Look for the common patterns
No matter what the industry might be, there are patterns that are common to all, and one of those patterns is that there will be islands of activity, bridged by workflows. In many cases those workflows will be manual, or at best semi-automated. However, as we seek to make industry more adaptive, responsive and efficient, that will have to change.
Industry’s response is – or should be – a digital transformation similar to that underway in business. This takes advantage of digital enablement, via the widespread use of connected sensors and controllers (the so-called Industrial Internet of Things, or IIoT) and near-ubiquitous connectivity to transform business models, organizational cultures and working patterns.
That in turn means adding intelligence at the network’s industrial edge. An obvious reason for this is to link the edge back to the core or cloud, where the heavy-duty number crunching takes place that enables the organization to analyze, predict and respond. However, as the IIoT grows, it is also increasingly important to do as much as possible at the intelligent edge in order to minimize latency and cope with lost connections.
The edge of the world
We call it the edge because it is where the digital world meets the physical world. It is where you can collect data on what’s really happening, and where you can use equipment to carry out physical actions. It is not a physical boundary though – it is a virtual or metaphorical edge that defines where the digital world stops and the physical world begins. And once we add the IIoT and the possibility to have sensors almost everywhere, the industrial edge can be even more diffuse than that.
And don’t make the mistake of assuming that when we talk about the industrial edge and the IIoT, we are merely referring to connecting up robots and assembly lines, or machine tools fitted with sensors – there are opportunities for industrial digital transformation in almost any area of industry. What about the trucks that bring supplies and then deliver what the machines have made? They will be fitted with many different sensors too.
Then there’s the electricity generating stations and distribution networks that power the machines – they are extensively instrumented to report their health status. And talking of health status, today’s hospital beds and wards contain plenty of electrical and mechanical equipment, all of which could be feeding back readings and reports for automated analysis.
In fact, outside of a few traditional manual crafts, it is hard to think of an area of human (or robot!) activity where the concept of the industrial edge does not apply. That shouldn’t be surprising, because the broad patterns are the same for all industries. Regardless of what’s at the edge – a machine tool, the GPS tracker on a lorry, a healthcare device – they all send and receive information, and that information all has potential value, especially once it is filtered and/or aggregated for analysis.
Bridging the islands
As I mentioned though, one of those shared patterns is that, whatever your actual industry is, it may have multiple islands of technology and connectivity within it. That nurse-call system by your hospital bed? It’s very likely incompatible with the IP phones and the blood pressure monitors. And those flexible manufacturing systems won’t talk directly to the web sales platform unless they are very state of the art, i.e. new – nor, probably, would you want them to. But there needs to be a route between the two.
We therefore need bridges between those islands – bridges that are secure, obviously, and smart as well, because while the industrial edge and the IIoT give us a sea of data, it can be in many different formats and much of it might also be transitory in nature. That means, for example, that the bridge could usefully filter out the noise, in the shape of those steady-state signals which are only ever relevant when they suddenly indicate an unexpected change.
If that smartness can also minimize latency by performing some of the analysis at the edge, or implementing policy-driven changes without referring back to the center, so much the better. Indeed, the key thing is to do as much as is practical at the edge.
The challenge here is the same for any industry, and it’s that the industrial edge is a lot more diverse than the average office or computer room. If you thought it was awkward getting different PCs and mobile devices talking to the office printers and file servers, you haven’t seen anything yet! At least today all that office hardware and software is designed to use the same type of network, and there are de-facto standards for printer drivers and for network file sharing.
But the common patterns mean that once you have solved this problem for one industrial edge, for example by developing an intelligent edge device, you can apply that to edges in other industries as well. To learn more, check out our recent paper on Industrial Digital Transformation, which looks at the key role of the intelligent edge and can be downloaded here
Bryan is a technology enthusiast and industry veteran. He has been analysing, explaining and writing about IT and business in a highly engaging manner for around three decades. His experience spans the early days of minicomputers and PC technology, through the emergence of cellular data and smart mobile devices, to the latest developments of the software-defined age in which we all live today. Over his career, Bryan has seen at first-hand how IT changes the world – and how the world changes IT – and he brings that extensive insight to his role as an industry analyst.
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