Maximilian Selmair

After many years in the automotive industry, I extend the benefits of dynamic simulations to diverse sectors and organizations. With ROI≡EFESO, I am developing data-driven simulation models across various professional domains worldwide.

As a Simulation Engineer at Tesla, I work on a wide range of projects, with a focus on solving complex problems that cannot be resolved through traditional, static calculations. I utilize AnyLogic simulation software, which enables us to analyze systems over extended virtual timeframes and account for the inherent randomness present in day-to-day manufacturing processes. These simulation studies provide us with the confidence necessary to make informed decisions before implementing solutions.

My thesis investigates optimisation techniques for scheduling an online autonomous mobile robot system for pickup and delivery with stochastic transportation requests revealed sequentially over a rolling horizon. In contrast to further research, the focus belays in a large-scale specification with a high traffic density, i.e. 100 robots in an assembly hall with 50,000 m². The aim of this study is to develop interoperable scheduling modules for an optimal overall performance of an AMR system.