Sebastian Stemmler

Papers

Total Citations

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About

Sebastian Stemmler’s research centers on intelligent control systems for industrial automation, with a particular focus on model predictive control (MPC) and robotics in manufacturing and logistics. His work addresses critical challenges in both precision machining and material handling. In his 2019 paper on model predictive force control for grinding, Stemmler tackled the labor-intensive nature of mold manufacturing, proposing a lightweight robot-based system to automate a process that often forces production to low-wage countries due to unattractive working conditions. This contribution, which has garnered 11 citations, directly confronts the skilled labor shortage in the die and mold sector. Simultaneously, Stemmler has advanced crane automation through his work on predictive anti-sway control for knuckle boom cranes, a 2019 study with 6 citations. By developing model-based controllers that inhibit dangerous load oscillations, he enhances both safety and efficiency in offshore cargo handling—a vital component of global logistics. Stemmler’s work exemplifies how applied control theory can transform hazardous or repetitive manual tasks into automated, reliable processes, making him a notable contributor to the future of smart manufacturing and autonomous heavy machinery.