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Digital Twin Technology

Digital Twin technology – via a virtual or augmented model of a physical ‘thing’ – gives us an exact, dynamic replication of a building, asset, product, process or system that exists (or is going to exist) in the real world. By using data from sensors on an entity we want to monitor or analyse, the twin gives us an interactive view which lets us monitor metrics that have a key bearing on performance. It also provides invaluable intelligence when it comes to predicting and pre-empting faults before they occur. 

While traditional models simply aid design and give us a copy of the property we’re proposing or building, a digital twin employs Internet of Things methodology to give us real time, real world insight – with ‘rich replication’ driven by live data rather than a static simulation built on limited dimensions or assumptions. The twin is constantly cloud-connected to IoT, SCADA, weather and other market data sources, which means it effectively self-evolves and becomes a living environment that we can use, test and assess for decision-making and collaboration indefinitely.​

What exactly is a digital twin?

A digital twin creates a virtual model that mirrors a physical object. By replicating an asset with a BIM environment that is sync’d with real time data from the real-world entity or system via sensors, we can monitor what is happening now, and predict what may happen in the future via simulation utilising AI and machine learning.

A digital twin allows us to carbon-copy wind turbines, buildings, and even multiple machinery components to stress-test and hypothesise throughout the lifecycle of the built environment we are designing or managing. This allows us to challenge ideas without making costly and time-consuming physical changes, and carry out accurate predictive analysis to mitigate operational risk and maintain optimum performance – while carrying out theoretical and remote troubleshooting when necessary to minimise or eliminate downtime.

By building a twin that’s plugged into past and present data future data our teams and clients can ultimately glean a complete picture of an asset from historical, real-time and AI learning respectively – understanding not only how something currently performs, but also how it might behave in the future.

Use cases for digital twins

  • Stress-test hypothetical ideas and assumptions – eliminate costly or time-consuming physical iteration
  • Carry out predictive maintenance on equipment, production lines, and facilities
  • Monitor assets or buildings to explore staff, resident, visitor or customers behaviour
  • Optimise manufacturing processes and workflow
  • Improve asset or system auditing
  • Promote integration between currently disconnected systems
  • Remotely troubleshoot equipment

Benefits of digital twinning

Design & concept stage

  • Streamlines ideation
  • Allows early feasibility/viability interrogation
  • Accelerates risk assessment
  • Enables testing of multiple hypotheses without physical prototyping
  • Enhances stakeholder engagement
  • Promotes closer, more immersive collaboration

Development & Manufacturing

  • CapEx savings
  • Reduced supply chain losses
  • Lower inventory costs
  • Improved quality control
  • Better productivity & agility
  • Minimises defects and waste
  • Improved safety & security

Operation & Maintenance

  • Reduced physical work (and associated costs)
  • Minimal service/support requirements
  • Optimises planned maintenance schedules
  • Cut physical troubleshooting & downtime
  • Digital audit trailing
  • Simplified remote training

While the concept of Digital Twin technology is generally ‘uniform’ at its core, its application can and does vary from case to case. At Sweco, our digital leaders, built environment experts and infrastructure specialists are constantly engaging with clients to interrogate and shape the opportunities it can unlock. To discuss transformational digital methodology with us, please get in touch below.

 

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