According to recent research, nearly three-quarters of European industrial companies (72%) will increase their Industrial Internet of Things (IIoT) investment over the coming three years. And for good reason, more than four in five (86%) of them believe it will deliver a Return on Investment (ROI) within 36 months.
The promise of IIoT, and the fact that the innovation involved reaches nearly every industrial operation in Europe, makes it the pre-eminent issue of our era. I expect that the degree to which manufacturers in the UK evolve into IIoT enabled enterprises will define our generation in industry.
What is less clear to many manufacturers as they venture into the (relatively) unknown, is what the IIoT really means for them in practical way.
IIoT has the potential to affect every aspect of every type of manufacturing. It has the power to change and enable processes from raw materials and the supply chain all the way through to the final product, and sometimes even on into a deeper relationship with the product’s use and direct consumer engagement.
It can be hard to get your head around going from where we are, to where we can be. But before we think too much about personalised production, serialisation (outside of pharmaceutical manufacturing), batches of one, or deep direct-to-consumer relationships, those of us who are championing the so-called Fourth Industrial Revolution, need to be aware that for most people directly involved in manufacture, the first thing on their mind is keeping production running today.
That said, to remain competitive and to benefit from the opportunity presented by IIoT, evolve we must!
The most important thing for all manufacturers right now is to have an understanding of a few core principles of IIoT that can be used to check that new procedural or asset adoptions will fit into the IIoT future. To that extent, the single most important understanding is that data is the life-blood of IIoT.
IIoT, in its shortest definition, is the leverage of the almost endless opportunities of data analysis.
Data is now being produced everywhere in the manufacturing process. At the device level, at the machine level, at the line level, at the plant level, at the organisation level. For most manufacturers, the first steps towards IIoT are to make better use of existing data. Naturally, where there is data and the need to manage, process, analyse and leverage it, there must be computers.
Computing that data can happen at various levels and in various ways, and this is the first point at which strategic decisions need to be taken.
What is ‘right’ for one manufacturer may not be right for another. The first line of computation is available at “the edge” – loosely defined as the place from which the data is collected – the machine, device or line level.
The next available place for computation is in the on-site data centre. The data centre might bring together feeds of data from around the factory into a central location on site. The third place for computation is in the cloud – off-site data centres.
But, what is the best approach?
The truth is that there will be a mixture of approaches – and that within the same facility, a mixture of approaches may be necessary.
The cloud offers huge computing power for extensive analysis – but do you need to send all of your data there? An onsite data centre at a plant level can offer the opportunity to spot trends and measure them against other business data from a single place – but is that where the data best serves the engineers running the machines? And what if it burned down!?
And the edge – data closest to the point of collection – that can be good for local management of machines or lines but do they run in isolation? Can this data at the edge be aligned with either the plant level or the cloud level to leverage the contextualised data needed for better business decisions?
And then there is security. What could you keep on the machines to reduce exposure? What can you ‘safely’ share with the cloud over a secure connection? These are decisions the relevant to manufacturers right now. Decisions that will help shape the IIoT strategy of the business.
In putting computing power into the heart of every manufacturing operation, it’s important to understand that the digital aspect of the plant then becomes critical to its uptime – back to that first priority of any manufacturer – keeping the production running.
In the IIoT world, if the computer goes down, the plant will almost always stop. If you can’t collect the data, then your figures won’t be accurate, you won’t know the status of machines – the plant may not even be safe. Since uptime is the primary concern of nearly all operational engineers, this reliance on IT systems won’t come easy – but it is an imperative.
Bringing IT to the levels of redundancy needed, while remaining dedicated to performing the tasks required in the industrial setting is vital. Always-On servers and software solutions can help to deliver this, while also helping to manage data on the edge, or on a hybrid of edge and data-room, or edge and cloud options, depending on the data being handled and the need to analyse it in context. The point here, is that there’s no ‘one-size-fits-all’ approach.
Getting together an implementation team with boardroom level representation and input from IT, OT, management and HR is the best practice for an effective IIoT strategy. IIoT affects the whole of the business, so strategising the needs, skills and ramifications for undergoing the change-management process required is vital – however quickly the changes to IIoT are being implemented.
In most cases, the expertise for digitisation won’t all be on-site. But as IIoT implementation spreads through the whole industrial sector, the skills for implementing it are also developing. Systems integrators, vendors and even trade associations will have expertise – it’s worth using it.
Whatever the implementation strategy, we know that IIoT is not If but when. We know that it’s about data, and we know that controlling, managing and analysing that data is what will give the early benefits to reducing cost, the extended benefits of competitive advantage and new business streams, and the future advantages of much deeper improvements in all of these things.