Large scale manufacturing units, especially industrial setups have complicated equipment. The equipment is expensive, any device failure can lead to cost to the company. Can this cost be reduced?
The world is leaning toward the Industrial 4.0 transformation, and so are the manufacturers. The manufacturers are moving towards providing services rather than selling one-off products. Edge computing in manufacturing is used to collect data, manage the data and run the analytics. It becomes essential to monitor assets, check for any faults, and predict any issues with the devices. Real-time data analysis of assets detects faults so we can carry out maintenance before failure of the system occurs. We can recognize all the faulty problems with the equipment.
Why Edge Computing?
Edge computing is used to collect data and then label it, further manage the data, and run the system's analytics. Then, we can send alerts to the end enterprise customer and the OEM to notify when maintenance service is required. Using network edge helps eliminate the pain of collecting data from many disparate systems or machines.
The device located close to the plants or at the edge of the network provides Condition-Based Monitoring, preempt early detection and correction of designs, ensuring greater productivity to the plant.
Key challenges and Drivers
- Device Compatible
- Flexibility in service
- Light device support
- Extractive Industries
To detect machinery failures, the equipment has a layer of sensors. These sensors pick up the information from the devices and pass information to a central processing unit.
Here, edge computing plays a crucial part in collecting and monitoring via sensors. The data from the sensors help the OEM and the system administrators to monitor the exact device conditions reducing the load on the end device itself. This way, administrators can monitor multiple sensors together. With the generation of the events, failure on one device can be collated with another device.
Edge also allows the processing regardless of where the end device is located or if the asset moves. The same application can be extended to other locations. Alternatively, using an edge helps remove the pain of collecting data from many disparate systems/machines in terms of battery.
The edge computing system based on conditions is used to collect statistics, manage the data, and run the analytics without any software hindrance. A system administrator can relax as real-time data analysis detects faults to carry out maintenance before any failure occurs.
Conditioned based monitoring can be used in Engineering and Construction to monitor the equipment. Administrators can use edge computing industrial manufacturing for alerts and analytics.
On-Prem versus Network Edge
Given that the on-prem edge is lightweight, it's easy to place anywhere on the location. On the other hand, installing a device is overridden if the manufacturing unit decides to go with the network edge; hence, the flexibility is automatically achieved.
How does Nife Help?
Use Nife as a network edge device to compute and deploy applications close to the Industries.
Nife works on collecting sensor information, collating and providing immediate response time.
Benefits and Results
- No difference in application performance (70% improvement from Cloud)
- Reduce the overall price of the Robots (40% Cost Reduction)
- Manage and Monitor all applications in a single pane of glass.
- Seamlessly deploy and manage navigation functionality (5 min to deploy, 3 min to scale)
Edge computing is an asset to different industries, especially device manufacturers, helping them reduce cost, improve productivity, and ensure that administrators can predict device failures.
You might like to read through this interesting topic of Edge Gaming - https://blogs.nife.io/edge-gaming-will-give-the-virtual-gamers-a-real-time-player-feel/