Real-time anomaly detection through collaboration between IoT sensors and AI
Posted: Wed Feb 19, 2025 3:33 am
The collaboration between IoT sensors and AI is an innovative method to dramatically improve productivity in the manufacturing industry. A system that processes data sent from temperature sensors in real time and uses AI to immediately detect abnormalities will significantly improve the accuracy of quality control. For example, a system that uses Amazon's services constantly monitors temperature data and immediately sends a notification if the temperature exceeds a threshold. This makes it possible to quickly and accurately grasp even minute abnormalities that would have been easily overlooked by conventional visual inspections. In addition,
the system is highly flexible and can be used in a variety of business malaysia whatsapp number data scenarios. Parameters other than temperature can also be monitored, and advanced anomaly detection that combines multiple factors can be achieved. For more advanced anomaly detection, methods such as random cut forest (RCF), which is suitable for time series data, are also used.
This fusion of AI and IoT will accelerate the smart factoryization of the manufacturing industry and will be the key to breaking through the limits of productivity.
3-3. Examples of cost reduction and improved operation rate through the introduction of predictive maintenance AI
Analog Devices' Smart Motor Sensor (SMS) is an innovative solution that utilizes predictive maintenance AI. This system automatically starts monitoring by simply attaching it to the motor, uploading data to the cloud every 20 minutes, and the AI diagnoses it. It has been estimated that companies that have adopted the system have been able to reduce their annual equipment maintenance costs by approximately 30%.
The unique feature of the SMS is that it can detect signs of abnormalities, identify the cause of failures, and propose countermeasures without the need for specialized knowledge. This prevents unplanned stoppages, improves operation rates, and reduces maintenance costs at the same time. It can also be linked to SCADA, contributing to the efficiency of the entire manufacturing site.
the system is highly flexible and can be used in a variety of business malaysia whatsapp number data scenarios. Parameters other than temperature can also be monitored, and advanced anomaly detection that combines multiple factors can be achieved. For more advanced anomaly detection, methods such as random cut forest (RCF), which is suitable for time series data, are also used.
This fusion of AI and IoT will accelerate the smart factoryization of the manufacturing industry and will be the key to breaking through the limits of productivity.
3-3. Examples of cost reduction and improved operation rate through the introduction of predictive maintenance AI
Analog Devices' Smart Motor Sensor (SMS) is an innovative solution that utilizes predictive maintenance AI. This system automatically starts monitoring by simply attaching it to the motor, uploading data to the cloud every 20 minutes, and the AI diagnoses it. It has been estimated that companies that have adopted the system have been able to reduce their annual equipment maintenance costs by approximately 30%.
The unique feature of the SMS is that it can detect signs of abnormalities, identify the cause of failures, and propose countermeasures without the need for specialized knowledge. This prevents unplanned stoppages, improves operation rates, and reduces maintenance costs at the same time. It can also be linked to SCADA, contributing to the efficiency of the entire manufacturing site.