Digital Twin Genie was deployed across 28 offshore oil rigs to reduce downtime, improve monitoring efficiency, and significantly enhance worker safety. By replacing manual supervision with a fully connected digital environment, engineers gained real-time visibility into rig performance, friction levels, failure conditions, and workplace dynamics. Within 17 days, the project delivered a functional system-wide digital twin with sensor-driven diagnostics, centralized dashboards, and predictive insights. This approach lowered downtime to 3% and reduced workplace accidents by 31%, demonstrating the value of digital twins in high-risk industrial environments.

Managing large fleets of oil rigs is both capital-intensive and operationally demanding. After adding seven new rigs to an existing fleet—raising total extraction capacity by 1,500 barrels per day—the client faced rising monitoring requirements and depleted capital funds. Manual supervision of 28 rigs was no longer cost-efficient, scalable, or safe. Digital Twin Genie was introduced to automate monitoring, improve transparency, and enhance safety conditions across the site.

The implementation was completed in just 17 days, including the period needed for initial data accumulation. Motion, proximity, friction, and damage sensors were deployed across all rigs and connected to Digital Twin Genie’s development kit. Data aggregation began within 24 hours, feeding a centralised dashboard that provided 24/7 visual access to rig health, operational performance, and environmental conditions.

A detailed digital replica of the entire extraction site was constructed, enabling engineers to monitor all rigs collectively or isolate individual assets to investigate anomalies. Shared intelligence connected all 28 rigs into a single system twin, with real-time data synchronised at 0.4578-second accuracy. This allowed rapid detection of pressure anomalies, equipment wear, and failure risks—capabilities that manual supervision could not provide.

The shift to predictive monitoring produced measurable results. Average downtime across all rigs dropped to 3%, far surpassing the initial goal of reducing downtime to 19%. Additionally, improved visibility into environmental hazards and equipment conditions led to a 31% decrease in annual workplace accidents. Full clarity on operational workflows also supported smarter maintenance planning and reduced unnecessary technician interventions.

Digital Twin Genie’s application demonstrates the transformational value of system-wide twins in the oil and gas sector. By merging equipment data, environmental modeling, and predictive analytics into one platform, operators can safely scale production, maintain high asset uptime, and significantly reduce risk in complex industrial environments.

<p><a href="https://www.challenge.org/knowledgeitems/digital-twins-optimising-oil-fields/" target="_blank">https://www.challenge.org/knowledgeitems/digital-twins-optimising-oil-fields/</a></p><p><a href="https://pdfs.semanticscholar.org/28de/85a9a081ca4e7ccbc0fa6a1a82dec8422665.pdf" target="_blank">https://pdfs.semanticscholar.org/28de/85a9a081ca4e7ccbc0fa6a1a82dec8422665.pdf</a></p><p>https://www.researchgate.net/publication/386387884_Digital_Twins_in_the_Upstream_Oil_and_Gas_Industry_Trends_Applications_and_Challenges</p>

EPLAN enables manufacturers to create digital twins of electrical control cabinets and wiring harnesses using its Pro Panel and Harness proD platforms. These 3D digital models integrate component placement, wiring paths, thermal behavior, and manufacturing specifications—providing a complete, engineering-grade representation of the final product. The digital twin improves panel design accuracy, reduces manual rework, accelerates production, and serves as the backbone for automated cable routing, documentation, and downstream manufacturing processes. It is widely used by machine builders, panel manufacturers, and system integrators to modernize electrical engineering workflows.

Facing the dual challenge of ageing infrastructure and the energy transition, distribution-grid operators like naturenergie netze have turned to digital twin technology to accelerate substation modernisation. In collaboration with EPLAN and entegra, naturenergie netze used a pilot substation in Rheinfelden, Germany, to model both its primary equipment (transformers, switchgear) and its secondary control systems (relays, automation) in a single virtual twin. 

The project began with detailed 3D scans of the physical substation, high-resolution photography of asset nameplates, and extraction of asset-management system data. These inputs fed a primtech model for the primary system which was then automatically exported to EPLAN for the secondary-system design. The unified twin serves as a “single source of truth”, linking engineering, procurement, asset-management and maintenance functions. 

