A digital twin defined autonomous milling process towards the online optimal control of milling deformation for thin-walled parts

Thin-walled parts are widely used in the aerospace industry, where the milling deformation of the parts caused by their thin-walled draping and extremely large size ratio characteristics as well as high material removal rate has been the most common quality issue that greatly affects the assembly performance and operation safety of aerospace equipment. Hence, effective management of milling deformation for a thin-walled part will significantly improve its quality, which, however, is still made difficult by the lack of a real-time deformation perception, optimization, and control method. To bridge this gap, a novel online optimal control method of milling deformation for thin-walled parts is proposed by incorporating digital twins into the milling process of thin-walled parts. To this end, a reference framework of the milling process digital twin (MPDT) for thin-walled parts are designed, where the autonomous operation logic of MPDT for online optimal control of milling deformation is further clarified. On that basis, three key enabling technologies of MPDT are introduced from the perspective of multidimensional high-fidelity MPDT modeling, knowledge-driven low-latency milling deformation simulation, and online optimal control of milling deformation, which provide an insight into the industrial implementation of MPDT. Eventually, a MPDT prototype system is implemented, where its application and evaluation results demonstrate the feasibility and effectiveness of the proposed approach.