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Advantech Actility Rotating Machinery Use Case

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2022 USE CASE LoRaWAN ® AI-based Intelligent Predictive Maintenance IoT Solution for Rotating Machinery SITUATION Many industrial facilities still rely on manual onsite inspections performed on a fixed schedule, that result in reactive maintenance when a problem occurs, or an asset is broken. Maintenance companies experienced challenges during the COVID pandemic, being unable to travel to customer facilities and perform asset health analysis. Service Providers were also prevented to realize their services and offers. The lack of critical asset performance health checks during that time resulted in high downtime costs and exponential slowdown. To implement efficient maintenance processes, a key challenge is to avoid lengthy processes of data connection, pre-processing, model development and inference engine development. SOLUTION Advantech and Actility partnered to offer an integrated Artificial Intelligence (AI) solution that allows Operations teams to perform machine prognostics and health management. Based on Advantech WISE-2410 vibration sensor, a high-performance WISE-6610 LoRaWAN® gateway, Actility ThingPark Enterprise IoT network management platform and Advantech iMachine/PHM application, the solution allows operators to monitor the status of multiple machines in a single dashboard, using real-time and next seven days' machine health index, including ISO 10816 and degradation levels. Smart Industry Global Device Maker CONTACT INFO: Advantech: Actility: BENEFITS The Predictive Maintenance Solution for Rotating Machinery allows operators to analyze data from LoRaWAN® vibration sensors and measure machine and equipment vibration frequencies to detect anomalous behaviour. This helps customers decrease the number of machine shutdowns and work accidents while increasing performance and safety. Users get a very precise machine status prediction, and prediction model retraining that refine the model while repositioning sensors or refining the model performance. The AI solution acts proactively based on the future state of the machine, instead of relying on routine inspections, thus preventing faults in advance. The fine-tuned pre-trained model allows users to gain inference results within two weeks of sensor installation. The LoRaWAN® AI-based Predictive Maintenance Solution ensures longer lifespan of equipment, lower spare parts inventory, and more cost-effective than run-to-failure or planned maintenance. It is available on Actility IoT marketplace ThingPark Market under 'Trial Kit form'.

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