The invention relates to a multi-process planning comprehensive 
evaluation system and method based on digital twinning and 
deep learning, and belongs to the field of process planning virtual 
simulation. The 
system comprises a physical equipment layer, a data sensing layer, an 
information processing layer, a 
virtual space layer and a digital twinning layer, the data sensing layer collects related real-
time data and historical data of the physical equipment layer in the 
machining process and sends the data to the 
information processing layer for data fusion analysis and 
processing; meanwhile, the acquired data is transmitted to a 
virtual space layer, and a dynamic 
virtual model corresponding to the 
physical entity is constructed under the guidance of requirements of related models in a digital twinning layer; the digital twinning layer is used for leading the other 
layers together, carrying out virtual-real interaction feedback, fusion analysis and iterative optimization, and carrying out comprehensive evaluation analysis on different process schemes of the to-be-processed part, so that process parameter optimization and process 
route improvement are realized. According to the method, the flexibility and dynamic adaptability of process planning are improved, the 
resource utilization rate can be improved, the 
processing period is shortened, and the production cost is reduced.