Flir, a Teledyne company, is highlighting a new advancement in automated non‑destructive testing (NDT) through a technical collaboration with edevis GmbH, a leader in active thermography.
 

Flir, a Teledyne company, is highlighting a new advancement in automated non‑destructive testing (NDT) through a technical collaboration with edevis GmbH, a leader in active thermography. Together, the companies demonstrate how the Flir A6450 long‑life cooled MWIR camera integrates seamlessly into automated inspection workflows to detect structural anomalies in real time, enabling manufacturers to identify defects that traditional point‑based methods or standard sensors often miss.

Across industries such as automotive, energy, and advanced manufacturing, hidden flaws like grinding burn, coating delamination, adhesion failures, and subsurface irregularities can compromise product integrity. Conventional inspection techniques typically examine only small areas, leaving critical defects undetected. The Flir–edevis approach introduces a new standard for full‑surface, high‑speed thermal inspection that delivers actionable results within seconds.


At the core of the system is the Flir A6450, engineered for continuous 24/7 operation in demanding industrial environments. Its long‑life cooler, rated for 27,000 hours, and its high‑speed MWIR imaging capabilities allow precise temperature measurement and rapid thermal response capture—key requirements for identifying subsurface defects during active thermography. When paired with edevis’ laser‑based excitation and advanced thermography software, the system reveals structural anomalies that are invisible to the human eye and difficult to detect with conventional sensors.

“Manufacturers are under increasing pressure to automate more of their quality assurance processes while maintaining absolute reliability,” said Mathew Hasty, Global Vertical Director at Flir. “The A6450 is designed for exactly these environments. Combined with edevis’ active thermography, it delivers real‑time insight into structural behavior that helps customers catch defects earlier and keep production moving.”

edevis’ active thermography platforms are widely used for structural inspection of metals, composites, battery components, and precision‑machined parts. By integrating Flir thermal imaging, these systems provide deeper insight into material behavior under thermal excitation and support automated decision‑making directly on the production line. The result is a reliable, contactless, and repeatable inspection process that scales to modern manufacturing throughput.


“Our mission is to make high‑precision NDT fully automated, fast, and easy to integrate,” said Alexander Dillenz Managing Director at edevis GmbH. “Flir’s A6450 gives us the thermal performance and long‑term stability required for continuous industrial use. Together, we’re enabling manufacturers to detect defects that would otherwise remain hidden and to do so at the speed their production lines demand.”

As industries accelerate their adoption of automated inspection technologies, the combination of Flir thermal imaging and edevis active thermography offers a scalable, future‑ready solution. Whether applied to brake discs, composite structures, battery cells, or semiconductor components, the integrated workflow provides manufacturers with a powerful tool to ensure product integrity and reduce scrap.

www.flir.com

 

Traditional utility thermal inspections have a major bottleneck: manual interpretation. It’s slow, subjective, and risks critical issues slipping through the cracks.

On Thursday, June 25th at 15:30, FLIR and Prasanna Technologies are hosting a compact, 30-minute webinar to show you how to automate the entire process.

By pairing FLIR’s iXX-Series thermal cameras with Styra (an AI-powered analytics platform), we are giving utilities a "single pane of glass" view across their entire asset network.

[Live Webinar] AI-Driven Asset Intelligence for Reliability

• Date: Thursday, June 25, 2026
• Time: 15:30 – 16:00 (30 mins)
• Cost: Complimentary
• Registration Link: Secure Your Virtual Seat Here

What you’ll learn in 30 minutes:

• AI Anomaly Scoring: Automatically detect and score thermal faults by severity.
• Dynamic Asset Health Index: Get a live, continuous health metric for your infrastructure.
• Map-Based Dashboards: See your entire network—substations to transmission lines—in one view.
• Automated Reporting: Eliminate manual paperwork with audit-ready reports generated in seconds.

If you are ready to eliminate false positives and transition to a truly predictive maintenance strategy, this quick session is built for you.

Can't make it live? Register anyway and we will email you the recording.

[Click Here to Register Now]

Dura Pump, the fluid control specialists, have solved a major problem for a leading social housing provider in the Midlands, where a site’s wastewater system was frequently blocking and flooding.

The original pump system, which had been under-specified for the level of occupancy on the development, was increasingly unable to cope with demand. In addition to flooding and tripping, the all too frequent blockages caused by rag debris had resulted in costly emergency tanker callouts.

