IoT offers enterprises invaluable information about their assets. In this blog, we explore how the latest IFS Cloud technology not only reports and resolves issues, but also maintains the lifecycle of expensive equipment.
Optimize your routine maintenance with the power of IFS Cloud.
Here are the five ways IFS Cloud supports end-to-end reporting, repair, and maintenance of IoT devices. In this case, we look at an example from the energy sector, using connected wind turbines.
IFS Cloud technology enables platform users to have a birds-eye view of all connected devices, alongside a deep dive into individual assets. Using digital twins, users can check device’s health status, including (in this case) altitude, temperature, vibration, and power.
Green, amber, and red indicators give a clear direction of your device’s current status. However, when an incident occurs, a more in-depth analysis needs to be undertaken. By looking at an individual asset, we can see exactly what caused disruption and respond accordingly.
Once we know more about the incident, and the system has automatically allocated an error code, we use the same powerful IFS Cloud platform to place a work order and assign a technician. The transparency of IFS gives the technician vital information. It saves time, for example, by ensuring technicians bring any tools they may need to resolve the issue. The system can also detect if a technician is the most correctly qualified for this incident. Or, in urgent situations, it can assign the closest technician available.
Once the technician arrives on the scene, this doesn’t always mean the issue can be resolved. In many cases, they will require outside expertise and support in the form of a remote assistance. Using AR (augmented reality), the remote assistant can guide the technician with complete visibility.
Once the issue the resolved, the IFS Cloud dashboard will automatically update the digital twin status.
While dealing with incidents is an important part of asset management, IFS Cloud technology is primed to support predictive management. Using real-time data, the system can analyze the best times to implement an upgrade while minimizing downtime. And it’s not only the device itself that can be monitored. Optimization requires tying many data sources together such as asset criticality, service levels, spare part supply, weather conditions and more.
This ongoing data collection can then be used further, to support the development of new infrastructure that is even more reliable.
