Fault prediction in surface treatment process using artificial intelligence

A computer-implemented method for fault classification of a surface treatment process, the method comprising: receiving one or more process parameters of the surface treatment process that affect one or more fault modes; and receive sensor data relating to measurements of one or more process states relating to the surface treatment process. The method includes processing, by a machine learning model deployed on an edge computing device that controls the surface treatment process, the received one or more process parameters and sensor data to produce an output that indicates, in real-time, a probability of process failure by one or more failure modes. The machine learning model is trained under a supervised learning mechanism based on process data, and fault classification tags obtained from physical simulation of a surface treatment process, and historical data related to the surface treatment process. 一种用于表面处理过程的故障分类的计算机实现的方法，该方法包括：接收表面处理过程的影响一个或多个故障模式的一个或多个过程参数；并且接收与表面处理过程相关的一个或多个过程状态的测量相关的传感器数据。该方法包括由部署在控制