To handle the demanding conditions for the housing provider (who manage over 10,000 homes), the Dura Pump-led project saw its engineers introduce a new unit with an extended knife system that could properly handle the solids in the wastewater by continuously reducing particle sizes, as John Calder, Technical Director, explains:

“Combatting solids, rags, wet-wipes and the like are a common problem in today’s world of wastewater management. We’ve seen time and time again that standard pumps gradually become overwhelmed, leading to very frustrating issues in the housing sector.”

He added: “Since we installed a 2.2kW Landia Submersible Chopper Pump, there has been a dramatic improvement in performance, with no callouts required. The housing provider has drastically reduced its maintenance costs, and importantly now provides a sound, reliable wastewater service for its residents.”

www.durapump.co.uk

www.landia.co.uk

 

 

 

 

 

 

 

Compressed air is a robust system that’s vital to manufacturing, but it’s also its most complex challenge. Navigating the delicate balance between system optimization and operational risk is what separates standard maintenance from true facility leadership.

In this EXAIR webinar to be held June 25th at 11:00 am, featuring Direktin, we identify the three most common technical failures that compromise system efficiency and inflate operating costs. Through live demonstrations and software modeling, we will break down the following:

1. Homemade vs Engineered Solutions: We’re running a head-to-head test between a standard drilled pipe and an EXAIR Super Air Knife. We’ll test them both with calibrated equipment and then plug those numbers into the Direktin calculator to show how easily you can calculate savings on-the-fly.

2. Loud ≠ Performance: Many operators mistakenly equate high decibel levels with high force. We demonstrate an open pipe vs. an engineered nozzle to prove that noise is a symptom of turbulence and waste, not performance.

3. Plumbing and Pressure Drop Failures: If your plumbing is wrong, your performance is gone. We’ll use EasyCAS software to model a botched installation and show how a lack of predictive setup leads to massive pressure drops and poor performance.

Stop guessing with your pneumatic setup. We’re going to show you how to audit your own processes, using the right tools, to ensure you get the maximum force-to-flow ratio out of your compressed air infrastructure. Register now for this live webinar. https://exair.co/190-swebpr

By Stefan van Bussel, Teamlead Technical Services, and Jeroen Wijnen, Maintenance & Installations Leader, Berkvens Doorsystems

Every morning in a manufacturing facility, before a single machine is switched on, a maintenance team lead is already working. Reviewing overnight breakdowns, scanning shift logs, checking notifications, building a picture of what the machine park looks like before the day begins. Here at Berkvens Doorsystems, that process used to take between 30 minutes and an hour. Every day. Per team lead.

Team leads now no longer need to spend this time; it is recovered by artificial intelligence (AI).

A manufacturer with nearly a century of tradition

Berkvens Doorsystems is a family-run manufacturer headquartered in Someren, Netherlands, and part of Xidoor. With three production facilities and five brands, we produce interior doors, frames, and sliding door systems for the housing, healthcare, hospitality, and education markets across Western Europe. Manufacturing at this scale demands disciplined asset management - diverse equipment across multiple production environments, high standards for uptime, and a technical team responsible for keeping it all running.

Like many manufacturers, we have made a foundational investment in an enterprise asset management (EAM) platform to bring structure to maintenance planning, work order management, and equipment tracking. EAM gave the technical department visibility it had previously lacked. But visibility only goes so far when the volume of data such as notifications, shift logs, work histories, and equipment records, keeps growing. At some point, reviewing all of it manually becomes the constraint. That is the problem AI is now solving.

The business case has never been clearer

Our experience sits within a broader industry shift that is accelerating. According to Ultimo's Maintenance Trend Report, 63 percent of manufacturing organizations are struggling with an aging workforce - a challenge that is as much about knowledge as it is about headcount. The diagnostic expertise accumulated over decades of hands-on maintenance work does not transfer automatically to the next generation. When experienced technicians retire, they often take with them an understanding of how specific equipment behaves that exists nowhere in any system.

AI in the form of digital workers is changing that equation. By learning from operational data over time, it can surface patterns and institutional knowledge that would otherwise be invisible or lost. For manufacturers already running an EAM platform, that intelligence is embedded in data they are already collecting. It simply needs the right tools to unlock it.

