A synchronous association approach of geometry, process and monitoring information for intelligent manufacturing

Abstract Data driven approach has been an effective means to realize intelligent manufacturing, and it is very important to get really valued data. It is difficult to realize real-time closed-loop control of complex machining conditions by only using monitoring signals without considering the geometry and process information of the workpiece which is being machined. Therefore, the synchronous association of geometry, process and monitoring information is the key to realize data-driven intelligent manufacturing. However, geometry, process and monitoring information is multi-source, multi-modal and heterogeneous data, and both static and dynamic information is involved, so the effectively synchronous association of the information is still a challenge. In order to address the issue mentioned above, the real-time synchronous association relationship among the three kinds of information is established by using the theoretical discrete cutter position points and the actual sampling cutter position point as linkages. In addition to that, time sequence matching and coordinate matching are combined for avoiding miss match of coordinate. Experimental results show that the proposed method can realize synchronous association of geometry, process and monitoring information in real time, and the average lag time for synchronous association at each cutter position point is far less than 0.1 ms, which is shorter than the minimum time period for signal acquisition.