Maintenance Has Magnetism!
As the new Editor-in-Chief, I’ve spent this spring getting to know the world of maintenance. And it’s truly fascinating.
Everyday professionals ensure that operations run smoothly in production plants, on roads, railways, in ports, and shopping centres. In factories, production lines are maintained and deliver on their targets without dramatic interruptions. Roads and transport routes are functional and safe, allowing goods and people to move reliably. Homes and public spaces are refurbished and maintained to ensure they remain good places to live and operate.
Ports, rail transport, depots, and airports – the very foundations of our society – must serve their users 24/7, come calm or storm. Maintenance stands guard and keeps everything running. It is a cornerstone of supply security – often invisible, but vital for life and its ongoing pulse.
Maintenance is a critical part of industry, infrastructure, and services. The expertise of professionals in our field will become even more essential as new technologies and artificial intelligence become part of everyday life. These tools will not replace people – on the contrary, they empower us to do our work better, more efficiently, and more safely.
Today, there are unprecedented opportunities for skilled maintenance professionals. Demand for our know-how is growing, and the future looks bright.
There is work in this field – plenty of it, all around the world. Maintenance never ends: equipment, structures, and processes require constant care and development. As a field, maintenance is a major employer, offering diverse career paths for a wide range of talent.
I look forward to inspiring encounters with experts and readers in our field. Together, we can raise maintenance to the position it deserves and ensure the sector remains attractive and vibrant well into the future.
The future of maintenance is built on competence – let’s make sure, together, that the availability of skilled professionals doesn’t become a barrier to progress. Let’s invest in education in every country – education that inspires, evolves, and continues to produce highly motivated top talent for the industry!
Jari Kostiainen
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NVDO: A Longstanding EFNMS Partner and Leader in Maintenance Innovation
The Dutch Maintenance Society (NVDO), a founding member of the European Federation of National Maintenance Societies (EFNMS), has been a key force in shaping the European maintenance industry for 50 years. As an active member of three EFNMS committees and the General Assembly, NVDO leads efforts that promote innovation and professional growth throughout the sector.
The Dutch maintenance market keeps growing, even with global economic challenges. It now makes up 4.1% of the country’s GDP and provides jobs for around 326,500 people—representing a 3.7% rise in 2024 from the year before, according to NVDO’s annual survey with universities and industry partners.
After slowing down in 2023, the sector bounced back in 2024, but the shortage of skilled technical workers remains a major challenge.
NVDO General Manager Ellen den Broeder notes that more than two-thirds of job openings over the past year were for technical positions, and companies are finding it increasingly difficult to attract qualified candidates.
“The tight labour market remains a major issue, especially in technical and technological roles,” den Broeder explains. “On a positive note, the proportion of women working in maintenance has risen to a record 9.9% this year—the highest level in at least eight years,” she adds.
Turnover and Talent Retention Under Pressure
According to Den Broeder, the absenteeism rate in the Dutch maintenance sector is 5.4%, closely aligned with the national average of 5.3%, reflecting stable attendance levels. Meanwhile, the NVDO Maintenance Compass report reveals a rising staff turnover rate in the sector. This is largely driven by retirements and employee dissatisfaction.
Furthermore, more professionals are leaving the maintenance field altogether, with the percentage of industry exits increasing from 28% to 39% in just one year.
“This poses challenges for the sector when it comes to training talent. With the rise of advanced technologies and the use of complex digital systems, the demand for well-trained and certified maintenance professionals is growing,” Den Broeder says.

Den Broeder emphasizes that addressing the labour shortage requires a collaborative effort “No single organization can solve this challenge alone. Public-private partnerships between government, businesses, and educational institutions are essential. NVDO is encouraged by the increasing number of such collaborations.”
Cybersecurity – a Core Priority
Den Broeder emphasizes the growing importance of training and retaining skilled professionals in the face of rapid technological change. As operational technology becomes increasingly integrated with IT systems, cybersecurity has emerged as a critical concern. Inadequate data protection can result in severe consequences, including the loss of sensitive business information, underscoring the need for proactive and robust security strategies.
She further notes that upcoming European regulations will compel companies to strengthen their cybersecurity posture. Among these is the Cyber Solidarity Act (Regulation EU 2025/38), a key legislative measure designed to bolster cybersecurity resilience across the EU. It introduces enhanced threat detection capabilities, improved coordination of incident response among member states, a unified risk management framework for EU institutions, and the creation of an Interinstitutional Cybersecurity Board to oversee implementation. The regulation will also introduce mandatory cybersecurity standards that companies must comply with.
Building a Resilient, Skilled Workforce Together
In response to these emerging challenges, NVDO is intensifying its support for the maintenance sector. The organization offers targeted training programmes, upholds certification standards, and promotes lifelong learning to ensure professionals stay current with technological advancements. In parallel, NVDO actively collaborates with industry stakeholders to raise cybersecurity awareness and develop practical frameworks to help companies protect their digital infrastructure and meet evolving regulatory requirements.
Den Broeder hopes that the EFNMS with its committees and partnerships can contribute to the common European-wide problem in the maintenance industry: “Tackling the shortage of skilled technical workers is a shared European challenge. NVDO is keen to explore European solutions that could add significant value to our members.”
Dutch maintenance society (NVDO)
• NVDO represents 326.500 maintenance professionals in the Netherlands.
• The Dutch maintenance sector has an estimated value of €30-35 billion, accounting for about 4% of the country’s GDP.
• NVDO serves as Europe’s largest maintenance platform, supporting businesses and professionals in Asset Management.
• The organization promotes knowledge transfer, advocacy, and networking to enhance maintenance efficiency.
• NVDO works closely with various stakeholders (fe: the government) to drive innovation and best practices.
Dutch Industrial Maintenance Market Set to Reach $9.97 Billion by 2032, Powered by Innovation and Steady Growth
The Netherlands’ industrial maintenance market is on a steady growth trajectory, projected to reach nearly USD 10 billion by 2032, with a compound annual growth rate of 2.7%. Despite challenges like high labour costs, the market continues to grow as companies embrace the benefits of digitization and automation.
Key trends include the rise of predictive maintenance using IoT for real-time monitoring, as well as targeted workforce upskilling initiatives to meet demand for specialized MRO (Maintenance, Repair, and Operations) services.
The Dutch government actively supports this shift through strategic policies and investments:
• Green Deal Industrial Plan: Part of the EU’s broader green strategy, it promotes clean tech and reduced carbon emissions in which NVDO contributes
• Industrial Decarbonization Scheme: A €750 million EU-backed initiative encouraging fossil-free industrial processes.
• Vision on Industry Policy:
A long-term focus on digital transformation and sustainability to boost competitiveness.
Sources: Polaris Market
Research, www.eerstekamer.nl
Text: Nina Garlo Photos: NVDO
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From Healthcare to Industrial Care: Kemira’s Revolutionary Approach to Asset Management
Just as modern healthcare has shifted from treating illnesses to preventing them, Kemira is revolutionizing industrial maintenance by treating its rotating assets like a population of patients. The secret? Treating equipment failure is not as inevitable, but as entirely preventable.
Through an innovative partnership with Asensiot Oy, the global chemical company has developed a groundbreaking preventive approach that’s already delivered a sevenfold return on investment across ten production sites.
“In safety, every accident is preventable. Yet, when it comes to rotating assets, we still accept failures as inevitable. Why are we willing to tolerate risks that we know can be eliminated? OEE (Overall Equipment Efficiency) can track performance but misses hidden risks, so we needed new metrics in risk assessment,” begins Carl Bristow, Director of Safety & Manufacturing Excellence at Kemira Oyj, a global chemical company.
Kemira operates over 60 production facilities worldwide, but previously lacked a comprehensive, real-time overview of the true condition of its rotating equipment, an essential requirement for enabling a new, more sustainable maintenance strategy.
Traditional condition monitoring practices focus mainly on critical assets, leaving the overall picture of asset health incomplete.
To improve data-driven management, Kemira launched a collaboration project with Asensiot Oy, a Finnish Value-as-a-Service company, in 2021. The goal was to create a new, scalable operating model that would support Kemira’s sustainable maintenance goals, motivate field personnel, and allow for easy and rapid implementation from one plant to another. This approach aimed to quickly identify concrete cases to achieve Kemira’s strategic objectives.