A digital worker is an AI system embedded in operational workflows that can independently monitor data, initiate actions, and complete multi-step tasks - handling the routine cognitive work that would otherwise fall to a person

What changed at Berkvens Doorsystems - and how quickly

We adopted Ultimo's digital workers as one of the Company’s earliest users. The starting point was practical: digital workers that analyze the data the team was already generating, delivered through the EAM system already in daily use. No new platform. No disruptive implementation. Intelligence added to the workflow already in place.

The morning review process was transformed almost immediately. Where our team leads had previously spent up to an hour manually cross-referencing breakdowns, notifications, and logs to build a status picture, the digital worker now assembles and summarizes that information automatically.

The digital workers’ output matches the team's own manual analysis more than 95 percent of the time, meaning the time recovered is genuine, not traded against accuracy. Across a team of technical leads, that amounts to between 125 and 250 hours of recovered productivity per person per year, with a direct financial value of roughly €12,500 to €25,000 annually per team lead depending on hourly rates.

Insights that were not visible before

Efficiency gains are the most measurable outcome, but not the most strategically significant one. What has mattered more for us is what Ultimo digital workers surface that manual review would have missed entirely.

By combining data across sources such as work orders, logbooks, and maintenance histories, the system identifies patterns that are hard to detect when each data stream is reviewed in isolation. This revealed that certain equipment issues were recurring structurally rather than randomly. That single insight changed how the team approached maintenance planning and where it directed improvement efforts.

By intelligently combining data from different sources, new insights emerge, enabling teams to set better priorities, identify structural issues, and carry out more targeted maintenance and improvements.

This is the practical meaning of Intelligent Asset Management: not AI as a reporting layer, but AI that changes which decisions get made, and when.

One lesson every manufacturer should hear

The most consistent message from our experience is that the value of AI is directly proportional to the quality of the data it works with. We believe that disciplined, consistent registration of notifications, work orders, and operational data is a prerequisite, not something AI can substitute for. Poor data hygiene does not get corrected by AI; it gets amplified.

For manufacturers evaluating where to start with digital workers in maintenance, this is the practical readiness test. The technology is capable. The question is whether the data foundation is there to support it. For us, years of structured EAM usage meant it was.

What comes next

The team's expectations continue to grow. The area generating most interest is troubleshooting support – a digital worker that not only identifies what has gone wrong but assists the troubleshooting.

Think of digital workers that analyze similar past failures and immediately suggest possible solutions. This can help technicians arrive at the right solution faster and further reduce downtime.

For a manufacturer operating across multiple factories and brands, that kind of embedded guidance - turning accumulated failure history into real-time decision support for any technician, regardless of their experience level - represents exactly the kind of knowledge transfer that the industry's workforce challenge demands.

The conclusion we have reached is the one more manufacturers are arriving at: AI does not replace the judgment and skill that experienced maintenance professionals bring. It removes the administrative burden that keeps them from applying it - and it finds the signal in operational data that no manual process reliably could. The starting point is closer than most organizations expect, and the returns begin earlier than most anticipate.

At the Food & Beverage Engineering Show 2026 and Sustainable Food Factory exhibition held at Derby Arena, industry professionals gathered to discuss the challenges and opportunities facing modern manufacturing. Among the experts sharing their insights was Andy Gailey, Managing Director of UPTIME Consultant Ltd, who highlighted the growing relationship between reliability, sustainability and operational efficiency.

The event, which brought together engineering and sustainability professionals under one roof, reflected a growing recognition that these disciplines are intrinsically linked. According to Gailey, sustainable manufacturing cannot be achieved without reliable assets and effective maintenance strategies.“Reliability and sustainability are two sides of the same coin,” he explained. “If you don't have a reliable plant, it becomes extremely difficult to achieve meaningful sustainability targets.”

This connection is becoming increasingly important as manufacturers face mounting pressure to reduce energy consumption, minimise waste and improve overall operational performance. Equipment failures, unplanned downtime and inefficient processes not only affect productivity but also contribute to unnecessary energy use and increased environmental impact.

Drawing on more than two decades of experience within the food manufacturing sector, Gailey emphasised that maintenance and reliability professionals play a critical role in supporting sustainability objectives. By ensuring equipment operates consistently and efficiently, organisations can reduce their consumption of electricity, gas and water while simultaneously improving production output.

