Ian Risk from the Centre for Modelling & Simulation explores the critical role that simulation plays in creating digital twins and enabling the construction sector to meet the housing demand
The ability to independently and accurately monitor and virtually model how a process or model performs in real time without physical intervention is the ultimate prize for engineers and manufacturers in meeting the housing demand.
Without the huge cost of interrupting operations, it allows for the assessment of all manner of scenarios which could improve performance, from a streamlined approach to construction at a time when the housing demand is sky-high, to assessing the sustainability credentials of a building.
This “holy grail” is now commonly referred to as a digital twin. Operating symbiotically with its real-world counterpart, the digital twin is a fully connected but virtually modelled representation, continually fed with live data from the real physical system or plan.
Creating a viable digital twin is a major undertaking. Within construction, if it is to be used to predict what may happen to a building as circumstances change – such as materials being substituted due to supply chain challenges and time pressures, then the commercial consequences can be substantial one way or another. This makes a high level of trust in the outcome essential.
Data driven
Any model is only as good as the data used to develop it. A digital twin is no different – it needs data to evolve with its physical counterpart.
Capturing real-world data historically has been a time-consuming issue. This has meant existing models are working retrospectively rather than being in a position to make predictions based on live data. A model that tells you what went wrong has far less value than one that tells you something will go amiss, particularly when developers must juggle site logistics, staffing during a skills shortage and the appetite to develop affordable, quality housing to meet government targets of 300,000 homes per year by the middle of the decade.
As our cities and buildings are being built with an increasingly digital focus, Industry 4.0 provides the means to capture and record data on a massive scale and can rapidly identify variations in the state of a component or system. This goes way beyond exceeding a set threshold and can provide insight into how a system may be degrading or acting out of its original design assumptions.
This amount of data means the digital twin has the potential to predict the remaining life of the system, anticipate maintenance activities or improve design for more resilience to variations. Following comments in May from the levelling up secretary Michael Gove, who suggested that quality over quantity was more important when it came to housing targets, this is particularly important to the sector as it strives to avoid delivering homes that are “shoddy, in the wrong place, don’t have the infrastructure required and are not contributing to beautiful communities”.
It is not only design and maintenance of a building that can be supported in this way. The efficiency of production, quality control and operations management can all be enhanced through artificial intelligence (AI) systems. But, to develop them reliably and make them cost-effective, one needs simulation.
Through-life simulation
Simulation can embed a lifetime of knowledge into a relatively simple algorithm. It is essential this is done to accurately encode knowledge into these systems and that the approach is endorsed by experts. Only then will the system have value and subject matter knowledge that can be relied on.
Simulation can also help us understand what is happening if things go beyond the realms of human experience or as unforeseen properties emerge throughout the whole-life of the building. By flagging potential issues before they happen, digital twin simulation can support the robust development of homes at a far faster pace than could be achieved in trial and error through build which, again, means less downtime and better productivity.
As the world around us changes, the construction industry needs to challenge what it does in a more comprehensive but economic way if it is to deliver results to meet societal needs – such as the drive for net zero in tandem with the housing demand. Virtualising design and simulation by embracing digitalisation is a key route to achieving this goal and realising the power of concepts such as digital twins.
Ian Risk
Chief technology officer
Centre for Modelling & Simulation
Tel: +44 (0) 117 906 1100
Twitter: @CFMSuk
LinkedIn: CFMS
YouTube: CFMS UK