“Just as healthcare focuses on proactive care for large populations, we decided to bring the same large-scale preventive approach to Kemira’s rotating assets. Yet, in industry, the focus is often on scheduling repairs, even though much of the risk of unplanned failures can be minimized by taking proactive actions to address fault progression at an early stage,” says Aki Karuveha, CEO of Asensiot Oy, a MyAsensiot Condition Screening® company.
By partnering with Asensiot, Kemira developed a new collaboration model with key metrics that provide proactive, actionable information on rotating assets in a structured format, integrated directly into Kemira’s SAP/HANA system. This enables early detection of potential issues, supports optimized maintenance planning, and reduces the number of corrective interventions required over the long term. It also streamlines maintenance actions, ensuring resources are focused on assets that truly need attention-minimizing unnecessary work and supporting the company’s sustainability and operational excellence goals.

From Vision to Reality: A Scalable Solution
“At first, we wanted to understand what kind of data we should collect and how this could be done efficiently, using available measurement technologies and without requiring special skills at our sites,” says Bristow.
At one of Kemira’s plants, a range of measurement technology tests revealed that wireless technology did not provide a cost-effective solution for achieving a comprehensive overview of asset condition at scale. On the initiative of Kemira’s field personnel, a pilot was launched using an operating model where relevant data is collected quickly and easily with a route collector during existing monthly inspection rounds. RFID technology ensures that data is always measured for the correct asset and later enabled field observations and asset-specific information to be accessed via mobile devices.
“We want our field personnel at production sites to be engaged in the process. Regular route routines and field observations support the development of our safety culture. So monthly measurement routine is much more than only focusing on data,” adds Bristow.
The ability of in-house personnel to conduct measurements provides exceptional flexibility, especially for monitoring batch processes, and enables rapid response when a change in asset performance is suspected. Additionally, quickly verifying asset condition after maintenance helps prevent failures that could arise from potential installation or assembly errors.

At Kemira’s production sites, comprehensive measurements are routinely performed once a month and more frequently if needed with the collected data uploaded to the supplier’s cloud service. The volume of transferred data is optimized, ensuring that only essential, standardized raw signals are sent for processing by artificial intelligence algorithms to pinpoint focus areas.
“We need actionable information integrated into our work order process, not just alarms. It was clear to us that technology alone would not support our sustainable maintenance goals,” highlights Carl Bristow.
Insights into Impact
In Kemira’s new condition screening operating model, only essential action-guiding, standardized non-routine notifications are generated for SAP/HANA, thanks to a scalable AI-algorithm-based screening and expert validation process. This allows Kemira to focus solely on what matters, maintenance actions that truly make an impact.
At the core of this new approach are the people in the field and supporting their daily work. User motivation stems from information that makes their work easier-most importantly, by identifying concrete cases where users can see the direct link between actionable guidance and real impact. Without impact, there is no value.

Following a successful pilot, the new operating model was rolled out to 10 production sites in different countries during 2023 (Wave 1). The deployment of monthly monitoring was straightforward and required no prior site-specific information. For a two-person team, the total fieldwork amounted to just around 14 days. In 2024, Kemira implemented the system at 16 additional production sites (Wave 2).
“Sustainable reliability is not just monitoring critical assets or avoiding unplanned shutdowns by scheduling repairs; its true impact at scale lies in extending asset lifetime and avoiding unnecessary maintenance actions to reduce overall risk of unplanned repairs,” explains Aki Karuveha.
Kemira’s Wave 1 Statistics
• Wave 1: 10 Sites (Results from November 2023 Onward)
• Deployment Time: 14 Days On-Site / 2 Persons
• Measured: 779 Individual Assets
• Extended Asset Lifetime: 14 Realized Cases
• Avoided Unplanned Shutdowns: 45 Realized Cases
• Estimated Costs Avoided: €2,264,000 (~7x ROI)
The Numbers Speak
“Kemira has achieved multiple benefits by adopting a sustainable reliability approach to rotating assets, including increased equipment uptime, reduced maintenance costs, decreased manpower requirements, improved energy efficiency, and a smaller ecological footprint,” summarizes Carl Bristow.

