Internationally growing flight and passenger numbers have led to a joined order backlog of Airbus and Boeing of approx. 12,500 aircrafts. With today’s production rates the delivery of all aircrafts would take 8.5 years. The resulting endeavor for higher productivity requests more flexible manufacturing solutions. A bottleneck in production is the machining of large aircraft components. These components are commonly machined by vast portal machines. Due to time-consuming referencing processes, cost-effectiveness of these high-invest-machines is often non-satisfying. Mobile robots already have proven their advantages for drilling and fastening applications performing short, high-accuracy movements. With mobile robot-based solutions machining processes can be executed simultaneously which increases the productivity significantly. However, machining paths often have the same dimension as the component itself. To overcome the limited workspaces of robots, these machining tasks have to be divided and long trajectories are separated in single overlapping segments. The machining of each segment requires repositioning of the mobile system and thus also a referencing process to resume the milling edge. Hence high-accuracy referencing strategies are required to achieve desired production tolerances of a few tenths of millimeters. In this publication different advanced optical reference strategies will be discussed taking the inhomogeneous behavior of a mobile robotic machining system into account. The realized system consists of a mobile platform and a CNC-machining robot. The determination of the reference between the mobile system and the component is based on an optical referencing process using a Laser Tracker and targets on the mobile system. Investigations on the absolute positioning and the machining accuracy have shown the impact of different referencing strategies on the resumption of milling edges especially for large work spaces. It can be concluded that advanced referencing strategies for mobile machining systems yield a sufficient accuracy and enables more flexible production solutions for the Future Factory.