Rather than planning on a case-by-case basis, the twin enables standardisation of substation modules and streamlines engineering workflows, cutting what traditionally took two to three years into months. Users can visualise primary and secondary equipment interactions, simulate upgrades while live operation continues, and plan replacement of control-system components without interrupting service. 

Beyond time savings, the twin creates efficiencies through avoiding data duplication, reducing engineering errors, and enabling better procurement and maintenance planning. The architecture emphasises “different views of the same model” rather than separate leading systems, thereby enabling multiple stakeholders (CAD, SAP, asset management) to access one central digital model. 

As grid operators prepare for increasing decentralised generation, two-way flows, and the need for flexible assets, EPLAN’s transformer-substation twin provides a blueprint for digitising one of the most challenging environments in energy infrastructure. The pilot demonstrates how utilities can respond to modern demands on the grid faster, smarter and more flexibly.

<p><a href="https://thevoltpost.com/eplan-entegra-digital-twin-transformer-substations/" target="_blank">https://thevoltpost.com/eplan-entegra-digital-twin-transformer-substations/</a></p><p><a href="https://discover.eplan.ch/whitepaper-elektrisiert-der-digitale-zwilling#" target="_blank">https://discover.eplan.ch/whitepaper-elektrisiert-der-digitale-zwilling#</a></p><p><a href="https://www.eplan.com/de-de/ueber-uns/standorte/europe/germany/headquarter-monheim" target="_blank">https://www.eplan.com/de-de/ueber-uns/standorte/europe/germany/headquarter-monheim</a></p><p>https://www.eprmagazine.com/special-report/digital-revolution-in-transformer-substations/</p>

Kaeser Kompressoren, a German air-compressor manufacturer founded in 1948, has transformed its business model by building digital twins of its compressor systems. These virtual replicas capture real-time operating data—pressure, flow, energy usage, vibration, and component health—enabling predictive maintenance and reducing unplanned downtime. The insights generated by the digital twin also support Kaeser’s innovative “air-as-a-service” subscription model, where customers pay for compressed air rather than owning equipment. Digital simulation further enhances the company’s configure–price–quote (CPQ) process, ensuring technically verified, cost-optimized, customer-specific solutions.

Kaeser began its journey in the air-compressor market shortly after World War II, identifying rapidly growing industrial demand for reliable compressed air. Seventy years later, the company again redefined its industry by embracing digital twins to modernize equipment operations and reinvent how compressed air is sold.

Kaeser developed detailed product-level digital twins for its smart compressor stations. Each twin mirrors the behavior of its real counterpart using sensor data streamed continuously to Kaeser’s data center. This enables precise tracking of machine conditions and early detection of deviations that could lead to breakdowns. As a result, maintenance teams can intervene before a failure occurs, significantly increasing system uptime—reaching reported levels as high as 99.987%.

The predictive insight generated by these twins became the foundation for Kaeser’s subscription-based service model, “air as a service.” Instead of purchasing compressors, customers subscribe to compressed air at a monthly rate, with Kaeser retaining ownership of the equipment and providing installation, monitoring, and maintenance. This relieves customers of both capital expenditure and the risk of mistimed repairs, while allowing Kaeser to optimize service schedules and component lifecycles based on real operating data.

Digital twins also play a key role in Kaeser’s configure–price–quote (CPQ) process. Engineering simulations validate custom configurations, explore performance-cost trade-offs, and ensure that proposed solutions meet customer requirements without eroding margins. The ability to test scenarios virtually—before building or installing anything—streamlines the sales funnel and enhances product quality over time.

Kaeser’s approach demonstrates how digital twins can span the entire product lifecycle: from design and configuration, to real-time operations, to service-driven business models. By combining predictive maintenance with a subscription offering, Kaeser has created a resilient, profitable service ecosystem built on data-driven reliability and continuous optimization.