Condition screening provides a comprehensive monthly overview of the health of rotating assets, delivering an extensive situational picture that seamlessly integrates with Kemira’s Asset Performance Management (APM) in SAP/HANA. Without a realistic picture of asset health, APM becomes ineffective, leading to poor decision-making, missed optimization opportunities, increased risks, and fragmented processes. Accurate asset health data is essential for APM to improve reliability, reduce costs, and enhance efficiency.
Kemira is continuously improving communication by linking SAP/HANA with the supplier, enabling tracking of maintenance actions and their impact on resolving flagged issues, and supporting efficient, active collaboration between Kemira and Asensiot.
Text: Mia Heiskanen, Aki Karuveha Images: Asensiot Ltd.
Summary
Kemira’s proactive, data-driven approach to rotating asset risk assessment is delivering tangible benefits across its global operations. By focusing on early detection, actionable insights, and scalable processes, Kemira is setting a new benchmark for sustainable reliability and maintenance excellence in the process industry.
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The Future of Rail Freight: the Rise of the Internet of Things and Digitalisation
Rail freight transport is undergoing a major transformation, driven by significant investments in the digitalisation of operations.
– The global rail telematics market is driven by the growing demand for efficient, safe, and cost-effective transportation systems.
The expansion is driven by the advancement of digitalization and integration of IoT technologies with an emphasis on real-time data analytics for predictive maintenance, says Adhish Luitel, Principal Analyst, ABI Research.
While Europe has made significant progress in the deployment of IoT, North America is still underdeveloped. According to ABI Research the region has a Total Addressable Market (TAM) of almost 2 million railcars, which offers significant opportunities for IoT-based solutions.
The role of IoT in railways
IoT technologies are transforming freight rail operations by integrating sensors, AI-based analytics, and cloud computing into everyday logistics. Smart train cars equipped with GPS, vibration sensors and automated reporting mechanisms can now send real-time data to operational control centres.
This connection allows operators to monitor location, freight condition and potential maintenance problems, ensuring maximum efficiency and safety throughout the transport process.
Predictive maintenance
Predictive maintenance is one of the most revolutionary aspects of IoT in rail freight. By analysing data collected in real-time from train wagons and infrastructure, AI algorithms can predict failures before they happen.
This reduces downtime, prevents costly disruptions, and improves safety by ensuring that potential mechanical problems are resolved proactively.
Replacing many manual tasks
Traditionally, machine vision and sensor-based inspection equipment, often installed at railway crossings, has been at the forefront of improving operational visibility.
Rail brake inspections are also a critical but time-consuming task. These inspections ensure that the air brake system is functioning correctly throughout the train, which can be more than a mile long. Manual checks require extensive coordination between train crews and control centres, which can cause delays and inefficiencies.
IoT technologies offer a solution by providing real-time data and predictive analytics, ultimately improving safety, reducing downtime, and improving compliance.
Challenges of integration
The deployment of IoT on freight railways faces a number of challenges. In North America, for example, the adoption of IoT-based visibility solutions has been slow compared to Europe, largely due to the extensive infrastructure and the different regulatory environments in different states and countries. In addition, integrating legacy rail systems into modern IoT frameworks requires significant investments in hardware, software, and training.
Security is another growing concern. As more and more train cars are connected, cybersecurity risks will increase, making it important for operators to put in place robust security measures. Strong encryption, real-time threat monitoring and compliance with industry security standards are essential for the successful digital transformation of the industry.
“AI algorithms can predict failures before they happen.”
“The deployment of IoT on freight railways faces a number of challenges.”
Trilogical Technologies: telematics solutions for long freight trains
As freight demand increases, rail operators are moving to longer trains, particularly in North America. Around half of freight trains are now over 1.65 km long, and this growth is continuing.
Trilogical Technologies presented its own technology at InnoTrans 2024. The company has developed the Long-Train Intelligence System (LTIS® ) to manage the complexity of longer trains by integrating real-time control systems that improve safety and efficiency. Key features of the system include:
Continuous Train Integrity: monitors wagon placement from start to finish and ensures train integrity during transport.
Driver Advisory System: provides drivers with status updates and alerts to prevent operational delays.
Condition monitoring: Uses sensors to detect anomalies and reacts quickly to avoid disruptions.
Condition monitoring and predictive maintenance: Supports predictive maintenance strategies that is estimated to reduce costs.
Hitachi Rail, Connected Places Catapult Announce AI Rail Maintenance Tech

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Industrial Robotics: Trends Defining the Next Generation
Industrial robotics is experiencing a transformative shift, driven by rapid advancements in artificial intelligence (AI), machine learning, and automation technologies. No longer confined to repetitive assembly tasks, robots have become central to the future of manufacturing, logistics, healthcare, and industrial maintenance. As companies demand greater efficiency, precision, and adaptability, robotics is evolving from a supportive tool to a strategic asset.
To better understand these changes, Maintworld spoke with Christian Schlette, Professor at the Mærsk Mc-Kinney Møller Institute (MMMI) Head of the University of Southern Denmark’s Center for Large Structure Production (LSP) and co-founder of the Danish Academic Society of Robotics (DACAS-Rob). According to Schlette, a trend in industrial robotics is the integration of AI, which allows machines to make autonomous decisions, learn from their environments, and optimize performance in real time.
“AI is increasingly enabling robots to handle dynamic environments and more complex tasks that go beyond hard-coded programming,” Schlette explains.
Among other innovations, collaborative robots—or cobots—have gained ground for their ability to safely operate alongside human workers, enhancing both productivity and workplace safety. Autonomous mobile robots (AMRs) are also reshaping logistics and warehousing, while soft robotics is opening doors to automation in fields that require delicate, adaptive handling—such as food processing and healthcare.
Robotics in Industrial Maintenance
In maintenance, robotics is ushering in a new era of predictive diagnostics. Robots equipped with sensors and powered by AI can now identify and address problems before they cause downtime. This shift from reactive to proactive maintenance reduces costs and improves operational efficiency. Robots are also being deployed in hazardous environments, performing inspections or repairs that would be dangerous for human workers.

