In 2025, the volume of data created and consumed worldwide exceeded 180 zettabytes (one zettabyte equals one billion terabytes), and this figure is expected to triple between 2025 and 2029. This global digital explosion has placed data centres at the heart of today’s critical infrastructure. From the perspective of the construction sector, data centres represent one of the most technically specialised building types. It is not simply a matter of erecting a large warehouse filled with equipment: the structure, the building envelope, the electrical installations, the cooling systems and the security controls must all function with almost surgical precision. And increasingly, these buildings must do so in a sustainable manner.
Every time we send an email, check the weather forecast or ask artificial intelligence for help, that request travels to a building that almost no one ever sees. A data centre is not your typical company server at the end of a corridor; it is a highly complex industrial infrastructure, with thousands of servers and a multitude of auxiliary systems. They are designed to store, manage and process vast amounts of data and ensure it is always available, supporting essential digital services: from cloud platforms to artificial intelligence, including banking, public administration and the connected industry.
Types of data centres: they are not all the same
The construction of a data centre varies dramatically depending on its purpose and scale. Designing a facility for an SME is not the same as designing a massive node for a tech giant. A distinction must be made between different types of data centres based on various characteristics:
Classification according to purpose:
On-Premises, built and managed by the company itself for its exclusive use, offering maximum control
Colocation (Colocation),where the provider rents out space, power and security to various companies, enabling them to outsource their infrastructure
Cloud Data Centers, virtualised infrastructure hosted by cloud service providers (e.g. AWS, Azure), designed for scalability and on-demand use
Hybrid, which combine physical infrastructure with cloud services, optimising flexibility and security
Managed services, which are those where the provider not only rents out space, but also actively manages the customer’s infrastructure.
Clasification according to size and capacity:
Hyperscale, which are large-scale facilities designed for massive cloud computing and big data, operated by tech giants (Google, Meta, AWS)
Edge Data Centers, which are smaller, decentralised facilities located close to the end user to reduce latency
Micro Data Centers, which offer compact, often prefabricated solutions for specific requirements or confined spaces.
Classification based on their level of redundancy and guaranteed availability:
This classification is based on the Uptime Institute’s Tier standard, which is the global benchmark.
Clasification
Availability
Redundancy
Typical profile
Tier I
99.671%
No redundancy
SMEs, offices…
Tier II
99.741%
Partial
Medium-sized companies
Tier III
99.982%
Maintenance without downtime
Deployment, cloud region
Tier IV
99.995%
Total, fault-tolerant
Banking, defence, hyperscale
Energy consumption: some staggering figures
One of the most critical aspects of data centres is their high energy consumption. A hyperscale data centre can consume as much electricity as a city of 100,000 inhabitants. Designing them properly is not just a technical matter: it is a collective responsibility. The International Energy Agency (IEA) estimates the annual energy consumption of data centres at around 450 TWh, accounting for almost 2% of global energy consumption. And estimates suggest that this consumption could double by 2030.
The energy efficiency of a data centre is measured using the PUE (Power Usage Effectiveness) metric. A PUE of 1.0 is the theoretical ideal – all the energy goes to the servers – and a PUE of 2.0 means that for every watt of useful power, another watt is spent on cooling, lighting and other auxiliary systems. The industry average is around 1.5, although the best modern centres already achieve figures between 1.1 and 1.2.
PUE (Power Usage Effectivenes) = total energy consumption of the facility / energy consumption of IT equipment
Cooling can account for between 35% and 45% of a building’s total electricity consumption. For this reason, innovation in cooling systems – liquid immersion cooling, two-phase heat exchangers, indirect evaporative cooling systems – is one of the most active areas of research and also one of the fields where we at CARTIF see the greatest potential for technology transfer.
The waste heat from a data centre should not be wasted; it can (and should) be reused for district heating systems or for nearby industrial processes. A data centre can literally act as the boiler for an entire neighbourhood. Recent European projects demonstrate that it is feasible to feed this heat into district heating networks to heat homes and commercial buildings in winter, turning a problem into an energy asset.
