In-process identification of milling parameters based on digital twin driven intelligent algorithm

The potential benefits of Industry 4.0 have led to an increased interest in smart manufacturing. To facilitate the self-diagnosis and adaptive ability milling system, a digital twin–driven intelligent algorithm for monitoring in-process parameters is proposed here. can extract radial width cut, axial depth cutter runout parameters, cutting constants end process at same time only by using force sensor. It important breakthrough this paper converge two different models realize cyber-physical fusion identifying process. By convolution model, twin technology approximate solution machining advance, so as narrow range solution. Furthermore, subsequent artificial intelligence find accurate current short calculation with numerical model considering effect. Milling experiments are carried out validate algorithm. shown that due complementary advantages give consider identification accuracy efficiency.