Leading Industries in Adoption
Industries such as automotive, electronics, healthcare, and logistics are leading the charge in adopting robotics. In automotive manufacturing, robots improve speed and precision on the production line. Electronics companies use robotics to handle micro-components with accuracy. In healthcare, surgical robots and diagnostic systems are transforming patient care. Warehouses are relying on robots to streamline everything from inventory tracking to order fulfillment.
The Role of AI and Machine Learning
AI and machine learning are at the core of this robotics revolution. These technologies enable predictive analytics for maintenance, enhance visual recognition systems for quality control, and allow robots to make decisions on the fly. This autonomy is making robots smarter, more efficient, and more adaptable to real-world challenges.
Cobots: Redefining Human-Robot Collaboration
Cobots are changing how humans and machines interact in the workplace. They are designed to assist rather than replace, taking over repetitive or physically demanding tasks while allowing human workers to focus on more complex activities. Because cobots are relatively affordable and easy to implement, they are especially valuable for small and medium-sized enterprises (SMEs) looking to embrace automation without major infrastructure changes.
Addressing Labour Shortages and Skills Gaps
The growing use of robotics is helping industries deal with persistent labour shortages. By automating routine jobs, businesses can operate efficiently with fewer workers. At the same time, AI-powered training tools are helping employees develop new skills and transition into roles that support or manage automated systems.

Challenges in Integration
Despite their promise, robotics systems can be challenging to integrate into existing operations. High upfront costs, compatibility issues with older equipment, and the need for workforce reskilling are common hurdles. However, many companies are overcoming these obstacles through strategic planning, modular solutions, and service-based models such as Robotics-as-a-Service (RaaS), which reduces financial risk by converting capital expenses into operational ones.
Supporting Sustainability Goals
Robotics is also contributing to more sustainable industrial practices. Intelligent automation can optimize energy use, reduce material waste, and enhance recycling efficiency. Robots can be programmed to perform tasks with precision and consistency, leading to fewer errors and less scrap, especially in high-precision industries.
Text: Nina Garlo Photos: Jusmatics Oy, the Danish Academic Society of Robotics (DACASRob)
How DACAS-Rob is Shaping the Future of Robotics in Denmark

At the forefront of robotics research and collaboration, the Danish Academic Society of Robotics (DACAS-Rob) connects universities and industry to drive innovation in robotics. Through joint research, educational initiatives, and applied projects, DACAS-Rob supports Denmark’s position as a key player in European robotics.
The society shares insights through webinars, video discussions, and its official YouTube channel, which highlights the latest in Danish robotics research and academic contributions. A dedicated webinar series also showcases leading-edge developments from across the country. https://dacas-rob.org/
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The Digital Twin Paradox: Data Can Remember – But Physics Knows
The concept of the digital twin has matured. What began as a passive mirror of physical systems has evolved into a strategic, intelligent asset, capable of sensemaking, foresight, and context-driven adaptation. This article explores how digital twins have advanced through successive generations, why physics-based modelling is now essential, and how hybrid approaches like Physics-Informed Neural Networks offer the key to navigating unpredictable, high-risk scenarios—the so-called Black Swan events.
Evolution of the Digital Twin: From Data to Understanding
Digital Twin 1.0 emerged from the world of operational technology (OT), characterized by real-time data acquisition and system visualization. These early twins mirrored reality without interpretation. They offered data, but not meaning; measurements, but not insights. Their role was reactive, not proactive. In a way, Digital Twin 1.0 was like a digital photograph—faithful, detailed, and ultimately flat. There was no depth, no sense of consequence, no capacity to engage with time. The twin showed what was, but had nothing to say about what could be.

Digital Twin 2.0 integrated IT and OT systems, expanding the scope to include enterprise data, ontologies, and structured coordination. It allowed visibility across operational and managerial layers, allowing stakeholders to ask, “What can I see and manage in my data?” While it improved situational awareness, it still lacked the ability to predict outcomes or guide actions. It was more like an instrument panel than a mirror—a dashboard that contextualized what had happened, but remained tethered to retrospective logic.
Then came Digital Twin 3.0, and with it, a deeper awareness of limitations. This phase highlighted a growing tension between data science and the reality of industrial systems when operations and maintenance professionals encountered the limitations of purely statistical or black-box machine learning models. Algorithms might detect patterns, but they could not explain them. A prediction without understanding is like a prophecy—possibly correct, but fundamentally unusable.
In this phase, digital twins began to resemble the portrait of Dorian Gray: an image evolving in parallel with the physical object, revealing degradation and change, but leaving us uncertain as to what was driving the transformation. Beyond reflection or replication, we needed reasoning. There was a clear need for digital twins to become trustworthy decision aids—not just dashboards or mirrors. That need laid the groundwork for a new wave of hybrid approaches, in which machine learning was enhanced with physics-based understanding. This shift was not only technical, but also cultural: engineers demanded interpretability, transparency, and causal reasoning, arguing, “Without physics, we guess. With physics, we project.”
Data Aren’t Enough
The limitations of purely data-driven methods in industrial contexts are well-documented. Traditional machine learning often fails to generalize to unseen conditions or rare events. It performs well when past patterns are stable, frequent, and well-represented. But the real world rarely behaves so cooperatively. In many cases, these models are trained on narrow slices of history—bounded, biased, and blind to what lies outside them.
When datasets are noisy, incomplete, or suffer from selection bias, models become fragile. Perhaps most critically, they produce results that are difficult for domain experts to interpret. This lack of transparency isn’t merely inconvenient—it can be dangerous. In safety-critical environments like energy, transportation, or manufacturing, trust is not optional. If the model can’t explain itself, engineers won’t act on it.
As systems grow more complex and interdependent, organizations are confronted with a paradox: they have more data than ever before, yet are increasingly unable to convert those data into meaningful decisions. Retrospective analytics focus on past correlations and cannot account for emergent behaviours, cascading faults, or nonlinear dynamics. They can tell us what happened, but not why—or what’s about to happen next.
Even advanced deep learning architectures, powerful as they may be, remain prisoners of their data. They extrapolate patterns; they do not infer causality. They can classify failures but rarely understand failure mechanisms. As a result, they fall short in helping us manage uncertainty, assess risk, or build resilient systems.