Challenges and solutions in data centre construction
From a construction perspective, data centres differ significantly from conventional buildings. Their design is determined by three key factors: availability, security and efficiency. Unlike conventional construction, the building process for a data centre is governed by critical concurrence: civil engineering works and the integration of complex systems (electrical and mechanical) must proceed in perfect synchronisation. The greatest challenges facing this type of specialised construction are:
Structure and floor load: server racks can exceed 1,500 kg/m². Floor slabs must be dimensioned to a much higher standard than in a conventional office building, and the structure as a whole must incorporate robust construction solutions designed to withstand external risks (earthquakes, flooding, fire).
Redundant power supply: dual mains connections, diesel or hydrogen-powered generators, and large-scale UPS (uninterruptible power supply) systems are required to ensure there are no micro-outages. Electrical rooms may occupy up to 30% of the total floor area.
Cooling: this is the major challenge, as the amount of heat generated by the servers is enormous. Systems range from precision air conditioning (CRAC/CRAH) to direct liquid cooling at the rack level, chilled/heated ceilings and free-cooling towers, which utilise outside air.
Physical security: another critical aspect that must include biometric access control, 360° cameras, electromagnetic shielding (Faraday cages), early-warning fire detection systems using aerosol or clean agents that do not damage equipment, and building materials with high REI ratings.
Cable and infrastructure management: raised access floors and suspended ceilings must accommodate kilometres of fibre-optic cables and other wiring, with strict compartmentalisation and redundant routes.
Building envelope and efficiency: it is essential to incorporate highly insulated façades, roofs that minimise solar gain, and a carefully considered orientation to harness prevailing winds for passive free-cooling strategies. Finally, the layout of plant rooms, the building’s orientation, and the integration of passive and active systems must optimise overall energy consumption.
The construction process for a data centre has specific characteristics that set it apart from other types of building projects, primarily due to the need to precisely coordinate multiple disciplines that rarely come together in a single project: heavy-load structural engineering, medium-voltage electrical systems, precision air conditioning, advanced BIM management and monitoring technologies. Following an initial phase of highly detailed planning and design – often supported by BIM methodologies – the construction phase is characterised by a tightly controlled sequence in which civil works and the installation of critical systems proceed in parallel.
Construction usually begins with a robust foundation (foundations and structure) capable of withstanding heavy loads and ensuring stability against vibrations. Subsequently, particular importance is attached to the installation of redundant electrical systems (transformer stations, generator sets, UPS systems) and HVAC systems, the integration of which requires specific technical spaces and extremely precise execution. In the final stages, exhaustive testing (commissioning) is carried out to verify that all systems operate in a coordinated manner under different operational scenarios, which is critical prior to commissioning.
The life cycle of a data centre – from conception through to operation and decommissioning – offers fertile ground for the application of emerging technologies. The following are the most significant from the perspective of construction and facilities engineering:
Digital twins and BIM. The BIM (Building Information Modelling) methodology is now an absolute must for data centre projects. It enables the precise coordination of installations across all disciplines before construction begins, identifying clashes and sequencing the work. The next step is the operational digital twin: a model updated in real time using installed sensors, which enables the simulation of failure scenarios, the optimisation of load distribution, and the management of predictive maintenance.
Industrialised and modular construction. Prefabricated data centre modules help to improve quality and reduce commissioning times. This trend is being adopted by leading data centres as a strategy for rapid scaling.
Artificial intelligence in management and predictive maintenance. State-of-the-art DCIM (Data Centre Infrastructure Management) systems incorporate machine learning algorithms that optimise the operation of cooling equipment in real time, manage load distribution between servers and predict when a component is likely to fail before it does.
Direct Liquid Cooling (DLC). Given the power density of new artificial intelligence processors – which can exceed 400 W per chip – air cooling is simply not enough. DLC systems circulate water or a dielectric fluid directly to the processor via cold plates, shifting heat management to the hydraulic system and enabling that heat to be recovered at usable temperatures.
Renewable energy and hydrogen. Major technology corporations have committed to operating on 100% renewable energy, and many data centres are incorporating rooftop solar photovoltaic systems or using PPAs (Power Purchase Agreements). Green hydrogen is emerging as an alternative to diesel generators for long-duration energy storage, with the first pilot projects already underway in Northern Europe.
