Closed Loop Manufacturing 4.0

本项目根据工业4.0原则提出了一个闭环制造过程，具有基于物理的仿真模型，在线监控和实时过程控制。加工过程**将在物理生产之前在虚拟环境中进行模拟，并存储在云或**数据库中。实时加工信息，如切削力和振动，将从固有的CNC（计算机数控）系统数据中获得。预模拟结果和实时测量将结合使用，以调整加工条件，以抑制颤振，防止刀具过度磨损，避免机器过载，同时最大限度地减少生产周期时间。因此，一个所谓的数字孪生加工系统（即仿真与实时的结合）将被开发出来，其核心功能包括仿真、监控和自优化。**该项目的具体目标包括：(1)利用主轴电流识别刀尖动力学以避免颤振；(2)利用进给驱动电流在线监测刀具磨损；(3)轨迹规划和进给量**优化，提高生产率；(4)用于切削力监测的进给驱动动力学识别；**和(5)将算法集成到商业上可行的加工仿真和监控软件中。**项目成果将用于通过增强智能加工功能来减少加工时间和零件废品率。将开发并应用于大批量生产的商业产品，以及用于小批量和高度定制型零件的**。该项目预计将使航空航天、汽车、工业机械和生物医学设备等关键制造业受益。

This project proposes a Closed Loop Manufacturing process with physics-based simulation models, online**monitoring, and real-time process control in accordance with Industry 4.0 principles. The machining process**will be simulated in a virtual environment ahead of physical production and stored in the cloud or in a**database. Real-time machining information, such as cutting force and vibration, will be obtained from inherent**CNC (Computer Numerical Control) system data. The pre-simulated result and real-time measurement will be**used in conjunction to adjust the machining conditions for suppressing chatter vibrations, preventing excessive**tool wear, and avoiding machine overloads, while minimizing the production cycle time. As a result, a**so-called digital twin machining system (i.e. combination of simulation and real-time) will be developed with**core functionalities in simulation, monitoring, and self-optimization.**Specific aims of this project include: (1) Identification of tool tip dynamics using spindle current for chatter**avoidance; (2) Online tool wear monitoring using the feed drive current; (3) Trajectory planning and feedrate**optimization for productivity increase; (4) Identification of feed drive dynamics for cutting force monitoring;**and (5) Integration of the algorithms into a commercially viable machining simulation and monitoring**software.**The project results will be used to reduce machining time and part scrap rates by enhancing intelligent**machining feature. A commercial product will be developed and applied for high volume production, as well as**for low volume and highly customized type of parts. The project is expected to benefit key manufacturing**sectors such as aerospace, automotive, industrial machinery, and biomedical devices.