<p><a href="https://us.kaeser.com/services/compressed-air-as-utility-service/" target="_blank">https://us.kaeser.com/services/compressed-air-as-utility-service/</a></p><p><a href="https://nz.kaeser.com/company/press/press-releases/n-complete-connectivity.aspx" target="_blank">https://nz.kaeser.com/company/press/press-releases/n-complete-connectivity.aspx</a></p><p>Image:&nbsp;https://www.itransition.com/blog/digital-twin-manufacturing</p>

The island nation of Tuvalu is building a national-scale digital twin to confront an existential climate threat. With sea levels rising 1.5 times faster than the global average, Tuvalu could see much of its territory submerged by mid-century. As part of its “Future Now” initiative, the government is digitizing islands, cultural artifacts, and administrative systems to preserve national identity and ensure continuity in the event of displacement. The first proof-of-concept—the islet of Te Afualiku—was fully mapped using drone imagery and citizen-supplied photos during the pandemic. The evolving digital twin will help model climate impacts, support long-term planning, and create a virtual homeland accessible through VR.

Tuvalu, comprising 124 small islands and islets scattered across the South Pacific, is among the world’s most climate-vulnerable nations. Much of its land lies only a few meters above sea level, leaving the country exposed to accelerating sea-level rise, tidal surges, and extreme weather. A major king tide in 2024 demonstrated the fragility of its infrastructure, flooding parts of the capital Funafuti, severing power, and delaying the formation of a new government. For Tuvalu, climate adaptation has become a matter of national survival.

To address this, the government launched the Future Now initiative, a multi-layered digital strategy that includes the creation of a national digital twin. The project aims to digitally replicate Tuvalu’s islands and cultural assets, effectively creating a “Digital Ark” that preserves heritage even as the physical environment becomes increasingly threatened. The first step in this effort was digitizing Te Afualiku—predicted to be among the first islands lost to rising seas—using drone mapping and citizen-generated imagery during COVID-19 lockdowns.

Tuvalu plans to map and model the remaining islands using a similar approach. These digital versions will be viewable online and through VR headsets, allowing Tuvaluans to interact with their land and heritage regardless of future physical displacement. While early-stage and primarily descriptive, the twin will also support informative climate simulations, helping leaders understand how sea-level rise will affect settlements, infrastructure, and safe-habitable zones over time.

Tuvaluan officials stress the project’s role in preparing for worst-case scenarios. As Foreign Minister Simon Kofe noted, scientists warn the islands may be fully submerged within decades—making digital preservation essential for cultural continuity, legal identity, and international representation.

As more environmental, geospatial, and socio-economic data layers are integrated, Tuvalu’s digital twin could become a model for how small nations use digital continuity to strengthen resilience in the face of global climate change.

<p><a href="https://zenodo.org/records/8069320" target="_blank">https://www.bbc.com/future/article/20241121-tuvalu-the-pacific-islands-creating-a-digital-nation-in-the-metaverse-due-to-climate-change</a></p><p><a href="https://zenodo.org/records/8069320" target="_blank">https://zenodo.org/records/8069320</a></p><p>https://connectsci.au/news/pages/cosmos-archive</p>

Thames Water is developing a digital twin of its extensive water supply network to tackle one of the UK’s largest infrastructure challenges: leakage. The network spans 13,000 square kilometers and serves 15 million people, yet nearly a quarter of the daily 2.6 billion liters of water is lost before it reaches customers. By combining sensor data, smart meters, acoustic loggers, and GIS asset information, Thames Water is building a predictive leak-detection system that identifies hidden failures, simulates repair actions, and provides early-warning insights. The pilot already demonstrates significant water-saving potential and is set to shape future industry standards.

Thames Water operates one of Europe’s largest and oldest water distribution networks. While some leaks are visible at the surface, the overwhelming majority—around 95%—are hidden underground and caused by factors such as aging pipes, pressure fluctuations, soil movement, temperature swings, and traffic loads. These invisible failures contribute to nearly a quarter of total water loss, representing millions of liters lost daily.

To address this persistent challenge, Thames Water is building a digital twin of its entire water supply system. This System Twin integrates data streams from smart meters, acoustic sensors that “listen” for leaks, pressure monitors, and geospatial asset records. By gathering these signals into a unified Digital Shadow, the company can detect anomalies earlier, assess risk hotspots, and visualize system vulnerabilities. The digital twin is one of several applications feeding into Thames Water’s broader system-risk visualization tool, which managers use to evaluate performance and prioritize interventions.

A pilot in Deptford, South London, demonstrated the system’s value. The digital replica successfully identified leaks caused by high pressure and valve degradation. By simulating various repair strategies, the twin also helped operators choose more effective solutions—saving an estimated one million liters of water per day. Thames Water expects the approach to reduce repair costs, shorten response times, and improve long-term resilience of the network.