The economic impact of data centres: why regions are competing to attract them
The importance of this infrastructure to the economy is undeniable. In Spain, planned investment for this year exceeds €8 billion, with projections reaching €67 billion by the end of the decade. A large data centre is not just a building: it is a major economic catalyst. The construction of a hyperscale centre creates between 400 and 2,000 direct jobs during the construction phase, with high demand for specialist roles such as industrial electricians, HVAC technicians, fibre-optic network installers and BMS (Building Management Systems) operators.
Once up and running, data centres create stable, well-paid jobs – systems technicians, facilities engineers, security operators – and pay electricity bills that make a significant contribution to the revenue of distribution companies and to local tax revenues. Over the last three years, Spain has experienced a wave of investment, particularly in Madrid (which is already one of Europe’s five largest data hubs), but also in regions such as Aragon, Navarre and Galicia, which have set up one-stop shops and introduced favourable electricity tariffs to attract major operators who, in turn, draw in technology companies seeking proximity to the infrastructure. In regions such as Castile and León, with land availability, access to renewable energy and favourable climatic conditions, there is a clear opportunity to attract this type of investment.
From a regional policy perspective, investing in this type of infrastructure contributes directly to the objectives of the European Digital Agenda (Digital Compass 2030) and to technological sovereignty, ensuring that the data of European citizens and businesses is not stored exclusively on infrastructure in third countries.
Opportunities and benefits for businesses and researchers
As we have seen, data centres can offer significant benefits, including the creation of direct jobs during the construction and operational phases, the development of highly advanced energy and telecommunications infrastructure, the attraction of technology companies and start-ups, and, more generally, an increase in regional competitiveness.
The data centre sector opens up numerous business opportunities where collaboration between industry and research centres is particularly valuable:
Specialist technical consultancy. The market is in demand for architects and engineers with specific training in data centres. The shortage of professionals with this profile in Spain presents a real opportunity for firms and consultancies that invest in training and certification.
Research into energy efficiency. Technology centres such as Cartif play a key role in developing and transferring solutions for energy optimisation, waste heat recovery and integration with smart grids.
Advanced building materials and systems. The industry demands high-efficiency building envelopes, water management solutions for evaporative cooling systems, and materials with rigorous environmental certifications (EPD, cradle-to-cradle).
Predictive maintenance and inspection. The use of drones equipped with thermal imaging, inspection robots and AI-based data analysis platforms to predict failures in critical infrastructure is a growing market offering high added value.
Industrial symbiosis with waste heat. Integrating data centres into district heating networks requires systems engineering, planning permissions and innovative business models, which provide fertile ground for applied research.
CARTIF’s role in promoting sustainable data centres
Data centres are, paradoxically, the most influential buildings of our time and, at the same time, the most invisible to the general public. They are built in industrial estates, hidden behind unassuming façades, and only feature in the media when something goes wrong. Yet every internet search, every bank transaction, every video call and every query to an artificial intelligence model passes through them.
At CARTIF, we see these projects as an exciting crossroads: the need to build faster, more efficiently and more sustainably, whilst demand is growing at a rate that defies all forecasts. The decarbonisation of the sector, the smart management of water resources in regions such as Castile and León, and the integration of data centres into the urban and energy fabric of cities are challenges that require precisely the kind of applied research and public-private collaboration that is our raison d’être.
When we enter a cathedral, stroll through a monastery, or visit a castle, we rarely think about everything that is happening “inside” them. We do not see how moisture slowly rises through the walls, how increasingly frequent and abrupt temperature changes generate invisible stresses, or how a millimetric crack can eventually become a striking fissure over time. And yet, that is often where the deterioration of heritage begins.
Preserving our historic buildings is not just about restoring them when a crack appears or cleaning them when a façade looks worn. Above all, it is about anticipation. It means understanding what is happening to them before the problem becomes evident. With this idea in mind, the Comprehensive Intelligent Monitoring and Predictive Risk Assessment Model for Cultural Heritage Assets (MIMER-BIC, Spanish acronym) was developed by the Cultural Heritage Area of CARTIF.
