In order to improve the intelligent management and control capabilities of CNC machining processes

the data acquisition requirements for intelligent management and control of machining processes are analyzed. The characteristics of various types of data are sorted out in real-time

data volume

structured degree

access speed

and scalability. Based on this

multi-source heterogeneous data which include manufacturing situation data

real-time process data and product inspection data

are divided into three categories: non-real-time structured data

real-time process data

and historical process data. Data organization and management strategies that incorporate data management methods such as memory databases

relational databases

non-relational databases

and technical data management streaming (TDMS) files

enable the integrated management of manufacturing situation data and process data. Finally

the application of intelligent management and control of a typical thin-walled rotating part CNC machining process is taken as an example to verify the feasibility and effectiveness of the proposed method.