In the world of the Industrial Internet of Things, or IIoT, we talk about the impact enterprises can derive from combining their Information Technology (IT) with their Operational Technology (OT). There’s an obvious linear relationship between effective operations and essential equipment that drives assets such as factories, oil platforms, wind farms, and even supertankers. Imagine the insights that could be brought to life by bringing the latest in data analytics to bear on the masses of data that your assets produce. However, how can you access your data in rugged, remote or disconnected locations?
In a recent survey by PwC, 22nd Annual Global CEO Survey, the top focus area for driving revenue growth was through Operational Efficiency. In other words, reduce operational overheads to increase margins.
One area where the operation efficiency and IIoT worlds meet is equipment monitoring, maintenance, and efficacy.
- How do you identify when equipment starts to fail?
- Is the equipment running within its most effective operative parameters?
- Is the maintenance service running optimally?
Greater insights into these areas can reap massive benefits in cost reduction and operations uptime.
IIoT and data analytics is only effective if you have OT data
Often we hear customers say this is all great news, but they have no way to acquire data that’s produced by their assets which are effectively “divorced” from the corporation. Even if equipment and assets have sensors connected, for example simple vibration sensors on a generator, it’s often the case this data isn’t collected and forwarded (“streamed”) anywhere they can realize its value.
Enter Edge Computing
As the IT and OT worlds meet, there’s a growing necessity for solutions which can:
- Gather or concentrate data from equipment, even on remote assets.
- Make sense of data and compute insights before the data leave the field, plant, site or even vessel.
- Ensure that only required data are streamed to a central location.
- Make the best use of available communications stack i.e. only send priority data over more expensive links.
- Make insights and analysis available to those on the asset who would immediately benefit, i.e. equipment anomalies.
This is where the IIoT loop gets closed by Edge Computing technologies. Edge is a combination of hardware and software designed to complete the final part of the IIoT puzzle.
Easier than it sounds
Industrial hardware manufacturers, such as Dell, have developed ruggedized Edge gateway computers certified for the most hostile conditions. These are industrial grade, mountable PCs with the ability to interface to the sensor data at one end and provide store and forward capabilities at the other.
Software agents are available to bring this IIoT hardware to life by local data analysis and securely sending the data to a central data repository.
Now we have a simple, industrial solution to getting the operational data back to your central operations. Here’s where the latest in data science and machine learning come to bear. Modern data science techniques can be used to provide immense insight into operations of remote assets. This is how we can provide improvements to initiatives such as operational efficiency, equipment failure, maintenance routines, and uptime. We can even get these insights into the hands of those responsible in a timely and intuitive manner, also those at the asset itself.
Edge computing is the last link in the ecosystem of technologies required to really bring the Industrial Internet to life. Until now, the Edge was the last bastion of truly siloed data, worsened by the fact that it was additionally an inaccessible source of operational data.
Now that this data can be accessed in a secure manner at scale, we can really begin to help business operations through modern IT techniques.