This model is based on something we can all agree on: to know what is happening to someone, we must first listen. And if that “someone” is something as valuable as our historic buildings, listening means measuring. Sensors record temperature, humidity, light (infrared, visible, and ultraviolet), air quality, crack growth, wall inclination, vibrations, the presence of insects that attack wood, the number of visitors, or even potential intrusions. However, the real innovation lies not in placing sensors, but in transforming that data into useful information. The model converts all these measurements into clear indicators and risk indices that, on a simple scale from 0 to 100, reveal whether a building is in a stable condition or requires priority intervention.
MIMER-BIC model graphic representation
Thanks to this methodology, it is possible to detect whether the indoor environment is endangering paintings or altarpieces, whether a structure is undergoing abnormal movements, whether excessive visitor numbers are affecting the microclimate, whether a weather event could accelerate external deterioration, whether a fire is starting, or whether someone has entered a restricted area. The focus is no longer on reacting once damage is visible, but on preventing it in advance and, above all, doing so with sound judgment.
Behind this advancement lie many years of research. The CARTIF team has worked intensively in different technologies such as:
3D surveying
HBIM
Preventive conservation
Structural analysis
Risk modelling
Advanced sensorization
Artificial intelligence applied to heritage
Yet this journey has not been undertaken alone. Close collaboration with companies in the sector (where the role of TRYCSA has been particularly noteworthy) has been key to ensuring that the model did not remain on paper but became a practical reality. Their hands-on experience, technical expertise, and commitment have made it possible to test, refine, and transform the methodological proposal into an effective and applicable tool.
The result is an original model with its own methodology (from the definition of architectural-functional typologies and major families of pathologies to the formulation of synthetic risk indices), protected under intellectual property regulations. This protection is not merely a legal formality: it is recognition that we are facing a pioneering proposal with high scientific and technological value for the heritage conservation sector. A model developed in the region of “Castilla y León”, yet with a clearly global vocation and positioned at the forefront of applied research in cultural heritage.
“We are facing a pioneering proposal with high scientific and technological value for heritage conservation sector”
At a time when climate change, tourism pressure, and limited resources are testing conservation capacities, having tools that enable prioritization, planning, and decision-making based on objective data is more necessary than ever. The MIMER-BIC model represents precisely that: a new way of caring for what belongs to us all, combining expert knowledge, technology, and collaboration between research and industry. Because, in the end, preserving heritage is not only about keeping old buildings standing. It is about protecting stories, memories, and a shared identity. And doing so intelligently today is the best guarantee that they will still be there tomorrow.
We all know that Artificial Intelligence (AI) is being successfully applied in sectors such as medicine, industry, and mobility, where there are millions of data points, images, and models with which to train increasingly accurate algorithms. However, when it comes to Cultural Heritage, the situation is quite different.
Heritage assets (monuments, artworks, archaeological sites, or historical archives, among others) are fragile and, in many cases, irreplaceable. There are no large datasets from which to derive the thousands or millions of examples needed to “feed” an AI system. Each heritage asset has its own architectural, material, conservation, and historical particularities that make it unique. This scarcity of data turns the application of AI techniques, as used in other fields, not only into a challenge but into a real difficulty.
Moreover, even when enough data exists to build a useful knowledge base, there is often reluctance to share it, let alone make it public. In many cases, information about the real state of conservation of an asset, whether movable or immovable, is considered sensitive or confidential. Revealing deterioration, vulnerabilities, or pathologies could have unintended consequences, ranging from legal or security issues to economic or reputational impacts.
Even so, AI can help extract maximum value from the available information by combining data from multiple sources: technical reports, scientific analyses, surveys, 3D models, historical images, or even expert insights.
What is very clear is that, unlike other fields that will be dominated by AI, in Cultural Heritage it will never replace the human expert. Decision-making regarding the conservation or restoration of an asset requires deep contextual knowledge, sensitivity (we’ll talk another day about what this means), ethical judgment, and creativity, qualities that no machine can replicate.
