Research Project: Development of a Framework with AI

The project aims to develop a framework that optimizes adaptive operational and maintenance strategies using reinforcement learning. Real operational data are integrated into digital twins to accurately determine condition forecasts and remaining lifespans. The framework enables flexible adaptation of strategies to variable operating conditions, increases resource efficiency, maximizes the availability of technical systems, and reduces costs. The innovative use of an AI-powered agent allows for the automated optimization of operational and maintenance measures to significantly enhance sustainability and efficiency in technical applications.

> detailed project description (.pdf)