Problem
Research questions and friction points this paper is trying to address.
Cyber-Physical Machine Tool
Digital Twin
Machining Process
Synchronization
Real-Time
A Cyber-Physical Machine Tool Framework with a Real-Time Machining Process Digital Twin
🤖 AI Summary
本文提出了一种同时维护机床和加工过程数字孪生的层次框架，通过集成实时CNC数据等方法，提高了加工过程的同步性和可追溯性。
📝 Abstract
Digital Twins (DTs) have emerged as a key technology for improving the monitoring, optimization, and automation of manufacturing systems. However, existing Cyber-Physical Machine Tool (CPMT) implementations primarily represent the machine tool, while the machining process remains only partially synchronized with its physical counterpart. This paper extends a previously presented CPMT framework by introducing a hierarchical DT framework that simultaneously maintains DTs of both the machine tool and the machining process. The proposed framework integrates real-time CNC operational data, a voxel-based workpiece representation, synchronized process vibration measurements, and a persistent part DT repository for process replay, traceability, and future synthetic data generation.
Experimental evaluation demonstrated real-time operation at a 20 Hz machining-state update rate, interactive visualization exceeding 100 frames per second, and a mean depth reconstruction error of 0.16 mm. The implementation provides a foundation for AI-assisted machining applications while preserving the machine tool monitoring and teleoperation capabilities.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Hierarchical Digital Twin Framework
Real-Time CNC Data Integration
Voxel-Based Workpiece Representation
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