Digital twin technology has evolved from a static design visualisation tool into a full life cycle asset intelligence platform, according to technology professionals, who say the technology can help reduce delays and cost overruns on major infrastructure projects.
Major capital works such as transport corridors, water treatment facilities and smart city backbone systems routinely exceed budget and fall behind schedule, says Johan Potgieter, cluster industrial software lead at Schneider Electric.
Potgieter says digital twin technology, having matured over the past three years, can address budget and deadline issues.
“Unlike earlier generations of digital twins that were largely confined to design visualisation, today's platforms create physics-based, behavioural models that remain connected to live operational data throughout the asset life cycle.”
The shift towards full life cycle asset intelligence has been driven by several developments, says Potgieter. “Sensors and connectivity have become more affordable, allowing real-time operational data to be captured. Edge and cloud computing have also advanced, making it possible to combine live data with advanced simulations.”
He says a physics-based behavioural model simulates how an asset performs under operating conditions rather than simply showing its appearance.
“A physics-based behavioural model does more than show what an asset looks like – it simulates how it behaves. It accounts for real-world factors such as pressure, temperature, electrical load, flow and mechanical stress, allowing engineers to test scenarios before making changes to the physical asset. A simple comparison is the difference between a photograph of an aircraft and a flight simulator. A photograph shows the aircraft, but a simulator behaves enough like the real thing to help test decisions,” Potgieter adds.
He continues: “Being connected to live operational data means the digital model continues to update after the asset is built. Sensors on the physical equipment provide real-time information, keeping the digital version aligned with actual performance. Together, these capabilities create a living digital representation that helps organisations understand how assets are performing, predict issues and make better operational decisions throughout their life cycle.”
He points to commissioning as one area where digital twins can drive project delivery.
“The traditional commissioning model is linear and sequential. Design is completed, equipment is installed, and then the testing begins. And this is when the problems start to surface. Virtual commissioning and resultant digital twins invert this logic entirely. By constructing a high-fidelity digital replica of the physical asset prior to construction, engineering teams can validate control logic, test failure scenarios and identify integration conflicts before a single cable is pulled,” says Potgieter.
He says moving testing and risk mitigation into the pre-construction phase allows design changes to be made in software rather than during physical commissioning, reducing the cost of correcting problems.
Obsolete models
Mark Walker, director at technology consultancy T4i, says digital models previously became obsolete once construction or manufacturing was complete.
“Today, a mature digital twin acts as an active data layer that survives the entire life cycle of the asset. Instead of just showing what an asset looks like, it actively uses machine learning and physics simulations to predict how the asset will behave under stress, when it will fail and how to optimise its yield,” adds Walker.
He says the technology also changes the economics of infrastructure projects.
“Moving from simple 3D visualisation to a full life cycle intelligence platform changes the financial model entirely. It shifts expenditures from a one-off project cost to an ongoing operational expense, and it structurally alters project risk. However, locally, the upfront cost profile is heavily impacted by the localised engineering skills shortage and the fact that major platform software is priced in foreign currency, exposing local budgets to exchange rate volatility.”
Walker says digital twins can also improve co-ordination during project planning.
“Virtual commissioning and stakeholder alignment in a complex environment is very difficult due to different technical languages and specifications. Digital twins address this directly by creating a single, interactive 'source of truth' – before any physical assets are ordered or steel is cut. Systems engineers can test their actual PLC (programmable logic controller) automation code against a high-fidelity virtual model of the physical machinery.”
Should disputes arise between the software vendor and a mechanical contractor about why a system is not hitting throughput targets, the shared simulation sandbox acts as an unbiased testing ground to isolate and prove where the bottleneck sits, Walker adds.
Potgieter concludes: “Digital twins will not solve the financial constraints that shape infrastructure delivery. However, they will substantially reduce the technical and operational risk that compounds those constraints into failure, and that is a meaningful contribution.”
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