This is not a definitive guide; this is not an exact science. But the logic is plain – to present a sensible way to think about devising an Industry 4.0 system that hits the mark. Because, when novel technology is brought to market by excitable marketing and desperate sales, enterprises can find they are sold a dream of digital change only to buy a nightmare of technological complexity, and of useless gadgetry and wasted effort. Which plays with the mind, screws with the picture, messes with the market – and makes the urgent drive to build a sustainable economy that bit harder.
Which no one wants. The best advice is to be deliberate about the whole Industry 4.0 scheme. Enterprises should plan carefully, and execute clearly, and measure at every turn. They should be narrow with their immediate focus and expansive with their grand vision; and they should be flexible, brave, opportunistic – to join the dots between. The below bullets do not present a definitive digital architecture. How could they? They present certain big tech elements, and leave the rest for the appointed system integrator; mostly, they just present a way to think about Industry 4.0.
Because it’s not an exact science, but it’s not rocket science, either. It’s Five Easy Pieces, like in the movie – a book of music that piano students should master before tackling more complex compositions. And like the movie, kind of, at a stretch, it’s about a cultured drifter in a blue-collar shirt trying to make sense of the world, and ready to ask stupid questions of stupid suppliers. Or something-like. What do you mean you don’t make side orders of toast?
1 | AN ORIGINAL PROBLEM AND AN ULTIMATE VISION
If it’s not broke, don’t fix it. But of course, everything is broken – insofar as everything could be better. The trick, at the outset, is to identify a problem or a set of problems that might be solved with good data insights – plus some new digital wizardry, perhaps. Are environmental targets tough? Are operations inefficient? Are margins tight? Are wages high? What is the problem, and where is it? Where improvements can be made, and how – just by monitoring and adjusting equipment and processes, or by introducing brand new machinery and systems?
This sharp focus must be placed in a wider context. What’s the big idea? What does the business look like in five years? How has it changed? How might new digital tech reimagine its operations and processes – and ultimately its products and services, as well? This future-gazing might come first, or be well-defined; it depends how urgent the original problem is, and how forward-thinking or deep-in-the-mire the management team is. But clearly, what starts in splendid isolation must sooner or later be integrated and expanded – into company-wide digital transformation.
2 | A STARTER APPLICATION AND A BUSINESS CASE
The original problem should eventually precipitate an initial solution, which should be costed and funded. There is some flip-flopping here, because the solution will invariably define the digital apparatus required to deliver it, as described below – which will, in turn, inform the investment case. And these elements will likely be revised or reduced, which means the scope of the starter solution may also change. But this is a fundamental part of the Industry 4.0 design process to bash-out a solution that delivers value, and a proof that can be readily multiplied.
Again, the point is to identify a first problem and design a first solution, and to re-work the process until the two functions tally in a suitable business equation where the investment is bearable and the return is discernible, and also scalable – in terms of productivity or efficiency gains, environmental compliance, security or safety standards, or likely some combination of these. A note, too, about measurement (which might have existed as a sixth bullet in this article, if it didn’t break the number count in the headline): always, value must be tracked and scored to keep the balance.
3 | A CAPABLE NETWORK AND A COMPUTE ENGINE
These are the two big-ticket tech blocks in the digital landscape: the connectivity and computing infrastructure. They are the foundational elements of the Industry 4.0 system. But they each present a mad range of options. The key is to keep the above decisions in mind – about the original problem and the initial solution, and about the ultimate vision and the final goal, and to work out how to prove the initial use case and when to bankroll the whole shebang. Because networks and servers come in all different flavours, in all different places.
Is the system for standalone apps like environmental monitoring? Is it for two-way sensors for on/off machine controls and anomaly alerts? Is it for high-fidelity robots and cameras with edge analytics? How much rides on the connection – vis-a-vis business blackouts, production losses, safety risks? Is the public cloud an option, or does latency and security mean the data stays on site? The answers to these questions will determine whether new-fangled 5G or patched-up Wi-Fi suits, or if some LoRa/BLE/RFID combo will cut it, as well as where the compute engine resides.
4 | A SENSOR SYSTEM AND A DATA PLATFORM
Similarly, and of course, the IoT makeup will be governed by the starter solution, and informed by the scope of the final project. What sensors are required? Are they to be strung-up on a separate network for people counting, security access, virus detection? Are they to be retrofitted to ancient machinery to monitor levels and flows, or wear and tear? Are they to be introduced in brand new equipment, such as autonomous guided vehicles and mobile robots (AGVs and AMRs), or integrated otherwise into factory lines on real-time production schedules?
And once the sensor network is pulling live data from the operating environment, where does it go, what does it do, and how is it rendered? You need an IoT platform, which ingests data from an analytics system in a compute engine in the cloud, and from another one that lives on-site at the enterprise ‘edge’. And this IoT platform, via its upstream repositories, should be able to draw data across any requisite IT/OT protocol, and render it on-time in a usable dashboard – which brings total visibility and control to staff on the shopfloor.
5 | A COLLABORATIVE PARTNER AND AN ITERATIVE LOGIC
As mentioned towards the top, Industry 4.0 is an iterative process – across all the design, build, scale, and run phases. And it takes a village, as the cliche goes; it is a speculative pursuit, and a team sport, and a long game. Whichever supplier is selected to ‘prime’ the project should be comfortable (!!!) to recognise its own strengths and weaknesses, and confident to bring in the correct partners alongside – and not just old mates from old jobs, but specialists that will bring new value every time.
Is this the most important part of it? No, the problem solving at the start is the most important bit; but collaborative co-creation is the common thread in everything, from diagnosis to treatment to rehabilitation. It is probably worth asking, as you sit across the table from a series of big-talking Industry 4.0 suppliers, whether you can see in their eyes and know in their souls that they are sympathetic to your situation and your industry, and that they know how to pull together a team to devise a bespoke solution to serve your business.
