Smart factories typically employ a variety of technologies and methods for equipment fault monitoring and maintenance, such as sensor monitoring, machine learning, remote monitoring, and automated repair. Sensors can monitor the status and performance of equipment in real time, promptly detecting anomalies for timely repairs. Machine learning algorithms can predict potential faults in advance, optimizing maintenance schedules. Remote monitoring technology enables real-time tracking of equipment operations, allowing for quick detection and resolution of issues. Automated repair technology utilizes robots or automated tools to perform equipment inspections and maintenance, thereby improving efficiency. By integrating these technologies, smart factories achieve comprehensive monitoring and maintenance of equipment, ensuring normal operation and enhanced production efficiency.

The TPM system of Alps System Integration (Dalian) Co., Ltd. leverages the TS series of equipment status data collectors to capture real-time production equipment status data. The backend system automatically performs equipment fault prediction and correlation analysis, generating intelligent maintenance work orders to reduce unplanned downtime and lower equipment failure rates. The TPM system fully digitizes maintenance activities in smart factories, enabling efficient digital linkages across equipment repair, maintenance, inspections, upkeep, spare parts management, and personnel evaluation, thereby improving maintenance management and execution efficiency while reducing costs.

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