However, what AI can -and inevitably will- do is support specialists: analyzing volumes of information that used to take weeks of work, detecting patterns, or proposing hypotheses about the behavior of materials, artworks, or entire buildings under different scenarios. In short, it can offer professionals an integrated and rapid view that enables them to make more informed decisions.
Looking to the future -which, in the case of Cultural Heritage, always means the long term- as more digital data is generated about heritage assets (3D scans, photogrammetric records, images in various spectral bands and resolutions, chemical analyses, or sensor data for preventive conservation), opportunities will grow. And they will do so exponentially. But always following a fundamental principle: AI is a tool to assist conservation, not a substitute for the human judgment that ensures our cultural legacy remains alive, understandable, and authentic.
CARTIF is already working in this direction alongside organizations that play a key role in the research, protection, conservation, restoration, and dissemination of Cultural Heritage. Projects such as iPhotoCult at the European level -where the applicability of AI to assess the structural integrity of historic timber roof frames inspected by a robotic dog in the Church of Nuestra Señora de la Asunción (Roa, Burgos) as a reference- will be evaluated. Likewise, the recently approved MINERVA project in Spain, which will digitize the processes of technical inspection of historic buildings defined in the previous ITEHIS project (recently presented to the Spanish Standardization Technical Committee for Conservation, Restoration, and Rehabilitation of Buildings), will contribute business and expert knowledge to guide how AI can best be oriented in this field.
There’s a long road ahead, but step by step. Shall we walk it together?”
Beneath the vaults of a Gothic church, within the thick walls of a Cistercian monastery, in the stucco of a Renaissance palace or the rammed earth and timber frames of a traditional house, a single truth emerges: built heritage is an essential part of our history and collective identity. It is a physical legacy made of stone, wood, lime, brick or raw earth, conceived with construction wisdom adapted to its time.
Today, however, many of these buildings are deteriorating, left empty, and, far too often, disappearing without ever having been given a second chance. The lack of contemporary use, societal passivity, the absence of maintenance plans, the associated costs and, above all, something rarely discussed or deliberately overlooked: a technical misunderstanding of how they were built, are accelerating their loss.
Lifecycle of the Monastery of Nuestra Señora del Prado (Valladolid), pilot building of the INHERIT project. Source: own elaboration
How can we preserve what we don´t understand? How can we maintain with sound judgement if we ignore how something was built, why specific materials were used, or what structural logic underlies it? Preventive conservation is not a trend, it is an urgent necesssity if we want to safeguard our cultural heritage with rigour and responsibility.
At CARTIF, we believe it is essential to research and develop technical, innovative, yet realistic and implementable solutions that address this challenge through knowledge and respect for what has already been built. We aim to contribute to asmarter, more useful conservation approach, one that avoids improvisation and standard formulas, and instead promotes a deep understanding of how things were constructed, in order to care for them better. We are convinced that heritage conservation is a collective process: a way of valuing what connects us, engaging citizens, and reinforcing our bond with the built environment.
Projects we have been involved in, such as INHERIT andiPhotoCult, support this vision and underscore the need for a new technological perspective on heritage conservation. We already explored this line of thought in our blog post “A proper approach to inspecting historic buildings”; if you’re interested in digging deeper, we recommend giving it a read.
Why can´t we apply the same criteria userd for contemporary buildings?
Historic buildings do not follow the rules of modern construction. Their materials, lime, brick, stone, wood, earth, are porous, natural, and adapted to local climates and contexts. Their construction systems, load-bearing walls, vaults, timber roof frames, obey a different logic. Assessing them using the same technical criteria as reinforced concrete or steel buildings is not only incorrect, it’s unjust.
We need tools that speak the language of built heritage. A specific approach that values their unique technical nature, because constructive diversity is not a problem, it’s a valuable asset.
A technical proposal for knowledge-based conservation
Today, many diagnostic inspections still rely almost exclusively on the expertise of the technician conducting them. While that professional judgement is valuable, even essential, it becomes insufficient if the data gathered is not structured in a consistent, traceable and useful way for follow-up actions such as maintenance planning, rehabilitation, or risk assessment.
