The new solution is based on the Advantech WISE-2410 vibration sensor, the high-performance WISE-6610 LoRaWAN® gateway, Actility’s ThingPark Enterprise IoT network management platform, and the advanced Advantech’s iMachine/PHM application, and is now available under Trial Kit form on Actility’s IoT marketplace: ThingPark Market.
The challenges of performing machines health checks
Maintenance companies have been experiencing increased difficulties in fulfilling their role in recent years. Due to the pandemic, they have been no longer able to travel to customer facilities to perform asset health analysis, and service providers are unable to realize their services and offers. Many are still battling an exponential slowdown due to the global lockdown.
Many manufacturers who rely on these services to maintain the health of process critical assets are helpless and thus face a high of costly downtime during these unprecedented times.
Implementing efficient maintenance processes is crucial to operators of industrial facilities, but it’s not an easy task. One of their greatest wishes is to avoid lengthy processes of data connection, pre-processing, model development, and inference engine development.
In the traditional method, still used by most factory operators, the on-site inspection is done manually, regularly but without stable inspection quality, and only passively reacting and informing the maintenance crew when the problem occurs.
Proactively Keeping Facilities at Productive Status Thanks to IoT
Actility & Advantech found a perfect partnership to join their forces and offer a solution to solve those issues.
Thanks to a great combination of hardware and software expertise, we designed a winning solution to keep our engines healthy and monitor them to prevent any possible mishap: the Predictive Maintenance Solution for Rotating Machinery Solution. Installing LoRaWAN-connected vibration sensors and easy implementation of the infrastructure, allows you to analyze data from sensors measuring vibrations frequencies of machines and equipment in order to detect anomalous behavior, therefore enabling industrial end customers to decrease machines shutdowns and work accidents while increasing performance and safety.
Users get a very precise machine status prediction and prediction model retraining that refines the model while repositioning the sensor or refining the model performance.
Moreover, the most important feature designed ad hoc for the new solution is that it now acts proactively based on the future state of the machine, instead of carrying out routine inspections, preventing machine faults in advance. With the finetuned pre-trained model, users can expect to gain the inference result within two weeks of sensor installation.
Using this solution means joining the Industrial Revolution 4.0, and therefore ensuring a longer lifespan of equipment, lower spare parts inventory, and more cost-effective than run-to-failure or planned maintenance.
Applying the solution in an infinite number of use cases
Thanks to Predictive Maintenance Solution it was possible to overview all types of machines in one-stop, in real-time getting also the machine’s historical and future status. It can be used in petrochemical plants, PCB plants, Semiconductor Manufacturing Plants, and so much more.
One of the most successful use cases is the rotating manufacturing machinery management in steel plants. In this specific industry, the failure of the manufacturing machine will seriously affect the product line, that is the reason why it is extremely important to prevent unexpected breakdowns.