Black Swan Events and Limits of Prediction
Black Swan events—rare, high-impact failures that escape conventional forecasting—pose one of the greatest challenges to modern predictive systems. These events may be triggered by subtle system degradation, unexpected interactions between components, or sudden environmental changes. What makes them especially dangerous is their invisibility in historical datasets: they lie outside the statistical envelope of what has previously occurred.
The core issue is that traditional machine learning is retrospective. It learns only from what it has seen. If a critical failure mode has never been captured in data or has occurred so infrequently that it leaves no meaningful statistical signature, the system remains blind to it. This is the paradox of the Black Swan: the more catastrophic the event, the less likely it is to be represented in our records. Absence of data becomes a dangerous illusion of safety.
In complex, tightly coupled industrial systems, this blind spot is a systemic risk. These systems often operate across wide ranges of physical conditions and are subject to wear, aging, and environmental variation. Over time, they can drift into failure modes that were never present in commissioning or early operation. Machine learning, dependent on narrow training distributions, cannot extrapolate meaningfully into these outlier states.
To address this, we must introduce the laws of physics as a structural layer in our predictive architecture. Physics doesn’t require observation to assert truth—it governs even in the absence of data. By incorporating physical principles such as conservation laws, thermodynamics, structural dynamics, or fluid mechanics into our models, we can give them a broader frame of reference. These principles can become a scaffolding for uncertainty, constraining predictions to remain plausible even when data are incomplete, noisy, or unprecedented.
The integration of physics is not just about increasing accuracy; it is also about building resilience into the logic of prediction. With physical knowledge embedded into them, systems can run simulations of hypothetical conditions, stress-test critical functions, and explore how anomalies might evolve—long before those paths are evident in sensor data.
By moving beyond statistical mimicry and embedding an understanding of how systems behave, we can start to detect the early tremors of Black Swan events. Only then can predictive systems evolve from pattern matchers into risk sentinels.
Articulating Physics through Synthetic Data and Simulation
In the industrial world, the scarcity of failure data isn’t just an inconvenience—it’s a fundamental obstacle. Critical failures, while rare and undesirable, are exactly the scenarios predictive models need to understand. But when they do happen, the conditions leading up to them are often chaotic, undocumented, or too hazardous to safely replicate. This creates a structural blind spot: the moments we most need to predict are the ones we least understand.
To overcome this, industries are turning to virtual prototyping and physics-based simulation as a new foundation for intelligent modelling. Platforms like Modelica, finite element modelling (FEM), and multi-body simulations allow engineers to recreate both normal and failure-prone behaviours of systems in controlled digital environments. These simulations are not only safe—they are hyper-configurable, enabling us to observe how a component responds under stress, fatigue, corrosion, overload, or even misuse.
The result is a new class of training data: synthetic, scenario-rich, and physically grounded. We can simulate how a rolling bearing degrades under variable loads, how thermal stresses propagate in a turbine, or how a gearbox responds to lubrication loss. Every simulation becomes an experiment—an opportunity to generate labelled datasets that fill the gaps in historical operation.
Techniques such as fault injection, stress testing, and parametric sweeping create data far beyond the reach of real-world experimentation. Because these simulations are based on first-principle physics, the resulting data both reflect possible system behaviours and reinforce the laws governing them.

Physics-Informed Neural Networks: From Data to Understanding
Synthetic data provide a plethora of rich behavioural patterns, but it’s the learning method that determines how much value we can extract from them. Traditional neural networks, even when trained on large datasets, remain limited by their lack of interpretability and adherence to physical constraints.
Physics-Informed Neural Networks (PINNs) revolutionize how machine learning models interact with knowledge. Unlike standard networks that learn correlations from data alone, PINNs encode known physical laws, such as partial differential equations, conservation of mass and energy, or thermodynamic boundaries, into the model’s structure. These equations shape the loss functions, enforce behavioural constraints, and inject meaning into every parameter.

This fusion creates models that are not only data-aware but also physics-consistent. PINNs can infer system behaviour in unmeasured conditions, extrapolate to unseen scenarios, and remain faithful to the physical truths engineers depend on. This makes them particularly valuable in data-scarce domains, where historical measurements are insufficient or unreliable.
In the context of digital twins, PINNs act as intelligent intermediaries between simulation and reality. They use synthetic data not just to train, but also to refine and validate system models in real time. Their predictions come with physical justifications, enabling engineers to see the twin not as a black box, but as a knowledgeable collaborator.
PINNs enable faster simulations, more accurate anomaly detection, and predictive capabilities that are both interpretable and grounded. They allow us to pose “what-if” questions, simulate failure paths, and anticipate how systems might evolve, not only statistically, but also structurally. For instance, a PINN model trained on turbine dynamics can predict the onset of blade fatigue long before vibration sensors detect anomalies.
Ultimately, PINNs elevate digital twins from descriptive to prescriptive intelligence. They do not just signal change—they explain it. They do not just see risk—they understand it. And in doing so, they lay the groundwork for a new generation of industrial decision-making, one that fuses data science with engineering judgment in practical and profound ways.
Conclusion: From Echoes to Insight
The evolution of digital twins is not just technological—it is conceptual. Instead of acting as mirrors of the physical world, twins are becoming intelligent agents that combine data, physics, and simulation into decision-ready insight.
Hybrid approaches, especially those using PINNs, represent the frontier of this transformation. They allow us to embed knowledge into our machines, not just feed them numbers. They empower us to detect the swan song of an asset before silence falls.
Most importantly, they offer a path to true contextual intelligence, turning overwhelming complexity into meaningful, actionable understanding. As Europe pushes for digital sovereignty and resilient infrastructure, the time to embed explainable, physics-informed intelligence into our systems is now.