The discussion also explored the current state of the food and beverage manufacturing sector.

While many businesses experienced a challenging and uncertain trading environment during the previous year, Gailey reported signs of renewed confidence across the industry.

As a specialist consultancy, UPTIME Consultant Ltd works closely with manufacturing organisations seeking to improve reliability and operational performance. Demand for these services has increased as businesses look for practical ways to enhance efficiency while controlling costs.

However, significant challenges remain. Rising employment costs, increased regulatory pressures and economic uncertainty continue to affect investment decisions across many sectors. Manufacturers are being forced to operate leaner than ever before while maintaining competitiveness in increasingly demanding markets.

One of the most discussed topics during the interview was artificial intelligence and its future role within manufacturing operations. While AI has become one of the industry's most widely used buzzwords, Gailey offered a more measured perspective.

Having spent several years studying machine learning and artificial intelligence technologies, he believes that many current applications fall short of the expectations often associated with true AI. He compared today's AI hype cycle to the early days of Industry 4.0, when numerous technologies were marketed under a broad and often misunderstood label.

Rather than relying solely on cloud-based systems and large-scale infrastructure, Gailey predicts that future industrial AI applications will increasingly move closer to the assets themselves. Manufacturers are likely to deploy smaller, site-based machine learning models that focus specifically on analysing plant performance, equipment condition and operational data within their own facilities.

This approach could offer several advantages, including improved data security, faster response times and greater relevance to individual operational requirements.

The interview reinforced a key message for maintenance and engineering professionals. Regardless of emerging technologies, the foundations of manufacturing success remain unchanged. Reliable equipment, effective maintenance practices and a commitment to continuous improvement will continue to underpin both sustainability and profitability.

As manufacturers navigate an increasingly complex operating environment, the organisations that successfully combine reliability, efficiency and innovation will be best positioned to meet future challenges while delivering long-term sustainable growth.

For more information visit www.uptimeconsult.co.uk

As artificial intelligence, predictive maintenance and digital transformation continue to reshape industry, many organisations are questioning how best to modernise their maintenance strategies. Donal Bourke, Managing Director of Eleco Asset Management, explains why successful asset management is not about chasing technology trends, but about building strong operational foundations that enable organisations to evolve with confidence.

The maintenance and asset man agement landscape is undergoing a period of significant transforma tion. Organisations across manu facturing, utilities, infrastructure and other asset intensive sectors are facing growing pressure to improve reliability, reduce costs, meet sustainability targets and embrace new technologies. At the centre of this evolution sits Eleco Asset Management, bringing together decades of expertise through solutions including Shire System and PEMAC. For Donal Bourke, Managing Director of Eleco Asset Management, the challenge is not simply about delivering software.

It is about helping or ganisations understand where they are today and identifying the most effective path towards greater maintenance maturity and operational excellence. According to Bourke, one of the strengths of the Eleco Asset Manage ment portfolio is its ability to support organisations at different stages of their maintenance journey. Some businesses are still heavily reliant on reactive maintenance practices, while others have developed ma ture preventive maintenance programmes and are now exploring con dition monitoring, predictive maintenance and artificial intelligence. The key, he explains, is recognising that there is no universal model for success. Every organisation operates within its own regulatory environment, culture and operational constraints. As a result, asset management strategies must be tailored to individual circumstances rather than forcing businesses into a predefined framework.

Despite the excitement surrounding emerging technologies, Bourke be lieves many organisations continue to face fundamental maintenance challenges. Ageing infrastructure, increasing compliance obligations, skills shortages and rising operating costs remain common concerns across multiple industries. At the same time, organisations are under pressure to adopt digital technologies and modern maintenance approaches. While these inno vations offer significant potential, Bourke cautions against focusing on advanced capabilities before addressing the basics. He frequently encounters organisations that have yet to standardise maintenance processes,

struggle to complete preventive maintenance activities consistently or lack reliable asset data. In these situations, introducing advanced technologies often creates additional complexity rather than delivering meaningful benefits. The most successful organisations, he argues, focus first on discipline, process and data quality. Once these foundations are established, tech nology becomes a powerful enabler capable of accelerating improve ment and supporting better decision making. Artificial intelligence has become one of the most discussed topics within maintenance and asset management.