Workflow towards preventive maintenance based on HBIM: from data collection to knowledge. Source: own elaboration
That’s why we believe it is crucial to open the debate and move towards the development of a methodological proposal that addresses the specific needs of this field, through clear technical criteria and a systematic approach that enables us to:
Identify and evaluate historical construction systems according to their own internal logic.
Detect and structure deterioration symptoms by technical domain (foundations, structure, façades, roofs, interior partitions and finishes, metalwork and joinery, accessibility, installations and smart systems).
Assess associated risks, whether physical, functional or environmental.
Generate structured, reusable data that can be connected to digital tools such as H-BIM models or maintenance platforms.
This approach does not aim to simplify through standardisation, but to intelligently unify technical criteria through consensus among professionals, adapting to different contexts and typologies while respecting the architectural and cultural diversity of the built heritage. It remains fully aligned with current regulatory frameworks, such as the UNE 41805 standard for building diagnostics, and takes as a reference the National Preventive Conservation Plan of Spain’s Institute of Cultural Heritage (IPCE).
What are the benefits of a well-designed technical tool?
Adopting a technical methodology adapted to heritage buildings offers tangible benefits for technicians, companies and public administrations alike:
Reduced medium- and long-term costs by avoiding emergency interventions.
Greater transparency and traceability through structured, comparable data across buildings.
Enhanced appreciation of traditional technical knowledge, acknowledging the logic and effectiveness of historic systems and materials, while also addressing professional niches that currently lack recognition.
Real support for decision-making without replacing professional judgement.
Seamless integration with digital models and H-BIM platforms to plan maintenance, evaluate deterioration risks, monitor material ageing or assess energy performance (when appropriate).
These tools are key to achieving a more useful and proactive form of management, enabling better planning, fewer interventions, and more effective conservation, helping us move towards sustainable, resilient, resource-efficient and ultimately cost-effective heritage.
Looking ahead: meaningful digitalisation
The potential of this approach does not end with inspection or diagnostics. It opens the door to digital tools capable of integrating 3D models, geolocated imagery, environmental or structural sensors, and lesion monitoring systems, or even AI-based tools capable of predicting deterioration patterns.
Workflow applied to the former collegiate church of Nuestra Señora de la Asunción in Roa (iPhotoCult project), with data acquisition using a ground-based robotic platforma (UGV). Source: own elaboration
But none of this will be useful without a solid foundation: reliable, technically sound and well-structured data. Because technology alone doesn’t preserve buildings. It’s people, with sound judgement, supported by tools that respect and understand what has been built.
Built heritage is not merely a collection of old stones. It is a living expression of our identity, our way of inhabiting space, our craftsmanship, our decisions and our memory. And today, more than ever, preserving it is a way of taking care of ourselves as a society.
Rural territories often struggle with challenges that can hold back their growth and development. Infrastructure gaps, limited job opportunities, environmental risks, and the need for greater social inclusion are just some of the issues they face. However, they now have the chance to take control of their future and actively shape a more sustainable and thriving community, through the RURACTIVE project that CARTIF’s Heritage Area is part of.
A significant tool provided by RURACTIVE is the Adaptive Monitoring Programme. This is not just about collecting data – it is about understanding the rural territories reality and ensuring that the solutions they implement truly benefit their region in the long run.
A clear picture of where they stand
Before Dynamos (the regional units of the project) can plan for a better future, they need to understand where they stand today. That is exactly what the Dynamo Baseline does. It provides a snapshot of a rural territory’s social, economic, environmental, and cultural conditions. With 136 key indicators, they can finally see the full picture of their strengths and challenges, from employment trends to biodiversity levels. This baseline is not a one-size-fits-all approach – it is tailored to a specific situation. It helps rural territories compare their progress with regional, national, and even European benchmarks, ensuring that they are aligned with broader development goals.
A smarter way to identify and solve problems
The Monitoring Programme allows us to go beyond just identifying problems. It helps us track their evolution and detect early warning signs before they become serious crises. The Early Warning Indicators (EWIs) play a crucial role in this, giving us the ability to act before issues like economic decline or environmental degradation get out of control.
By continuously refining our list of indicators and including new, relevant ones, we ensure that the monitoring system remains flexible and adaptive. This means that as a region evolves, its ability to respond to new challenges also improves.
