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因此，除了“基于条件的维护-CBM”之外，还需要根据资产和设备的条件执行维护，并且还需要“预测性维护”来检测设备故障或异常的早期迹象，并更快，更有效地执行维护。The technology stack to enable this is as outlined below: • Sensing which enables trend monitoring and data collection on the status of various equipment and facilities by using a wide variety of sensors • Edge computing which enables the development of applications using machine learning libraries, and helps in real-time control and interface with various cloud services • AI and machine learning which automatically analyze collected data and capture the “Anomality” that are signs of abnormality earlier than trend monitoring
工业AI，建立下一代自治操作
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