AIBIZ Co., Ltd. (CEO Ha Seung-jae) announced that it has registered a patent for 'a method, device and program for detecting anomalies in process equipment by integrating a plurality of anomaly detection techniques.' The patent focuses on overcoming the limits of process data management and analysis done manually by workers in various manufacturing processes. In an organically linked manufacturing process system, if an anomaly occurs in some process equipment, defects can occur in the entire process and in products. Existing process equipment anomaly detection systems require skilled workers to manually check vast amounts of data. It is difficult for workers to review all real-time data, and less experienced workers find it hard to accurately judge anomalies in the data. This patent automatically detects anomalies in process equipment by integrating a plurality of anomaly detection techniques. It uses the large amounts of data generated during semiconductor manufacturing processes (Bin, PCM, Wafer Map, FDC Data). AI technology analyzes defect patterns and efficiently detects abnormal data. The technology can be applied to various industrial fields, including semiconductor manufacturing processes. AIBIZ explained that an automated anomaly detection system can reduce variation in workers' skill levels and improve the yield of the entire process through rapid on-site response based on real-time data analysis. Ha Seung-jae, CEO of AIBIZ, said, "Following the previously published patent 'Method for training a deep learning model for detecting abnormal operation of factory equipment,' this patent will bring benefits in many areas, such as productivity improvement and yield improvement in the manufacturing industry," and "going forward, AIBIZ will present a new paradigm of real-time process diagnosis AI and innovate existing industry practices based on solid technological capability."