5 industries set to be transformed by digital twins

Digital twins are fast transforming industry. Developed by NASA - like so many other technologies in everyday life - a digital twin is a model of a physical, real-world object, process or service, allowing users to map out designs and operations.

With a virtual representation of reality rather than the real thing, digital twins can give users a clearer picture of what’s happening, identify trends and test possible changes without risk.

The technology relies on a large number of inputs, often from connected data-gathering sensors measuring a real-world counterpart, and its developing rapidly; the market is set to reach $86.09 Billion by 2028.

Manufacturing

From design and prototyping to quality management, production scheduling and even repair and maintenance, digital twins give manufacturers a way to optimise their processes, boost productivity and reduce downtime. Over 70% of engineers say digital twin technology have become vital to physical asset design - laptops to cars, beds to boats.

In the past, it may have taken a dozen test drives of a vehicle to identify problems and isolate issues. Now, with an exact digital replica of the vehicle viewable in a 3D space, the majority of any design flaws can be found before the car is ever driven, thus resulting in faster lead times, and fewer wasted prototypes.

Logistics

Digital twins are, ultimately, composed only of data. This means that anything, from a physical object such as a truck to the agricultural sector’s entire supply chain, can theoretically be mapped digitally, creating a digital twin.

“It allows manufacturers to digitally replicate and analyse their entire manufacturing footprint for potential pain points,” as Matt Tichon, Vice President for Industry Strategy at LLamasoft, puts it. “Businesses can assess the potential impact [an event] will have on their end-to-end operations. With this knowledge, they can prepare for any eventuality that they can imagine, big or small.”

Knowledge is power, and with digital twinning of logistics and supply chains, companies can anticipate how different changes will affect their business in a sector with high exposure to risk - like climate events, geopolitical developments and pandemics. Digital twins also help logistics providers improve efficiency and reduce transport costs, testing different strategies and logistic routes before rolling them out in the real world.

Healthcare

There are already multiple digital twin developers working in the healthcare industry, with two primary services available to aid healthcare professionals in different ways.

Companies such as Unlearn.ai provide digital twinning services that model and map patients in order to speed up clinical trials. By making digital twins of patients, Unlearn.ai uses machine learning combined with baseline data to model how a patient’s health would’ve continued had they not received the experimental treatment.

Where traditional clinical trials require enrolment in a trial group and a control group (who receive placebos) this form of digital twinning replaces the need for a control group, as digital twins of each patient act as said control group.

This greatly reduces clinical trials lead times, as well as reducing the number of patients required - potentially saving pharma companies millions in market research costs.

A digital twin can also be used to create 3D models of medical equipment and organs of specific patients. Companies such as Dassault Systèmes have already made astonishing headway into this, as shown with their living heart project, which help with both research and medical device design, already in partnership with industry organizations such as Philips, Medtronic, and Boston Scientific.

Digital twins of organs are also reducing medical training costs and accelerating development of medical equipment. Where the project development of a pacemaker once needed a constant flow of patients and cadavers for analysis and tests, the bulk of development can now be completed entirely digitally.

Construction

In the same vein as the manufacturing industry, digital twin technology will greatly aid in both the design and implementation of modular construction. Unlike the manufacturing industry, which has generally kept up to speed with digital transformation, the global construction industry has more room for innovation.

For the starting phase of construction, architects will be able to have their designs modelled into a digital twin, using the data provided by IoT to show what elements may cause issues before construction has even begun.

Along with the actual physical construction, the cost, energy requirement, timeframe and carbon footprint of a construction project can all be more accurately mapped and predicted with the use of a digital twin, providing construction companies with vital information on how their project should progress.

The implementation of digital twins technology can rapidly reduce both cost and development time, as was discovered when CadMakers provided digital twins technology to design the Brock Commons Tallwood House at the University of British Columbia in Vancouver: “As a result, the 20-month project was completed in under 17 months and delivered in half the time of an equivalent building using traditional methods.”

Finance

There are many benefits available for banks and other financial services institutions that incorporate digital twinning, one of the most universal ones is the ability to predict markets. There already exists a multitude of detailed twins of the world market and specific stock exchanges, created through IoS data and monitoring of the real-world component.

These digital twins can then be used to run simulations for different scenarios, from predicting volatility in different stock options or loan programs, to estimating losses or gains after certain events.

And digital twinning can also help with the regular day-to-day running of a business, measuring IoS data to show what times and days customers are most likely to call help lines, or how a mortgage offer is likely to pan out a decade down the line.