Mesenchymal stem cells are highly relevant candidates for cell based therapies. Since their production is prone to high batch to batch variations, the processes are often automated. Robotic cultivation systems such as the StemCellDiscovery to date are mainly using reactive production schedulers, which can cause suboptimal resource utilization. This thesis investigates whether model based, predictive reactive scheduling is suited to increase efficiency in automated production of stem cells.