Empowering communities with data and knowledge
A major advantage of participating in RURACTIVE is that rural territories are not alone in this process. Through the RURACTIVE Digital Hub, Dynamos have access to a shared platform where they can visualize and analyse all collected data. This not only makes progress more transparent but also helps local leaders and citizens actively participate in shaping development strategies.
Moreover, the project encourages a participatory approach, meaning that community members, local businesses, and organizations all have a voice in defining priorities and evaluating progress. By engaging with this programme, rural territories gain stronger decision-making power based on real, measurable evidence.
Fig 1. Adaptive monitoring programme
The Figure shows the whole process when a Dynamo gets to the RURACTIVE Ecosystem and the Adaptive Monitoring Programme is applied. First, a complete baseline is developed describing the Dynamo’s current situation, based on the values of the Key Rural Empowerment Indicators (KREI). This modular baseline includes an extensive list of available indicators, but adapts to the specific conditions of the Dynamo being analysed. With the collected information a Dynamo situation diagnosis is elaborated, helping to identify the challenges and define the possible solutions that will be later used in the Local Action Plan (LAP). Next step is to fine tune the list of indicators, or even include new specific indicators adapted to the solutions, and identify which will be the early warning indicators (EWI). The Monitoring Tool manages data collection and processing, supporting the periodic reporting on the LAP evolution and Dynamo’s continuous consultations.
Building a stronger, more resilient dynamo
Joining RURACTIVEand using its monitoring tools is not just about tracking numbers -it is about transforming a region into a place that is more connected, resilient, and prosperous. With a structured, data-driven approach, rural territories can design strategies that truly work for them, ensuring that innovation, sustainability, and inclusion are at the heart of their development.
For a Dynamo, this is not just another project – it is an opportunity to take charge of its progress, backed by knowledge, collaboration, and cutting-edge tools.
Co-author
Maya Tasis. Graduated in Technical Industrial Mechanical Engineering by the Oviedo Unviersity. She has experience in the challenging sector of automotion, coordinating industrial works, international projects and management of multidisciplinar equipment. Researcher at CARTIF, where she collaborates in international projects of improvement of industrial processes and projects of the Natural and Cultural Heritage area.
The term eco-design is rather known nowadays, but you’ve probably heard little about eco-manufacturing, especially since it’s not a term widely recognized in technical or academic literature. However, it is a concept that has recently started to be used to describe manufacturing practices that centrally incorporate environmental aspects. Well, I’ll go even further, and try to explain what “metal-eco-additive manufacturing” is, a term I just invented to title this.
Forty years ago, Charles Hull’s invention of stereolithography (SLA) gave rise to what we now know as 3D printing – or additive manufacturing. Going one step further, the concept of metal 3D printing emerged after decades of development and experimentation, though its ideation can be attributed to Carl Deckard, a pioneer in Selective Laser Sintering (SLS) about 30 years ago at the University of Texas. Far from its industrial application at the time, its development went hand in hand with advances in new materials and high-power lasers in the 2000s. Although many have heard of processes for metal 3D printing, such as Selective Laser Melting (SLM) or Electron Beam Melting (EBM), it’s worth noting that the technology took 10 more years to reach large-scale industrial production – not just prototypes, as was done during the development phase for sectors like aerospace, automotive, or medical (which had the money for such “toys”).
Over the past 15 years, metal 3D printing processes have significantly improved (in precision, resolution, speed, physical properties, quality control, etc.), largely due to the emergence of new materials and their characteristics. On the other hand, methodologies have been created to analyze the efficiency of manufacturing processes themselves, parametric control, automation, and robotics, which directly impact costs, thus enabling the expansion of metal 3D printing applications to other sectors. Currently, these enhanced processes include, for example, Powder Bed Fusion (PBF), Direct Energy Deposition (DED), and metal Binder Jetting.
