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“The issue with the evaporation dust reflux pump P106 was able to be detected and resolved in advance, thanks in large part to the ’intelligent brain’ for equipment management; artificial intelligence technology has truly enabled predictive maintenance of equipment. ”Recently, Li Jiaqi, a technician from the Second Refining Department of Cangzhou Refining & Chemical Co., expressed great admiration for the effectiveness of intelligent equipment management. The “intelligent brain” he referred to is the three intelligent operation and maintenance systems put into use by the company in 2024: the machine pump monitoring and management system for work teams, the predictive maintenance decision-making system for rotating equipment, and the online monitoring system for pump groups. Since the beginning of this year, the company has utilized these three independently operating systems in conjunction with each other to break down data barriers and enable data interoperability, thereby creating a collaborative working mechanism that allows the \"smart brain\" to function effectively. This approach has enabled the establishment of a three-tiered equipment management protection system comprising \"basic data collection, intelligent trend prediction, and in-depth fault analysis.\" Recently, the preventive maintenance decision-making system for rotating equipment detected an abnormal upward trend in the monitoring indicators for the bearings of the evaporator reflux pump, and recommended maintenance before the alarm threshold was reached. Li Jiaqi detected an abnormal short-term increase in the vibration levels of the pump, and promptly activated the pump cluster monitoring system to perform a spectral \"CT scan\" in order to accurately identify potential faults in the pump shaft. The maintenance team carried out predictive maintenance based on the system’s instructions, and found that the actual location of the fault matched exactly with the location identified by the system’s analysis. “These 3 intelligent operation and maintenance systems are equivalent to providing equipment with a ‘team of general practitioners’; the decision-making system acts as an ‘examination expert’ who can predict signs of problems, the management system functions like an ‘electronic medical record’ that keeps track of the disease progression, while the monitoring system serves as an ‘imaging specialist’ who can accurately locate the affected areas.” ”Li Jiaqi used an analogy to explain it. It is reported that since these three systems have been used in conjunction, the device alarm mechanism has shifted from triggering alerts after incidents occur to providing early warnings based on trends; fault detection has moved from manual inspection to intelligent identification; and the maintenance approach has changed from reactive handling to proactive prevention. Two potential equipment issues have been successfully identified through these systems, thereby supporting the long-term stable operation of the equipment.