Considering initiatives like Industry 4.0 or the Industrial Internet of Things, robots will play an important role in intelligent factories, producing highly customized products with high variability and in small lot sizes. In this setting, complexity of planning and programming such robotic applications grows due to the drastic increase in flexibility, performance and robustness required. In this paper, we propose a tool-supported methodology for the development of control software for dynamically forming multi-functional robot teams. The main challenges for achieving this overall goal are modeling of robot team skills, techniques for automatically deriving process steps from the products’ construction plans, finding allocations of those steps to possible robot teams with compatible skills and calculating collision-free execution schedules with a high degree of parallelization to improve cycle times. The proposed approach integrates process experts and automation experts on all levels. Two case studies will serve as test beds to the developed approach: production of carbon-fiber reinforced polymers and assembly of furniture.