Breakdown to breakthrough: how Bentley is rethinking maintenance for competitive advantage

At Smart Manufacturing Week 2026, The Manufacturer caught up with Bentley Motors’ Head of Maintenance, Jonathan Peedell, to discuss the major issues facing maintenance today from the cost of downtime, reliability and data integration challenges to workforce gaps, legacy systems and infrastructure constraints.

Technology is impacting every area of manufacturing operations, and the maintenance realm is no different. As a business function, maintenance has shifted from a supporting role to a strategic priority in manufacturing.

Unplanned downtime alone costs billions annually and can halt production, disrupt supply chains and erode brand loyalty and competitiveness. To that end there are numerous trends in the space that are helping to redraw the map around what industrial maintenance means in a modern manufacturing setting.

There is an ongoing shift towards predictive and prescriptive maintenance; the rise of AI, advanced analytics and IoT are driving the connected factory; while sustainability and asset longevity are becoming key business performance indicators.

Driving change

Jonathan explained that there are predominantly two driving factors behind maintenance evolution into a strategic business function rather than a reactive support role. These are adaptability and, unsurprisingly, money.

He cited that UK manufacturing is currently in its most cost-conscious period of the last 20 years. The variety of road bumps in that time – from the economic slump of the late 2000s, through to Brexit and COVID, and on to conflict in Ukraine and the Middle East – have meant that we are in an economy of constant flux, where the only certainty is uncertainty.

He commented: “In terms of productivity, no one really knows where they’re going to be, and what investments they’re going to be able to make. That’s intrinsically linked to the profit margins of a business. Crucially, a manufacturer’s facilities are increasingly being looked upon as possible asset generation, and maintenance functions have the ability to capitalise on that and go beyond the function of merely maintaining the technical uptime of an asset.”

Whereas in less frugal times, businesses would think little of purchasing new pieces of equipment, there is now true value to be had in businesses investing in the capability that will enable them to sweat their assets a little more. And, the homegrown experience to be able to do that – which comes from the maintenance function – combined with their ability to push any investments out a little further, is becoming far more prevalent and valuable within manufacturing businesses.

Downtime dilemmas

Unplanned downtime remains one of the biggest operational risks in manufacturing. However, there are some organisations who are still falling short when it comes to reliability and resilience.

Jonathan believes that much of this shortfall is down to the fact that many manufacturers are still only part way through their digital transformation journey. Many businesses have machine learning and/or AI models that can inform when to expect failures or schedule maintenance.

“Right now, not all manufacturers have something conjoined that can go away and actually take action. In some cases you may know that there is something that needs doing, but what we don’t always have is the investment available. We may need to spend money to change the asset or make it future ready and increase its reliability.

“So, at the moment, it’s that end-to-end connection that many manufacturers lack; the knowledge of the problem may be there, but there’s not always a defined route to fixing it.”

Crucially, a manufacturer’s facilities are increasingly being looked upon as possible asset generation, and maintenance functions have the ability to capitalise on that and go beyond the function of merely maintaining the technical uptime of an asset.

As the saying goes, you can’t manage what you can’t measure. There are a lot of devices out there, so look around and see what you can implement yourself. You don’t necessarily need third-parties to come in to install and integrate them. There will be elements that your own maintenance functions can implement very easily. And that will allow you to have a better understanding of how much life you still have within an asset and whether you can continue to sweat it.
Jonathan Peedell, Head of Maintenance, Bentley Motors

Similarly, many manufacturers struggle with disconnected systems due to poor data visibility. This lack of connectivity is currently adding to the labour intensiveness of maintenance functions because ultimately, there is still a reliance on a manual intervention to make something happen.

So, the role of data integration in enabling effective predictive maintenance strategies will become critical in the long-term. And this will be an area where AI will have a definitive role in enabling manufacturers to be more dynamic and increase the capability to join together what are now separate, isolated and individual platforms, systems and pieces of equipment.

AI potential

Like many areas of manufacturing, AI and advanced analytics promise major improvements in maintenance performance. But it’s certainly nothing new for Bentley, as Jonathan explained that the business has been working on and using predictability algorithms for around three years.

“On their own they are strong and very competent examples of where AI has given tangible benefits,” he added. “We have mitigated several quite sizable potential breakdowns using exactly that. In a standard machine learning environment, we would have just been waiting until we hit an upper or lower control limit.

“Now we’ve got a piece of AI that can recognise an anomaly, and can tell us, for example, whether we need to go in and do something over the weekend, or whether we should take action immediately. That’s how AI is working right now, but integrating it into something wider that actually takes action is the next stage.”

