The evolution of manufacturing towards intelligent and digital processes requires innovation in machining quality control. While current research primarily addresses single-scale quality control, it overlooks comprehensive multi-scale product quality characterization. Digital twin technology emerges as a potential solution. This review examines digital twin applications in machining quality control, highlighting limitations of traditional methods and exploring multi-scale quality characterization at macro, meso, and micro levels. It evaluates multi-scale quality changes during processing and summarizes comprehensive characterization methods across scales. The study concludes by discussing future prospects for digital twin technology in multi-scale machining quality control and optimization.

中文翻译：

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数字孪生驱动的加工质量多尺度表征：现状、挑战和未来前景


制造业向智能和数字化流程的演变需要加工质量控制方面的创新。虽然目前的研究主要涉及单尺度质量控制，但它忽视了全面的多尺度产品质量表征。数字孪生技术成为一种潜在的解决方案。这篇综述研究了数字孪生在加工质量控制中的应用，强调了传统方法的局限性，并探索了宏观、中观和微观层面的多尺度质量表征。它评估了加工过程中的多尺度质量变化，并总结了跨尺度的综合表征方法。该研究最后讨论了数字孪生技术在多尺度加工质量控制和优化中的未来前景。