The journey from Building Information Modelling to Digital Twins

Often called a Digital Twin, a concept introduced in 2002, is becoming increasingly relevant to the built environment. A Digital Twin is a virtual, or digital, representation of the elements and dynamics of a physical asset or system used for simulation, prediction and decision-making. The virtual model is not only a static representation of the physical asset, it can also be integrated with real-time data.

With valuable data insights, a Digital Twin can radically alleviate operational and maintenance burdens to improve safety and forecasting. For every asset, data source or location, there is a potential virtual version, fed from existing technologies that becomes richer and increases in functionality with every event or data source added.

By creating a Digital Twin, insights that reflect the physical twin’s structure, performance, health status, asset criticality, maintenance history, financial data, and resources help to optimise operations of the physical asset and predict system inefficiencies or security incidents. The physical twin’s systems can be simulated in a virtual environment with substantially less risk at a lower cost.  

We have encountered many asset owners that store their asset data across multiple disparate systems. Creating a Digital Twin which integrates the multiple sources and formats of asset data (TOTEX, CAPEX, OPEX, age, and other attributes etc...) has been proven to be beneficial for asset owners in decision making.

There are four levels of maturity for Digital Twins:

• Pre-Digital Twin: Created during the upfront engineering, it is a virtual prototype of the envisioned physical asset. The elements, their respective relationships, and actual data is created as early as the planning and design stage, then carried over through to the end of the construction phase. This helps designers and engineers to plan and mitigate risks in the design and construction stage. Currently, the industry refers to these models as Building Information Modelling (BIM) or digital engineering models.
• Informative Digital Twin: A virtual replica of the completed physical asset that captures similar characteristics of the Pre-Digital Twin and incorporates maintenance, asset health, finance, resources, and performance data of the physical asset.
• Performance Digital Twin: Connects digital and physical versions of the asset using sensors or Internet of Things (IoT) devices. This allows for real-time data of the physical assets to be reflected in the digital model. This allows information like status data, performance, and operational health from the physical asset to be constantly monitored.
• Autonomous Digital Twin: Automates discovery of new knowledge and insights through data mining and machine learning which enables it to continuously learn and improve over time. This generates predictive insights from the asset which lead to reduced downtime, optimised energy consumption and the development of new business models that foster continuous optimisation processes and deliver true value.
  

Still, building and infrastructure systems lack connectivity. One way to overcome this is by leveraging BIM to act as the Digital Twin for distributed IoT systems. There is a rapidly growing, global movement towards the use of Digital Twins and today’s sophisticated digital technology allows a vast array of business challenges to be addressed.

With the advancement of cloud data storage and IoT, BIM is the first step in creating a Digital Twin of the built environment – one that can provide significantly enhanced spatial context for distributed IoT systems.

Like many asset-intensive industries that are adopting digital transformation, the built environment is transitioning towards a computing platform. This in turn, will help asset owners improve their customer experience by being able to better understand their customer’s needs and optimising enhancements to existing facilities, operations and services which help drive the innovation of new business models. 

As the fourth industrial revolution evolves towards autonomy, much of that will derive from Digital Twins – enhanced by artificial intelligence and domain expertise. Asset owners can begin to safely, flexibly, and progressively model what matters to them and their customers — interacting across their enterprise, supply chains and customers.

Asem Zabin is an experienced digital assets and engineering consultant. His career includes successfully fulfilling leadership roles on numerous global complex projects. He is passionate about helping organisations kick off their digital transformation journey by creating strategic digital roadmaps and robust business cases to achieving business efficiency. Expertise includes change management, digital engineering frameworks, processes, and standards such as ISO 19650.