Beyond leakage detection, the twin will support decision-making for pressure management, asset reliability, and emergency planning. Insights from this project will also contribute to developing industry-wide digital twin standards in collaboration with partners and UK water regulators. Post-project benefit tracking and wider deployment activities are planned for 2025, marking a path toward a fully data-driven future in water management.

<p><a href="https://smartwatermagazine.com/news/thames-water/thames-water-and-project-partners-awarded-ps15million-drive-innovation" target="_blank">https://smartwatermagazine.com/news/thames-water/thames-water-and-project-partners-awarded-ps15million-drive-innovation</a><a href="https://smartwatermagazine.com/news/thames-water/thames-water-and-project-partners-awarded-ps15million-drive-innovation" target="_blank"></a></p><p>https://www.thameswater.co.uk/about-us/innovation/unlocking-digital-twins</p><p>https://waterinnovation.challenges.org/winners/unlocking-digital-twins/</p><p><a href="https://info.tigergraph.com/graph-ai-summit-helping-solve-prominent-uk-water-and-wastewater-companys-asset-problems" target="_blank">https://info.tigergraph.com/graph-ai-summit-helping-solve-prominent-uk-water-and-wastewater-companys-asset-problems</a></p><p>Image: https://www.hidropolitikakademi.org/en/article/31147/how-digital-twins-are-transforming-water-management-for-a-more-resilient-future</p>

Tata Steel is deploying a digital twin of its novel HIsarna iron-making process at its IJmuiden pilot plant to accelerate sustainable steel production. The twin links real-time thermal and operational data with physics-based models and AI to detect process instabilities, test improvements virtually, and support emission-reduction goals. This initiative exemplifies how older heavy-industries can leap toward digital continuity and decarbonisation through advanced simulation.

The steel industry faces mounting pressure to reduce carbon emissions, with European targets calling for up to 80 – 95 % reduction by 2050. In response, Tata Steel’s European unit developed the HIsarna process: an iron-making method that bypasses sinter and coke production by injecting iron ore and coal directly into a reactor and converting it to liquid iron. Early tests show at least 20 % lower CO₂ emissions compared to conventional blast-furnace routes, and potential reductions of up to 80 % when combined with carbon capture. 

However, the HIsarna process presents significant technical complexity: fluctuations in off-gas composition and thermal behaviour persist, making scaling difficult. To address this, Tata Steel collaborates with the Digital Twin research community to build an advanced process twin of key thermal and sintering steps. This twin assimilates real-time and historical plant data, couples multi-physics models (thermal, fluid, chemical) and uses AI/ML for automated updating of the model’s state. 

In practice, engineers simulate different raw-material mixes, injection profiles and thermal settings in the digital environment to identify weak spots in the physical process and optimise performance before implementing changes onsite. This approach reduces reliance on costly empirical trials, accelerates learning, and aligns with Tata’s ambition of building a large-scale demonstration plant in India following successful pilot validation. 

By treating the process twin as a strategic asset rather than just a monitoring tool, Tata Steel is shifting the paradigm in heavy-industry manufacturing. The twin supports smarter, faster decision-making, advances decarbonisation, and lays the foundation for future autonomous plant operations.

<p><a href="https://www.tatasteel.com/corporate/wealsomaketomorrow/blog/hisarna-a-radical-new-steel-making-process-at-tata-steel-the-tomorrow-series/" target="_blank">https://www.tatasteel.com/corporate/wealsomaketomorrow/blog/hisarna-a-radical-new-steel-making-process-at-tata-steel-the-tomorrow-series/<br></a></p><p><a href="https://www.tatasteel.com/corporate/wealsomaketomorrow/blog/hisarna-a-radical-new-steel-making-process-at-tata-steel-the-tomorrow-series/" target="_blank">https://www.digital-twin-research.nl/research/research-project-2/</a><br><br><a href="https://www.digital-twin-research.nl/research/use-cases/tata-hisarna/" target="_blank">https://www.digital-twin-research.nl/research/use-cases/tata-hisarna/</a><br></p><p>https://products.tatasteelnederland.com/sites/producttsn/files/tata-steel-europe-factsheet-hisarna.pdf<br><br></p>