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Abstract：
The digitization of production systems has revolutionized industrial monitoring. Analyzing real-time bottom-up data enables the dynamic monitoring of industrial processes. Data are collected in various types, like video frames and time signals. This article focuses on leveraging images from a vision system to monitor the manufacturing process on a computer numerical control (CNC) lathe machine. We propose a method for designing and integrating these video modules on the edge of a production line. This approach detects the presence of raw parts, measures process parameters, assesses tool status, and checks roughness in real time using image processing techniques. The efficiency is evaluated by checking the deployment, the accuracy, the responsiveness, and the limitations. Finally, a perspective is offered to use the metadata off the edge in a more complex artificial-intelligence (AI) method for predictive maintenance.
摘要：
生产系统的数字化彻底改变了工业监控。分析自下而上的实时数据可以实现对工业过程的动态监控。收集各种类型的数据，像视频帧和时间信号。本文重点介绍利用视觉系统中的图像来监视计算机数控（CNC）车床上的制造过程。我们提出了一种在生产线边缘设计和集成这些视频模块的方法。这种方法检测原始零件的存在，测量过程参数，评估工具状态，并使用图像处理技术实时检查粗糙度。通过检查部署来评估效率，准确性,响应能力,和限制。最后,提供了一种观点，可以在更复杂的人工智能（AI）方法中使用边缘的元数据进行预测性维护。
