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In a rapidly changing and uncertain global environment, the ability of companies to anticipate, absorb and flexibly adapt to disruptions is a key factor for long-term success. This master’s thesis focuses on the identification and evaluation of resilience indicators that describe a company’s status quo in terms of resilience. Based on data management and sustainability principles, the goal is to define which data and metrics are essential to capture resilience across different sustainability dimensions and to explore how these indicators can be integrated into a structured assessment framework that supports decision-making.
The research will be carried out at Fraunhofer IPA, with the supervision support of an interdisciplinary team combining expertise in sustainable production, resource efficiency, and digital transformation. The results are expected to contribute to ongoing research on sustainable and resilient industrial systems, supporting companies in navigating future challenges through better data-driven insights.
Identify relevant data sources and key metrics from case studies or existing frameworks
Develop a conceptual model or data-driven approach for resilience assessment
Validate findings through expert interviews or data analysis (optional)
Student (w/m/d) enrolled in a master’s program at a German institution, ideally in engineering, data sciences, sustainability management, or a related field.
Good English communication skills
Possibility to publish your results and present them in internal or external research forums
Apply online now. Lisa Schäfer
schaefer@ipa.fraunhofer.Fraunhofer Institute for Manufacturing Engineering and Automation IPA