Well, the thing with additive manufacturing is like any technological process – progress is unstoppable: we don’t make airplanes the same way we did 120 years ago, right? 120 years ago, flying was already a reality (12 seconds and 36.5 meters), but I doubt we would agree to define “flying” the way the Wright brothers did in 1903. Their goal was “simply” to fly and survive. I don’t think they could have imagined that their scientific curiosity would become a key pillar of the global economy, nor did they think about 600-passenger airplanes, certifications governing the industry, or the pervasive existence of spaces for takeoff and landing.
In the same way, Carl Deckard, beyond his scientific interest in mechanical engineering, probably didn’t envision changing the world with his invention. However, just as air transport did, the additive manufacturing of metal parts has had, has, and will continue to have a massive impact globally. We now have new rules of the game and manufacturing possibilities for designs that were impossible until recently (generative designs), as their economic and environmental costs were prohibitive and bordering on madness. For example, if you don’t know how an airplane turbine is made (at least what it’s made from or how long it takes!!), you can’t appreciate the madness I’m referring to… and there are more and more airplanes every day!
Ecological awareness (so necessary today), the challenge ahead, and the transition to sustainability, will drive the circular economy in the use of metal additive manufacturing (or 3D printing). Or could it be additive manufacturing that will foster environmental sustainability? Or maybe a “virtuous loop” could be created where both fields will feed back into each other, by means of new concepts such as the one that I am coining here as metal-eco-additive manufacturing?
Simulation with lego of a metal-eco-additive-manufacturing laboratory. Author: Norberto Ibán Lorenzana
The thing is that everything evolves and new challenges arise; it won’t be enough just to design landing gears that fulfill their mission: apart from ensuring no one dies, they must be competitive. We must (and will be required to) know they were created in the most sustainable way possible and under circularity criteria. How? Well, looking towards the future, let’s imagine that the manufacturing conditions for a structurally responsible part could combine several manufacturing processes, not just one (machining) or the other (additive). Let’s also imagine that we could make parts that, although they could have inadequate finishes due to faster processes, these could be corrected in later treatments with techniques that require less effort. Or even, imagine that, if a part fails, we could refurbish it directly: that is, print what is missing on the same part so that the company using it can repair it in their own facilities. We wouldn’t have to throw away the part! Nor make a new one! We would avoid inventories of parts, storage, or transport of those spare parts, which is highly undesirable…
Well, the combination of additive manufacturing and circularity has a synergy point that will be researched and implemented over the next 4 years through a European project called DIAMETER, which involves more than 20 prestigious entities from 4 different continents.CARTIFis just one of these privileged entities that have already started working to build a bridge between metal additive manufacturing and the circular economy.
This bridge will be a framework where a series of metal parts used in critical cases across various production sectors will be analyzed, manufactured by different additive manufacturing processes. In DIAMETER, experimental physical results from the manufacturing processes will be compared with computational simulations of the parts in these processes to predict how the parts will respond to different process modifications. These responses (in terms of stress/deformation, among others) will provide mechanical knowledge about the parts and processes in terms of failures, waste, quality, or the need to integrate post-processing (hybrid manufacturing combining additive and subtractive). In short, a combination of possible scenarios and results that must be transformed into quantifiable outcomes under a sustainability approach to feed into an artificial intelligence system that will provide automated, optimal decisions on procedures and configurations in metal additive manufacturing of parts.
“Feed into an artificial intelligence system that will provide automated, optimal decisions”
“One moment, this is crazy!”
Well, yes, it’s as crazy as machining a 3m³ block of stainless steel on a 6-axis lathe for a week to get an airplane turbine or a hydraulic turbine. Or, seen another way, 500K€ for a week, with the possibility that, if there are errors, the turbine might need to be thrown away and start over from scratch.
But let’s take it step by step. The first thing will be to characterize these manufacturing processes, see how the parts are generated and whether they suffer deviations, inaccuracies, or analyze the quality of the surface itself. For this, artificial vision technology for geometric verification of parts during the manufacturing process will be used, which are technologies in which CARTIF has been working 30 years… and we have much ahead to go in the future!
Co-author
Iñaki Fernández Pérez. PhD in Artificial Intelligence. Researcher at the Health and Wellnes area at CARTIF. He is currently collaborating on several projects that seek to apply cutting-edge technologies (AI, IoT, Edge Computing…).
