Manufacturing gurus often refer to Industry 4.0. At its heart is the Industrial Internet of Things, where condition monitoring happens in real time and engineers use digital technologies to improve plant performance and avoid breakdowns.
How much production can you afford to lose this month? It’s not a question any maintenance engineer wants to ask. But even if the answer is close to zero, how can you be sure your assets won’t fail?
It’s to answer questions like these that growing numbers of manufacturers are turning to a network of sensors and other devices, to connect their machines and harvest data about how they are operating. This is known as the Industrial Internet of Things (IIoT), and it is a crucial component of Industry 4.0.
Ian Clarke, CEO of consultants Velocumen, who advises manufacturers on automation, says: “Industry 4.0 is more than just plugging a sensor on your rotating bearing and monitoring it in the cloud. It’s about being able to take that data and using it to influence what you’re doing across the factory as part of a holistic solution.”
Using web-connected devices to monitor your assets’ performance is an essential first step to creating a smart factory – PwC calls IIoT “the digital backbone” of manufacturing transformation.
Building a smart factory
Going digital need not mean buying all new machinery, says Clarke. “The vast majority of machines in factories are old – in many cases they’re over 40 years old. But you don’t need to go out and buy all new kit to start your digital journey,” he adds.
For example, condition monitoring devices, can be added to almost any machine, however old, he says. These devices can, among other things, detect excessive vibration. Coupled with oil analysis, this type of monitoring gives early warning of failure.
Many machines have Programmable Logic Controllers (PLCs) - industrial computers that control the asset’s operation. A PLC’s primary function is to ensure an industrial system performs a required function, usually in combination with a range of sensors and actuators.
Bringing all the data from PLCs and condition monitoring devices together creates a comprehensive picture of how the whole factory is working. This ‘smart factory’ approach is the essence of Industry 4.0.
Smart factory data allows you to undertake maintenance based on the actual performance of a machine rather than a more traditional time or utilisation-based approach. It also allows you to optimise your processes to make them leaner and more efficient.
Accessing the data
Of course, you need access to the data that a machine generates and it’s important to work with original equipment manufacturers (OEMs) to ensure you can connect their machine to your Industry 4.0 system.
Manufacturing Technology Centre (MTC), in Coventry, has set out to help UK PLC overcome the barriers and challenges of adopting IIoT and Industry 4.0. They’ve built several use cases to demonstrate a smart factory.
“We’re trying to demonstrate what we call the art of the possible – that’s what we’re about,” says Naim Kapadia, Electronics Technology Manager at MTC. “We are trying to demonstrate it in a factory so that people can see it and say, ‘This could be possible for us to do’.”
“Think big, start small and scale fast.”Naim Kapadia, Electronics Technology Manager, Manufacturing Technology Centre
Digital technology will make your businesses more competitive, but Kapadia says you need to take a gradual approach: “Think big, start small and scale fast. Trying to tackle too much, too soon will slow you down and make it harder to implement,” he says.
“My recommendation is start with a specific use case, stay focused on the why and continue to apply the lessons learned. It’s a key starting point to justify investment so you’re not asking for millions of pounds to start the ball rolling,” he adds.
If your firm hasn’t started yet, you are by no means alone. A global survey by PwC at the end of 2021 found that two-thirds of manufacturers are still at the start of their digital journey. Only 3% of the firms surveyed said they had a fully digital factory.
It’s a picture Ian Clarke recognises. “In almost every business I visit, not all of the machines are connected into a site-wide digital strategy,” he says. “Many companies struggle to create a sensible strategy for how they’re going to find out what is going on in those machines.
“In the very biggest companies, of course, it’s happening. But the vast majority of British manufacturing and process industries fall into the category of SMEs and they’re totally under-connected when it comes to a site-wide digital strategy.
“I see them every week. They might have spent half a million pounds on a machine but if they want to find out what’s going on with it, they have to walk up to it or speak to the machine operator who gives them a piece of paper with the batch records.”
A game changer for maintenance engineers
PwC’s survey acknowledges that going digital is a major challenge for companies of all sizes, because it will involve looking again at your organisation, the skills of your people - to say nothing of obtaining investment in the project.
Gary Harvey, Head of Field Services at RS UK & Ireland, says many smaller companies struggle to go digital. “They haven’t really got a plan to move them from where they are now to where they’d like to be, which is usually, to be in more control than they are today,” he says.
“Condition monitoring is as simple as giving you an extra piece of information. You can then use that information to help make a decision about when you do maintenance at a time convenient to you.”
“We can now gather huge volumes of data that can often directly or indirectly infer the condition of industrial machines. And that’s a real game changer.”Dr Moray Kidd, Maintenance Engineering Academic
Dr Moray Kidd, Maintenance Engineering Academic, sums up the benefits. “We can now gather huge volumes of data that can often directly or indirectly infer the condition of industrial machines. And that’s a real game changer.” he says.
But it’s what you do with the data that counts, he adds.
“Some companies are sat back gathering large volumes of data, even using machine learning. But they’re not acting on that data and they won’t see a difference in operational performance.”
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