools may assist with tasks such as interpreting requirements, generating model structures and components, supporting validation activities, automating repetitive tasks, and improving decision-making.

This thesis investigates how AI can be leveraged to improve efficiency, quality, and ease of simulation model development.

Objectives

The objective of this thesis is to investigate how Artificial Intelligence can support the development of simulation models and improve the productivity of simulation engineers.

Specific objectives may include:

· Identify simulation development activities that can benefit from AI support.

· Evaluate how AI can assist in transforming system requirements into simulation models.

· Investigate AI-supported approaches for model creation, verification, and validation.

· Explore opportunities to automate repetitive and time-consuming modeling tasks.

· Develop and evaluate one or more proof-of-concept solutions for AI-assisted simulation modeling.

· Assess the benefits, limitations, and practical applicability of AI-assisted modeling workflows.

Methods

· Literature Study: Review existing research on AI applications in simulation modeling and engineering.

· Modeling Workflow Analysis: Analyze simulation development workflows to identify opportunities for AI support.

· Use Case Definition: Define and evaluate AI use cases that support simulation model development and analysis.

· Concept Development: Design and prototype AI-assisted capabilities for simulation model development and analysis.

· Implementation: Develop one or more proof-of-concept solutions using relevant AI technologies and frameworks.

· Evaluation: Evaluate AI-assisted simulation solutions through practical case studies focusing on efficiency, quality, usability, and industrial value.

Deliverables

The expected deliverables should include well-documented paper and a demonstration for the simulation team, covering the following:

· AI-assisted proof-of-concept solution for simulation model development

· Demonstration case study

· Evaluation of AI's impact on simulation modeling efficiency and quality

· Best practices for applying AI in simulation projects

· Recommendations for future AI-assisted simulation workflows

Research Questions

The thesis should address some of the following questions:

1. How can AI support simulation engineers during simulation model development?

2. Which simulation modeling tasks are most suitable for AI assistance?

3. How can AI reduce the time and effort required to build simulation models?

4. Can AI improve model verification, validation, and debugging activities?

5. How can AI support the generation of model logic and simulation scenarios?

6. What limitations and risks exist when using AI to support simulation model development?

7. How does AI-assisted model development compare with traditional development approaches regarding efficiency, quality, and usability?

8. Which AI-enabled capabilities provide the greatest value in industrial simulation projects?

We are looking for 2 students with a background in one of the following master’s programs (or similar):

· Production engineering

· Systems, control and mechatronics

· Supply Chain Management

We believe that suitable students have completed one or more simulation courses with good grades and possess solid theoretical knowledge, practical experience and a strong interest in production systems and/or production logistics environments. Curiosity about working as a consultant is an advantage. Candidates must be fluent in both Swedish and English.

The master’s thesis will be carried out at AFRY’s office in Gothenburg during the spring semester of 2027.

Contact information:

Niklas Palm, [email protected], Team Leader Simulation, AFRY Supply Chain Management

Please remember to attach both students’ CVs to the application. Applications will be reviewed on an ongoing basis, and the application deadline is November 20, 2026.

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