Text: Diego Galar
Photos: iStock, SHUTTERSTOCK Images: Diego Galar
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Thanks for the past—looking ahead to new adventures
This is my final editorial as Editor-in-Chief of Maintworld Magazine.
As of January 2025, Jari Kostiainen has taken over the role, bringing fresh leadership to the publication. We’ve also restructured our editorial team, and I’m pleased to welcome back two familiar faces—Nina Garlo and Mia Heiskanen.
For me, this marks the conclusion of my full-time working life, though I won’t be stepping away from the maintenance scene entirely. I will continue contributing to Maintworld as a freelancer, and in my role as a Board Member of the European Federation of National Maintenance Societies (EFNMS), I remain well-positioned to follow the latest developments in maintenance and asset management. Over the years, my work in this field has evolved into a passion, enriched by a strong professional network and many valued friendships.
The Growing Importance of Asset Management
Asset management is becoming an increasingly critical focus for many companies. However, its full implications for maintenance professionals and production teams are still being defined.
Another key topic shaping the future of our industry is artificial intelligence (AI)—a subject we’ve covered extensively in our magazine. Whether AI will completely transform maintenance remains to be seen. Some have already raised concerns about unnecessary hype surrounding AI and its effects.
While AI and asset management are important, we must not overlook the fundamental skills essential to maintenance. After all, industries worldwide quite literally keep moving thanks to a thin layer of oil within machines, components, and moving parts. The expertise required to maintain these essential systems remains irreplaceable.
As I step into a new phase, I would like to take this opportunity to say thank you to all the colleagues, professionals, and friends I’ve had the privilege of working with over the years.
This issue will also feature an overview of Jari Kostiainen, who will be leading Maintworld into the future.
We continue to welcome your feedback and story ideas.
Jaakko Tennilä
Editor-in-Chief, Maintworld Magazine (until the end of 2024)
Jari Kostiainen
Editor-in-Chief, Maintworld Magazine (from 1.1.2025 onwards)
jari.kostiainen@kunnossapito.fi
Editor-in-Chief, Maintworld Magazine (until the end of 2024)
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Painting the Picture of Cybersecurity
Cyber threats are no longer confined to computer screens as they shape industries, economies, and even societies. In this exclusive interview, cybersecurity global expert Mikko Hyppönen paints the picture how the digital battlefield has evolved, what industrial leaders must do to protect their business operations, and why AI-generated art unsettles him.
The walls around Mikko Hyppönen tell a story. Abstract paintings, digital sculptures, and eerie sound installations inspired by cyber threats surround him. Standing in the heart of Museum of Malware Art, the world’s first cybersecurity-themed art gallery at
WithSecurity headquarters Helsinki, he speaks about a different kind of artistry, the symphony of cyber defense, where every note can make the difference between harmony and chaos.
Hyppönen, a legendary cybersecurity expert and global thought leader, has spent decades tracking the evolution of digital threats. But for him, the battle against cybercrime is more than just a technical challenge; it’s a fundamental aspect of modern society’s survival.
The evolution of cyber threats. Looking back at his career, Hyppönen reflects on how dramatically the cybersecurity landscape has changed. “When I started in the 1990s, viruses were mostly created by hobbyists—teenagers writing code for fun, sometimes destructive, but without a real financial motive. Today, we are facing highly organized crime syndicates and nation-state actors who conduct sophisticated attacks for power, money, and political gain.”
One of the most surprising transformations has been the industrialization of cybercrime. “Hackers don’t just create malware anymore,” he explains. “They run full-fledged businesses, complete with customer support for victims who are paying ransoms. The attacks are automated, efficient, and relentless.”
The industrial cyber war is a new battlefield. “Technology revolutions shape our world more than anything else,” Hyppönen states. “We’ve seen it with the internet, mobile technology, and now artificial intelligence. Each revolution brings progress but also risks.”
For industrial and manufacturing companies, these risks are no longer hypothetical. Cyberattacks on factories and production lines are becoming as disruptive as physical disasters like fires or power failures. “The difference is that no arsonist stands outside a factory trying to set fires every single day. But cybercriminals are constantly trying to break in, every hour and every second.”

Recent attacks have shown how organized and persistent cybercriminals are. “These aren’t lone hackers in basements,” Hyppönen warns. “These are fully structured organizations and the methods they use range from exploiting outdated systems to deploying sophisticated AI-driven phishing campaigns.”
The weakest link is connectivity and complacency. Many industrial leaders still believe they are not targets. “Why would they come after us?” is a common sentiment, Hyppönen says. “But when you analyze attack patterns, you see no logic in victim selection. One day, a steel manufacturer in Canada. The next, a furniture company in the Netherlands. Hackers don’t choose their victims; they find vulnerabilities and exploit them.”
What is a common entry point for these attacks? Poorly secured remote access systems. In the race for efficiency and digital transformation, factories have connected their networks in ways that expose them to threats. “Every system today assumes that electricity and the internet will always be there,” Hyppönen explains. “The moment one fails, production halts. In ten years, losing internet connectivity will be as catastrophic as a total electricity failure today.”
Seeing the unseen. When asked how companies can defend themselves, Hyppönen emphasizes one thing: visibility. “You can’t protect what you can’t see. Do you know how many devices are connected to your company network? How many are running outdated software and how many have unnecessary access to critical systems?”
Hyppönen recommends industrial companies to conduct regular security audits, penetration tests, and continuous network monitoring. “Think of it like tuning an orchestra. If one instrument is out of tune, the entire performance suffers. The same applies to cybersecurity. A single vulnerable device can be an entry point for disaster.”
One of the most effective ways to test a company’s vulnerabilities, he adds, is to order a controlled attack. “Ethical hacking exercises allow organizations to identify weak points before real attackers do. We conduct these penetration tests, and, in my experience, there is no system that cannot be breached. Once vulnerabilities are found and fixed, the test should be repeated to ensure security improvements hold.”

