If you aren’t talking about the Industrial Internet of Things, you just aren’t cool these days. Most people I talk to struggle to really define the IIOT, and it wasn’t until a couple of days ago that I realized why. For those of us in the automation world, we have been connecting lots of individual data points to the internet for quite a long time now. So while it may be novel to connect your refrigerator or smoke detector to the internet, industrial equipment has been there for years.
So what’s the big deal with the IIOT, and if you’re reading this, why should you care? Most plant operations personnel already have more data on their SCADA systems then they can reasonably pay attention to at any given time. Is more information better, or is it just going to add confusion?
The answer to these questions is pretty complicated if you get down in the weeds, but the big picture answer is fairly simple: Efficiency. IIOT will make your operation run more efficiently than ever previously possible, and it will do that through analytic tools that will notice opportunities for operational improvement humans just aren’t capable of. How, you ask with amazement, is this possible?
IIOT, Blind Men, and Elephants
Remember the old story about the group of blind men meeting an elephant for the first time? One felt a leg and insisted that an elephant is like a tree. One felt the trunk and thought an elephant is very like a snake. Others felt the ears, tail, and flank and all came to equally understandable, but incorrect conclusions. The moral of the story, of course, is that you can come to very wrong conclusions when operating without all the facts.
In manufacturing business today we have a very similar situation. Operations thinks a manufacturing business is a control loop needing to be optimized. Maintenance thinks the business is an asset to be maintained and managed. CFOs think the business is a set of financial statements. Managers, HR, and other executives and departments all have their own perspective, but all operate from an incomplete and often grossly out of date set of data.
So the point of IIOT is two-fold. First, it’s to bring all the data from the manufacturing business into one place, and then second, it’s to make sense out of that data in each context in which it is viewed. Back to the blind men and the elephant, it would be the equivalent of backing all the blind men away ten feet and suddenly giving them sight. Then in addition to site, it would be giving them the Wikipedia article on elephants, the individual history of that particular elephant, a complete guide to its care and feeding, and direct, specific advice on how to optimize that elephant’s existence. They would not only all be operating from the same information set, they would all come to the same optimal conclusions regarding the elephant.
In a manufacturing setting, this would mean collecting real-time data from the plant floor control systems, climate control, fire and alarm systems, inventory, HR, rates from the power company, order forecasts from sales, cash positions, up-stream supply chain, and whatever else you can imagine. Then with powerful analytics systems, everyone in the organization can work together to make the business more efficient and streamlined than anyone thought possible.
What can I do to take advantage of this?
Build network infrastructure. Since the focus is now data collection, not just machine or loop control, we’ll connect more and more sensors just for the information they provide. Those sensors will probably be connected via Ethernet, and they will probably not go through a PLC or DCS. They will connect directly to the historian. You will need secure, high bandwidth network infrastructure everywhere in your facilities.
Invest in analytic tools. High-end Big Data Analytics tools are beginning to distill into the operations world. Some large automation suppliers already have these tools in place, and they will continue to improve with real-world experience. Newer/smaller automation suppliers have more.
Embrace Change. You’ll have to accept sometimes odd-sounding or counter-intuitive advice produced by analysis tools to improve operations. If you’re willing to make that leap, however, you’ll see efficiency improvements that you did not think were possible.