While Bourke acknowledges its potential, he is careful to avoid overstating its capabilities. He believes many organisations are currently more focused on AI capability than AI readiness. The dis tinction is important. Artificial intelligence relies on structured processes, quality data and consistent behaviours. Without these foundations, even the most sophisticated AI tools will struggle to deliver reliable outcomes. Maintenance teams must therefore consider whether their organisation is genuinely prepared to benefit from AI. Robust maintenance processes, well structured asset hierarchies, effective data governance and strong workforce engagement all play a crucial role in determining success. Equally important is the human element. Main tenance technicians must consistently capture meaningful information about the work they perform. Procedures must be followed and systems must be used correctly. If data quality suffers, artificial intelligence simply magnifies existing weaknesses. Bourke describes AI adoption as a journey rather than a destination. Rather than asking what AI fea Page - 8 | June/July 2026 - engineeringmaintenance.info believes significant gains can also be achieved through better mainte nance practices.

Operational excellence and sustainability, he argues, are far more closely linked than many organisations realise. Looking ahead, Bourke believes the most successful asset manage ment organisations will be those capable of balancing operational discipline with a willingness to embrace change. Strong maintenance processes, trusted data and effective governance will remain essential foundations. At the same time, organisations must be prepared to adopt technologies that genuinely improve decision making and workforce effectiveness. tures they need, organisations should first assess whether they possess the operational maturity required to take advantage of them. He also highlights an important distinction between AI enhanced and AI enabled environments. In AI enhanced environments, people remain at the centre of decision making while artificial intelligence improves efficiency.

Examples include automatically triggering maintenance workflows when condition monitoring systems identify potential issues. AI enabled environments represent a more advanced stage of maturity. In these situations, artificial intelligence takes on a greater share of structured activities, analysing maintenance history, identifying recurring failure patterns and generating recommendations based on historical outcomes. Predictive maintenance is another area often surrounded by miscon ceptions. Bourke argues that many organisations are closer to achiev ing predictive maintenance than they realise. Modern industrial facilities already generate vast quantities of oper ational data through SCADA systems, equipment sensors, IoT devices and condition monitoring technologies. The challenge is not neces sarily collecting the information but determining what happens when anomalies are detected.

Successful predictive maintenance depends on the ability to convert operational insights into effective maintenance actions. Maintenance activities must be prioritised, work orders generated and planners pro vided with the information required to intervene before failures occur. In many respects, predictive maintenance is as much a workflow challenge as it is a technology challenge. The organisations achieving the greatest success are those that integrate operational intelligence directly into maintenance execution processes. Ultimately, the future of asset management is not about choosing between people and technology. It is about creating an environment where both can perform at their best. For organisations willing to focus on fundamentals while embracing innovation responsibly, the next era of asset management offers significant opportuni ties to improve reliability, efficiency and long term business performance.

www.eleco.com/ pemac Customer expectations are also changing rapidly. Businesses increasingly expect maintenance software to be intuitive, con figurable and capable of integrating seamlessly into existing environments. Rather than focusing exclusively on functionality, customers are increasingly evaluating outcomes. They want to under stand how quickly value can be realised, how reliability can be improved and how systems can support compliance requirements while reducing administrative burden. For Bourke, this shift reflects a broader trend within asset management. Organisations are no longer investing in software simply to digitise existing processes.

They are seeking measurable improvements in reliability, planning effectiveness, decision making and workforce productivity. Sustainability is another area where maintenance plays a critical role. Well maintained assets operate more efficiently, consume less energy and often remain productive for longer periods. Effective main tenance strategies reduce unnecessary downtime, minimise premature equipment replacement and optimise spare parts consumption. While sustainability initiatives are often associated with large scale capital investments, Bourke believes significant gains can also be achieved through better mainte nance practices. Operational excellence and sustainability, he argues, are far more closely linked than many organisations realise.

Looking ahead, Bourke believes the most successful asset manage ment organisations will be those capable of balancing operational discipline with a willingness to embrace change. Strong maintenance processes, trusted data and effective governance will remain essential foundations. At the same time, organisations must be prepared to adopt technologies that genuinely improve decision making and workforce effectiveness.

Ultimately, the future of asset management is not about choosing between people and technology. It is about creating an environment where both can perform at their best. For organisations willing to focus on fundamentals while embracing innovation responsibly, the next era of asset management offers significant opportuni ties to improve reliability, efficiency and long term business performance.

www.eleco.com