Abstract
As a typical manufacturing equipment, CNC machine tool (CNCMT), which is the mother machine of industry, plays an important role in the new trend of smart manufacturing. As the requirement of smart manufacturing, the abilities of its self-sensing, self-prediction and self-maintenance are necessary. In order to make CNCMT become more intelligent, a research about Digital twin (DT) for CNCMT is conducted. In this research, a multi-domain unified modeling method of DT is established, a mapping strategy between physical space and digital space is explored, and an autonomous strategy of DT is proposed. These methods can optimize the running mode, reduce the sudden failure probability and improve the stability of CNCMT. Finally, this paper provides a demonstration of DT model building and using strategy in fault prediction and diagnosis for CNC milling machine tool.
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The work is supported by National Natural Science Foundation of China (Grant no. 51405270).
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Luo, W., Hu, T., Zhang, C. et al. Digital twin for CNC machine tool: modeling and using strategy. J Ambient Intell Human Comput 10, 1129–1140 (2019). https://doi.org/10.1007/s12652-018-0946-5
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DOI: https://doi.org/10.1007/s12652-018-0946-5