Justifying investment

Of course, when budgets are squeezed, it’s hard for manufacturers to justify investment in predictive or prescriptive maintenance. Technology should never be introduced for the sake of it and it’s always important to have a business case that underlines the value.

But as Jonathan explained, as long as manufacturers have that business case in place and understand the problem they’re trying to solve, achieving predictability within maintenance is no longer as daunting and expensive as it once was, and it’s possible to deliver results with a moderate amount of investment.

“It’s only when you start getting into ecosystems, and taking on lots of the other functionality, that the cost begins to ramp up,” he said. “Particularly within maintenance functions, there is typically a reasonably healthy skill set in situ. Within the maintenance section of a business there will be some very curious and interested people, and there will be myriad platforms that they could potentially start using alongside some of the data that you collect.

“Of course, a lot of that data has to go through compliance routes within the businesses, but the data isn’t GDPR-based so it’s not data that’s going to trip you up further down the line. So, my advice would be to go away and have a look at the solutions that are available; they’re not as expensive as you think.”

Beyond the AI

During Smart Manufacturing Week Jonathan took part in a panel discussion around the key trends and themes within the world of manufacturing maintenance. Predictably, AI emerged as a key discussion topic. However, it certainly wasn’t the only subject on the agenda.

Beyond the AI buzz, there were lengthy conversations around the maintenance training journey, and how to get people to stay within maintenance functions. He explained that there’s a general appreciation for the fact that maintenance professionals are sought after assets.

That means they can be hard to retain, and so consequently, the quality of experience they can be given in a role directly correlates to their time in a function, and the time they want to stay with a given business.

“We’ve known for quite some time that we’re heading towards a digital world, with app-based solutions and connected technology,” he continued. “What we have within maintenance is curious people. What we need to do is keep them that way; get them excited to work with technology, and be hands on with AI and digitised solutions. If you can’t offer them those things, they have the ability to find jobs elsewhere.

“But there’s no doubt that if you’re an individual working in a maintenance function, and you have a keen eye and understanding of digitisation, you have a very healthy career ahead of you.”

Another key consideration within the world of manufacturing, and maintenance in particular, is legacy architecture and how organisations modernise maintenance practices without completely replacing existing assets and systems. And in the modern environment, it’s here where maintenance professionals can truly earn their spurs.

Cost complexities are often forcing businesses to stall the replacement of ageing assets, and in some instances, postpone investment in new machinery all together. Therefore, the importance of maintenance functions is made even more apparent as they are the ones who hold the key to being able to sweat existing assets to their full potential.

“If you look around Smart Manufacturing Week, we are surrounded by hundreds of companies that offer haptic sensors, IoT devices and all manner of technology that can be configured and bolted onto old pieces of equipment,” Jonathan added. “We’ve done the same with 35 year old pieces of equipment, and it’s been very successful. In a cost-conscious world it’s the best way to go.

“As the saying goes, you can’t manage what you can’t measure. There are a lot of devices out there, so look around and see what you can implement yourself. You don’t necessarily need third-parties to come in to install and integrate them. There will be elements that your own maintenance functions can implement very easily. And that will allow you to have a better understanding of how much life you still have within an asset and whether you can continue to sweat it.”

Evolution

It’s clear that rip out and replace is simply not an option for most manufacturers, particularly in the current climate. Therefore, asset sustainability and longevity are becoming more important.

As such, maintenance is evolving to support both operational performance and environmental goals, and it’s clear to see why its role is so vital in this regard. Maintenance is very good at looking at equipment through the lens of energy management and optimising it in the most effective and efficient way. “This can sometimes be down to something as simple as the spare parts you stock,” Jonathan continued. “The difference between IE2 or IE4 motor technology, for example, is an indication of how technology always moves on.”

And just because a core asset is of a specific age doesn’t mean that it can’t be cost effectively and sustainably upgraded moving forward. As Jonathan explained further, swapping a complete asset out for a replacement that is, on paper, more energy efficient isn’t necessarily the most sustainable path to take.

“The cost of scrapping an asset and the waste that this could potentially generate, can in itself be counterproductive. So, rather than replacement it’s sometimes advisable to look at an existing asset and see what can be done to make it slightly more efficient; maintenance people are fantastic at doing that.”

Looking ahead, it’s open-mindedness and a holistic approach that will separate manufacturers with world-class maintenance strategies from those that continue to struggle with downtime and inefficiency.

Companies will need to leverage the skill sets they’ve got in order to get a full understanding of their environment and ensure everyone is bought into the mission to keep technical uptime where it needs to be.

And while it’s easy for many businesses to be seduced by the promises and potential of technology and AI in particular, Jonathan explained that over the next five years, success won’t necessarily be centred around who has the best AI solution. Rather, it will hinge on the organisations that have a comprehensive understanding of their environment.