The AI dilemma: art or algorithm? Despite his fascination with technology, Hyppönen is not entirely comfortable with all aspects of artificial intelligence. “I don’t particularly like the idea that AI can create art, whether it’s music, poetry, or visual art pieces,” he admits. “Creativity has always been uniquely human, and the thought of a machine generating something deeply emotional feels unsettling to me.”
To illustrate his point, Hyppönen recalls an example. “Last year, a song generated entirely by AI made it to the German single charts. The AI composed the melody, wrote the lyrics, arranged the music, and even synthesized the vocals. No human intervention. And yet, it became a commercial hit.”
He pauses for a moment before adding, “That’s both impressive and terrifying despite the fact that I actually liked the song.”
What’s Next? Looking ahead, Hyppönen sees an even more disruptive technological shift on the horizon: quantum computing.
“Once we have sufficiently powerful quantum computers, they will break most of today’s encryption standards,” he warns. “This means that every piece of encrypted data stored today might become readable in the future. Organizations need to start preparing for post-quantum cryptography now.”
The implications for industry are profound. Secure communications encrypted financial transactions, and intellectual property protection all depend on encryption. “If we don’t develop new security standards in time, we could face a global crisis where everything we thought was safe, is suddenly exposed,” he adds.
The man behind the mission. For someone who spends his days battling digital criminals, how does Hyppönen unwind? The answer lies in a different kind of machine: the pinball machine. “I love playing pinball,” he says with a smile. “I even compete at the national level.” Restoring and maintaining vintage pinball machines gives him the same satisfaction as fighting cyber threats. Both require precision, patience, and an eye for patterns.
But ultimately, what keeps Hyppönen motivated is the bigger picture. “Cybersecurity isn’t just about protecting computers. It’s about protecting societies,” he says. “In a world where everything runs on technology, securing digital infrastructure is as crucial as securing physical borders.”
Hyppönen also highlights the value of working with a team of top-tier professionals from around the world. “The best part of this job is working alongside some of the most brilliant minds. Together, we help organizations during their worst moments: when they’re in the middle of a crisis and need real solutions fast.”
As he walks through the gallery, past an AI-generated piece visualizing a ransomware attack, Hyppönen pauses. “We’re in a digital renaissance. And like any great era of change, it comes with both beauty and destruction. Our job is to make sure the balance tips toward the right side. The cyber symphony is now playing, but the question is: are we listening?”
According to Mikko Hyppönen, one of the most surprising transformations has been the industrialization of cybercrime
He works as the Chief Research Officer at WithSecure and as the Principal Research Advisor at F-Secure. With over 30 years of experience, he has been instrumental in battling major cyber threats and has worked on some of the most significant malware outbreaks in history. Hyppönen has also been a key figure in uncovering cybercrime operations and online espionage.
Hyppönen has been named one of the 50 most influential people on the web by PC World and was recognized as a “Code Warrior” by Vanity Fair. He has written extensively for publications such as Scientific American and Foreign Policy, further solidifying his position as a thought leader in the field.
In addition to his speaking engagements, Hyppönen is the author of the book If It’s Smart, It’s Vulnerable, where he discusses the security risks posed by modern technology.
From Invisible Threats to Visible Art
“While malware was never meant to be art, it reveals an unintended artistry — a creativity born from skilled programming mixed with disruptive intent. By bringing malware and art together, the Museum of Malware Art lets us look beyond the code to see the bigger picture these digital threats paint a story about trust, vulnerability, and the hidden effects of technology.”
Mikko Hyppönen
Chief Research Officer, WithSecure
Curator, Museum of Malware Art
Text: Mia Heiskanen
Photos: Sami Perttilä
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Shaping Denmark’s Maintenance Industry
The Danish Maintenance Society (DDV) is a non-profit network that connects professionals in Denmark’s maintenance industry. With around 1,000 members from over 350 companies, DDV fosters knowledge exchange and collaboration through conferences, seminars, and company visits. Its mission is to help organizations optimize operations through effective maintenance, positioning maintenance as a key factor for long-term success.
DDV’s vision is to be Denmark’s main hub for operational optimization through maintenance. It offers a platform where organizations can learn best practices, improve processes, and stay updated on developments in the maintenance field.
“Our goal is to position maintenance as a strategic advantage for businesses, ensuring sustainability and improving efficiency,” says DDV Chairman Jesper Pedersen.
Evolution of Denmark’s Maintenance Sector
Denmark’s maintenance sector has evolved with technological advancements, automation, and sustainability demands. DDV has developed the DDV Analysis, an online tool for organizations to benchmark their maintenance maturity.
The tool measures perceived maintenance levels across five stages: planned maintenance, proactive maintenance, optimized organization, engineered reliability, and maintenance excellence, using 25 key subjects to benchmark organizations’ maintenance practices.
It helps identify improvement areas and encourages internal discussions on best practices. With over 400 responses so far, DDV aims to verify these results through academic research in 2025.
Through the DDV Analysis, organizations can identify their strengths and weaknesses, align their maintenance strategies with company goals, and prioritize investments in areas that will deliver the greatest impact. The tool also fosters internal discussions within organizations, helping maintenance teams build a common understanding and approach to challenges.
Attracting and Developing Talent in Maintenance
“The maintenance sector in Denmark is shifting from merely fixing equipment to optimizing operations and reducing downtime,” says Eva Mosegaard, CEO of DDV.
Attracting young talent is a priority for DDV and for the success in the industry. The organization offers the Asset Maintenance Management course for professionals new to maintenance or project management. In collaboration with educational institutions, DDV also publishes the textbook Vedligehold (Maintenance), which is used in a variety of educational programs, including Marine and Technical Engineering and the Technological Diploma in Maintenance. This resource provides students with essential knowledge about strategic maintenance management and optimization of production and process plants. DDV offers free membership to students, helping them stay connected to the industry and providing them access to a vast network of professionals.
“Our goal is to equip the next generation of maintenance professionals with the knowledge they need to succeed,” says Pedersen.
Meeting the Need for Interdisciplinary Skills
As automation and digitalization transform maintenance, there is a rising demand for professionals with interdisciplinary skills. DDV offers specialized training courses in technologies such as AI, predictive analytics, and digital twins. Their Machine Learning/AI network focuses on predictive maintenance, helping members reduce downtime and costs.
“The future of maintenance is deeply tied to digitalization, says Mosegaard.”
“Our members are increasingly interested in exploring the potential of AI and predictive analytics to enhance operations and prevent unexpected breakdowns.”
Sustainability and Climate Goals
Sustainability is a key focus for DDV, with the organization helping members adopt energy optimization, circularity, and sustainable repair practices. DDV encourages its members to align with the United Nations’ Sustainable Development Goals (SDGs), including those focused on clean energy, responsible consumption, and innovation.
“Sustainability is not just a trend; it’s a necessity,” says Pedersen.
Innovations Shaping the Future of Maintenance
Predictive analytics, AI, and machine learning are transforming the future of maintenance in Denmark. These technologies enable organizations to monitor equipment in real-time, predict potential failures, and optimize maintenance schedules. While still a relatively new area for many DDV members, there is growing interest in these innovations.
DDV has established a network focused on Machine Learning/AI, where members can explore the application of these technologies in maintenance. Events and workshops in this network have been met with great success, and the demand for knowledge in this field continues to grow. Additionally, DDV works to keep its members informed about global trends and technological developments through its online platform, OPTIMERING.NU, which shares relevant case studies and insights.

