Digital
Embracing new digital technologies.
What is a digital twin?
A digital twin is a virtual replica of a physical object, process or system, enriched with continuous data. This has many use case scenarios such as improving real-time monitoring, predictive maintenance, performance management, decision-making, transparency and scalability.
The many reasons to use digital twins
Before you begin your digital twin project, you need to decide which type of digital twin best fits your goals. A digital twin can be useful in several scenarios, including planning, operating and maintaining infrastructure assets, simulating and testing scenarios to investigate future outcomes based on historic and real-time data, and enhancing collaboration between stakeholders and citizens.
Specifically, digital twins can have several types that can be used in different ways, including:
Planning twin
For planning new and upcoming developments
Service twin
For asset maintenance activities
Compliance twin
To comply with various standards
Monitoring twin
For monitoring and reporting on KPIs
Performance twin
For the reliability of key assets
Energy Twin
For energy management and sustainability
There is no one-size-fits-all for digital twins. An infrastructure developer would have different needs from a water authority than from a state government. But there are core capabilities that unite all types of digital twins.
Different uses, but one core – the capabilities of digital twins
No matter the use-case scenario, digital twins have the same central capabilities and activities that would enable an organisation to use data and insights to make decisions that help an asset, process, service or environment to be as effective, rationalised or useful as possible.
The central capabilities of a digital twin are:
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Connection
Digital twins require a connection between the digital replica and the physical asset. When things change in the physical world, updates must be made to the digital replica to reflect these. This connection is usually made through telecommunications networks to facilitate the transmission of data between the physical and digital environments. -
Integration
The digital replica can ingest or reference data sets, aggregate them, link them and prepare them for analysis and visualisation. -
Analysis
The digital twin can aid the process of inspecting, cleansing, verifying, interpreting, transforming and modelling data to create new information and insights. -
Simulation
Digital twins can model a system to gain insight into alternative conditions' potential real effects or outcomes, and possible courses of action. -
Visualisation
Digital twins can represent multiple sources of data in an easily accessible manner.
Benefits and challenges of digital twins
Digital twins can improve each phase of the asset lifecycle with a wide array of benefits:
Improved design and construction
Using digital twins to simulate and analyse different design options, identify potential risks and clashes and optimise construction sequencing can lead to reduced costs and improved project outcomes.
Enhanced infrastructure resilience
The real-time insights provided by digital twins can be utilised for proactive maintenance, optimised energy consumption and asset lifespan expansion.
Data-driven decision making
Having a single source of asset information aids in informed decision-making for operations, maintenance and future investments.
Increased collaboration and communication
Digital twins can be used to provide a shared platform for stakeholders to access, visualise and analyse asset information, fostering collaboration and communication across teams.
However, the implementation of digital twin technology comes with its own set of challenges, including:
Data management
Digital twins can require vast volumes of data from diverse sources, which raises concerns about data quality, security and interoperability.
Cost and complexity
Developing and maintaining digital twins require investment in technology, resources and specialist skills.
Lack of standards
There is currently no widely adopted standards for digital twin creation and data exchange.
Cybersecurity risks
The interconnected communication components required to run a digital twin can be attractive targets for cyberattacks.
These challenges can be mitigated and even become opportunities for growth and innovation through AI, machine learning, cloud computing, industry collaborations and systems thinking.
GHD’s approach to digital twins
We work closely with clients to develop digital twins that suit their specific needs. We aim to support practical goals like improving customer service, safety, decision-making, risk management, and long-term planning.
We take time to understand the key business processes and workflows it should reflect. This approach helps the digital twin better represent how the real-world asset would react to hypothetical or future scenarios.
Through this method, we were able to assist the Wellington City Council in improving its smart city and digital twin programme. An Urban Planning Digital Twin toolset was created from their existing technology, which was used to explore population density scenarios for its underutilised sites within central Wellington. We saw how expansion plans might impact water requirements, energy use, carbon emissions and the impact of density on transport and green space.
This digital twin toolset complemented existing town planning by bringing traditional 2D plans to life in 3D, improving stakeholder communication through 3D visualisations and providing simplified explanations of complex planning rules.
Visit our digital expertise page learn more about digital twins and our digital practices.
Articles referenced
Want to go deeper?
Explore how Wellington Water applied digital twin technology to urban planning, transforming traditional plans into interactive visualisations.
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