Where are we now?
It’s commonly accepted that the AECO sector lags behind most of the other major sectors in terms of digitalisation. This contributes to the poor service received by clients in terms of data and information collected during the planning, design and construction phase and especially during and after the handover phase when the owner/occupier takes possession of the asset. This is because upfront planning for the operational phase of the asset is often overlooked or lacks relevant detail or structure.
Poor handover processes generate unexpected costs and delays to start up and operations. Then during operations, public and private asset owners struggle to optimise the value of their portfolio. For example, maintenance activities can be reactive or simply annualised and are not optimised based on actual performance data. Also, reliance on document sharing rather than information leads to storage and access issues over the life of an asset, especially as supplier contracts change, face bankruptcy, or people leave in which case data is lost.
What about BIM?
BIM, or Building Information Modelling means that 3D Models are now regularly developed as part of the design and build phase and there have been examples of the models or the associated meta being handed over to help onboard asset management systems. This provides some value, but the benefits of the BIM model are quickly lost unless the models and the data are maintained throughout the asset or portfolio’s lifecycle. The maintaining of BIM models could a be a significant for organisations and updates are invariably manual.
The Rise of the Digital Twin
Now with the decreasing cost of cloud storage, Internet of things (IoT) sensors, LiDAR scanning and data analytics, we have the opportunity to more closely and critically evaluate our assets. Thanks to IoT sensors and analysis of performance using data analytics tools, information can be visualised back into the BIM model, allowing the model(s) and the asset to be simultaneously updated. That is one simple use case for Digital Twin, there are many more as according to Gartner:
“A digital twin is a digital representation of a real-world entity or system. The implementation of a digital twin is an encapsulated software object or model that mirrors a unique physical object, process, organisation, person or other abstraction. Data from multiple digital twins can be aggregated for a composite view across a number of real-world entities, such as a power plant or a city, and their related processes”
The term “Digital Twin” gained recognition in 2002 in a paper published by Michael Grieves on Product Lifecycle Management at the Florida institute of Technology but the concept can be traced back to the 1960’s with NASA creating simulations of outer space conditions.
The future of Digital Twins
As more use cases for Digital Twins become apparent, it is expected that Artificial Intelligence and Machine Learning will further advance the automation opportunities and the data analytics will become more predictive in nature. Conceptually, Digital Twins are also seen as an enabler as we move towards Smarter Cities and integration with Autonomous Mobility.
Considerations for Digital Twins
- The AECO sector must guard against over–hype around Digital Twins and be careful not be a solution looking for a problem, therefore it is vital to engage with asset owners, service providers and end-users to understand their needs.
- Align to common frameworks for Digital Twin such as the Gemini Principles in the UK
- Organisations must have a foundation of information management in place, with BIM models being shared within a Common Data Environment, aligned to international standards like ISO19650
- Contract and Commercial – what will be the impacts on responsibilities? Will performance contracts accompany digital twins?
- Security implications of IoT sensors and cloud hosting
- Can Digital Twins enable the AECO industry demonstrate a tangible reduction in energy usage, both embodied energy and energy in use?