Industrial production systems are increasingly affected by complexity, uncertainty, and interdependencies. Ensuring resilience under these conditions requires approaches that go beyond traditional risk management.

The paper “Requirement analysis and approach for Chaos Engineering in industrial production” by Anh Minh Augustino Doan, Leonie Meldt, Tim Bokemüller, Niklas Pohl Joachim Metternich, and Matthias Weigold investigates the transfer of Chaos Engineering, an established methodology in software engineering, to industrial production. The approach is based on deliberately introducing controlled disturbances to analyze system behavior, identify weaknesses, and improve robustness.

A key contribution is the development of a structured process model covering identified requirements and Chaos Experiment design, execution, monitoring, and system improvement. In contrast to conventional risk management methods, Chaos Engineering enables iterative learning directly within the system under realistic conditions.

The applicability of the approach is demonstrated in a learning factory environment, where targeted disruptions are used to evaluate system performance and resilience mechanisms. The results indicate that Chaos Engineering can provide a systematic framework for strengthening resilience in industrial production, particularly in complex and distributed systems.

The article is published in the CIRP Journal of Manufacturing Science and Technology.
Read the full paper here (wird in neuem Tab geöffnet)