As a typical manufacturing equipment, CNC machine tool (CNCMT) is the mother machine of industry. Fault of CNCMT might cause the loss of precision and affect the production if troubleshooting is not timely. Therefore, the reliability of CNCMT has a big significance. Predictive maintenance is an effective method to avoid faults and casualties. Due to less consideration of the status variety and consistency of CNCMT in its life cycle, current methods cannot achieve accurate, timely and intelligent results. To realize reliable predictive maintenance of CNCMT, a hybrid approach driven by Digital Twin (DT) is studied. This approach is DT model-based and DT data-driven hybrid. With the proposed framework, a hybrid predictive maintenance algorithm based on DT model and DT data is researched. At last, a case study on cutting tool life prediction is conducted. The result shows that the proposed method is feasible and more accurate than single approach.

作为典型的制造设备，数控机床（CNCMT）是工业的母机。如果不及时排除故障，CNCMT的故障可能会导致精度降低并影响生产。因此，CNCMT的可靠性具有重要意义。预测性维护是避免故障和人员伤亡的有效方法。由于较少考虑CNCMT在其生命周期中的状态变化和一致性，因此当前方法无法获得准确，及时和智能的结果。为了实现CNCMT的可靠的预测维护，研究了一种由Digital Twin（DT）驱动的混合方法。这种方法是基于DT模型和DT数据驱动的混合。在提出的框架下，研究了基于DT模型和DT数据的混合预测维护算法。最后，进行了切削刀具寿命预测的案例研究。结果表明，所提出的方法比单一方法可行，准确。