“AI and predictive analytics are still emerging fields in the maintenance sector, but the demand for knowledge is increasing,” says Mosegaard.
“We are excited to help our members stay informed and explore how these technologies can help them improve their operations.”
Staying Updated with Global Trends and Standards
DDV ensures its members stay aligned with global trends and standards, contributing to the translation of international maintenance standards through Dansk Standard. The organization also organizes workshops on Maintenance KPIs to help professionals stay competitive globally.
“By staying updated on global trends and standards, our members can ensure their practices align with the latest industry developments,” says Pedersen.
“This is key to maintaining high performance and competitiveness on the global stage.”
Vision for the Future
Looking ahead, DDV’s vision centers on innovation, collaboration, and sustainability. It aims to maximize asset reliability, optimize resources, and contribute to Denmark’s circular economy. DDV’s leadership believes proactive maintenance will continue to drive value for businesses and help position Denmark as a global leader in maintenance.
“We believe proactive maintenance will continue to drive value for organizations,” says Mosegaard.
As DDV fosters collaboration, the Danish maintenance sector is set to remain at the forefront of innovation and sustainability.
Jesper Pedersen,
DDV Chairman, Principal Engineer at Vattenfall
“Networking is an important part of my daily work. Through a professional network, knowledge and skills are developed and can be used both personally and professionally. I participate in the development of the DDV Analysis, and I am also a member of the editorial board of the book Vedligehold, participating also as an instructor in DDV courses and facilitating several networks.”
Eva Mosegaard,
Text: Nina Garlo Photos: The Danish Maintenance Society
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Smart Welding Revolution
As industries worldwide grapple with the shortage of skilled welders, automation is stepping in to bridge the gap. Kemppi, a leading innovator in welding technology, is at the forefront of this transformation, working alongside research institutions and industry partners to develop solutions that improve efficiency, quality, and adaptability.
Kemppi’s latest collaborative project involves VTT Technical Research Centre of Finland, Tampere University, and several industrial partners, including Wärtsilä Finland Oyj. The initiative aims to enhance robotic welding and cobot welding to address challenges in automated welding, particularly in low-volume, high-variation production environments.
“One of the key issues in automated welding is ensuring consistent quality while adapting to variations in materials, joint geometries, and positioning errors, says Artturi Salmela, Product Manager for Automation at Kemppi.”
“Through advanced process control and real-time monitoring, we can dynamically optimize welding parameters, reducing errors and improving the overall welding quality.”
Wärtsilä Case: Tackling Large-Scale Welding Challenges
A prime example of this technology in action is Wärtsilä’s production of diesel power plant components. These large, complex structures require precision welding, and achieving high quality with traditional automation has been difficult due to variations in the workpieces. Wärtsilä faced significant challenges with ensuring the structural integrity of massive engine base frames, which require numerous high-quality welds in complex geometries.
The key obstacles:
• Inconsistent workpiece geometry: Large parts had minor but impactful variations, requiring flexible welding approaches.
• High material thickness: Thick metal structures demanded precise heat input and deep penetration welding techniques.
• Quality assurance: Maintaining uniform quality across vast surfaces while minimizing rework and production delays.
To address these, the project implemented real-time seam tracking and adaptive welding control, improving consistency and reducing manual intervention. Additionally, advanced welding cameras, such as those developed by Cavitar Oy, enabled defect detection and process monitoring, ensuring precise execution. These enhancements led to higher efficiency and significant reductions in welding errors.
“The project has already delivered promising results, particularly in seam tracking and AI-assisted welding quality monitoring, Salmela notes.”

“We’ve successfully reduced error rates and improved welding precision. Moving forward, we will continue refining the AI-based welding control and further integrate cobot solutions to enhance flexibility and efficiency in complex welding tasks. The goal is to develop a robust, scalable automation framework that can be implemented across different industrial applications.”
What is cobot welding?
Cobot welding refers to the use of collaborative robots (cobots) in welding applications. Unlike traditional industrial welding robots, which operate in isolated automated cells, cobots are designed to work alongside human welders. These robots assist in welding tasks by automating repetitive actions, enabling increased efficiency and precision while allowing human welders to focus on more intricate work. Cobots are typically lightweight, easy to program, and adaptable to various production needs, making them an ideal solution for manufacturers looking to enhance productivity without fully replacing skilled labor.
Enhancing human and machine collaboration
A breakthrough in welding automation has been the adoption of collaborative robots (cobots). Unlike traditional industrial robots, cobots work alongside human welders, handling repetitive tasks while allowing skilled workers to focus on complex, high-value welds.
Kemppi’s cobot welding solutions offer several key benefits:
• Improved productivity: Cobots assist welders by automating monotonous welding tasks, increasing overall output.
• Flexibility: Unlike fully automated welding cells, cobots can be easily reprogrammed for different tasks, making them ideal for dynamic manufacturing environments.
• Ease of use: Cobots are designed with intuitive interfaces, allowing welders with minimal automation experience to operate them effectively.
• Enhanced ergonomics: By reducing the need for welders to perform physically demanding and repetitive tasks, cobots improve workplace conditions and reduce strain-related injuries.

One successful implementation of cobot welding has been in manufacturing components for heavy industry, where parts are often large and require multiple welding passes. By using cobots, manufacturers have been able to achieve greater consistency while reducing fatigue-related errors among welders. In Wärtsilä case, cobots have played a crucial role in handling fewer complex welds while human welders focused on more critical joining tasks.
The future of welding automation
The long-term goal of this initiative is to create an ecosystem where automated and collaborative welding solutions coexist efficiently. As robotic welding technology continues to evolve, manufacturers will be able to scale production while maintaining high-quality standards.
“Cobots and robotic welding won’t replace skilled welders entirely, but they will significantly enhance their productivity. By combining human expertise with automation, we can achieve better efficiency, improved quality, and a more sustainable manufacturing process, Salmela concludes.”
Kemppi has already seen success with cobot welding solutions, which have proven to increase efficiency while maintaining high-quality standards. As industry embraces these advancements, the role of automation in welding will only grow, helping manufacturers meet increasing demands with greater flexibility and precision.
Key Facts:
• Project partners: Kemppi, VTT, Tampere University, Wärtsilä, Cavitar Oy, HT Laser, Visual Components
• Focus areas: Cobot welding, robotic welding, real-time quality monitoring, seam tracking
• Key technologies: Collaborative robots, advanced welding cameras, adaptive process control
• Industry impact: Increased efficiency, improved welding quality, reduced reliance on manual labor
• Outlook: Cobot-assisted welding increasing automation while supporting human expertise
Text: Mia Heiskanen
Photos: Kemppi



