基于数字孪生的复杂产品装配过程管控方法与应用

Aiming at the issues including the real-time and comprehensive visual monitoring, the analysis and prediction of the operating status, an assembly process management and control method for complex products based on digital twin was proposed. A digital twin model for the assembly process management of the complex product was constructed. On this basis, the real-time collection and management of assembly process data was achieved based on workflow technology. Then, the real-time data-driven synchronized operation of the shop-floor digital twin was proposed. Afterwards, through combining application of grey Markov predictive model, T-K statistical control chart and association rule algorithm, the real-time prediction and analysis of small sample quality data in the assembly process of the complex product were realized. A digital twin-based assembly process management and control system for complex products was developed and verified in a satellite assembly shop-floor.