面向航空复杂零件智能工艺规划的孪生工艺模型构建与应用研究

Currently, process planning of complex aviation parts still depends on manual experiences and lacks the coordination between process design and machining. The above issues case the problems like unreliable setting of process plans, un-timely responsive adjustment of machining process, and difficult to control the geometric accuracy and physical performance indicators of complex aviation parts. To bridge the gap, the digital twin is introduced into process planning and a novel reference framework of digital twin process model (DTPM) is proposed. Accordingly, by fusing the on-site data, quality information and process knowledge, the construction methods of data space, virtual space, and knowledge space of DTPM are proposed. Then, the co-evolution mechanism of multiple spaces of DTPM driven by geometric errors and physical performance indexes during machining process is introduced, which realizes the linkage optimization of process design and machining. Finally, aviation thin-walled parts are taken as an example to develop a DTPM prototype. Its application examples show that DTPM could provide supports for aerospace manufacturing enterprises to innovate process planning methods and realize the linkage optimization of process design and machining.