Coming Soon: Your Digital Twin

Marshall McLuhan once famously observed, 'First we build the tools and then they build us'. The future Digital Twin market holds endless potential as it's becoming a mainstream technology faster. Moreover, the COVID-19 pandemic increased the demand for factory and shop floor automation, real-time planning, and better worker augmentation.

Over the next decade, we will witness a complete transformation of nearly every environment in which companies do business. One example is Digital Twin technology is no longer a concept but a solution, that can be used to promote industrial growth.

Building on Artificial Intelligence (AI), the Internet of Things (IoT), and 5G communications, advanced software systems are remaking the nature and complexity of human engineering. In particular, Digital Twin Technology can provide companies with improved insights to inform the decision making process.

Just like in the early years of the Web, businesses are racing towards a future utterly different from the one they were designed for. We are living in an age where everything that exists in the real world is being replicated digitally, our cities, our cars, our homes, and even ourselves. A digital twin is an exact replica of something in the physical world, but with a unique mission, to help improve, or in some other way provide feedback to, the real-life version.

Digital twins are reshaping the foundations of engineering by combining data from human experts with machine intelligence to drive the evolution of work in new and unexplored ways.

Initially such twins were just sophisticated 3D computer models, but AI combined with the IoT have meant that you can now build something digitally that is constantly learning from and helping improve the real counterpart. By detecting anomalies and automating repair processes, digital twins can model and simulate entire procedures and processes. Most importantly, this technology enables firms to anticipate problems and prevent mistakes before they occur.

Soon, whatever is happening in the physical factory will be reflected inside the virtual one in real time: frames being dipped in paint; doors being sealed onto hinges; avatars of workers carrying machinery to its next destination.

The concept of making a duplicate or ‘twin’ of an asset to enable simulations and predict outcomes based on changes in the operating conditions finds it origins in the 1960s with the Apollo space program.

It came to the forefront in April of 1970 when NASA engineers used copies of the spacecraft systems originally intended for training to support the rescue of Apollo 13 after a disastrous explosion of its oxygen tanks. As the astronauts slept in the lunar module, the command module had to be powered down to preserve the batteries. NASA engineers used what amounted to a twin of the command module’s electrical system to devise a series of steps to power up the frozen spacecraft without draining what little power remained in the batteries.

A process that normally took two days on the launchpad was completed in under two hours. It was an extraordinary feat. And yet, the technology has only matured since then.

Neural networks reflect the behavior of the human brain, allowing computer programs to recognise patterns and solve common problems in the fields of AI, machine learning, and deep learning. Neural networks, also known as artificial neural networks (ANNs) or simulated neural networks (SNNs), are a subset of machine learning and are at the heart of deep learning algorithms. Their name and structure are inspired by the human brain, mimicking the way that biological neurons signal to one another.

Professor Sandra Wachter, a senior research fellow in AI at Oxford University, understands the appeal of creating digital twins of humans, "it is reminiscent of exciting science fiction novels, and at the moment that is the stage where it is at".

Technology analyst Rob Enderle now believes that we will have the first versions of thinking human digital twins "before the end of the decade". "The emergence of these will need a huge amount of thought and ethical consideration, because a thinking replica of ourselves could be incredibly useful to employers," he says. "What happens if your company creates a digital twin of you, and says 'hey, you've got this digital twin who we pay no salary to, so why are we still employing you?'

Enderle thinks that ownership of such digital twins will become one of the defining questions of the impending metaverse era. In Meta's virtual reality platform, Horizon Worlds, for example, you may be able to give your avatar a similar face to your own, but you can't even provide it with any legs because the technology is at such early stages.

Current examples of the real world application of Digital Twin technology include:- 

  • In Formula One racing, the McLaren and Red Bull teams use digital twins of their race cars. Meanwhile, delivery giant, DHL, is creating a digital map of its warehouse and supply chains to allow it to be more efficient. And increasingly our cities are being replicated in the digital world; Shanghai and Singapore both have digital twins, set up to help improve the design and operations of buildings, transport systems and streets.
  • In Singapore, one of the tasks of its digital twin is to help find new ways for people to navigate, avoiding areas of pollution. Other places use the technology to suggest where to build new infrastructure such as underground lines. And new cities in the Middle East are being built simultaneously in the real world and the digital.
  • Dassault's Living Heart project has created an accurate virtual model of a human heart that can be tested and analysed, allowing surgeons to play out a series of "what if" scenarios for the organ, using various procedures and medical devices.
  • Perhaps even more ambitious than replicating human organs is the race to build a digital version of our entire planet. US software firm, Nvidia, runs a platform called Omniverse, designed to create virtual worlds and digital twins. One of its most ambitious projects is to build a digital 'doppelganger' of the Earth, capturing high resolution imagery of its entire surface. Earth-2  will use a combination of deep-learning models and neural networks to mimic physical environments in the digital sphere and come up with solutions to climate change.
  • In March this year, the European Commission, in conjunction with the European Space Agency among others, announced its own plans to make a digital twin of the planet, it calls Destination Earth. By the end of 2024, it hopes to have enough data from real-time observations and simulations to have a digital twin that will focus on floods, drought and heatwaves, alongside natural disasters such as earthquakes, volcanic eruptions and tsunamis, and provide countries with concrete plans to save lives in the face of these growing challenges.

While still an emerging technology, Digital Twins are the future. That means now may be the perfect time for CTOs to start collaborating with other leaders across their enterprise to understand how to put Digital Twins to work.

Accenture forecasts organisations will use digital twins to invent products, design experiences and run their businesses in completely different, innovative ways and because of the numerous potential use cases, the digital twin market is projected to rapidly grow within the next few years. The market was valued at $3.1 billion in 2020, but is expected to reach $48.2 billion by 2026, and is expected to grow to $184.5 billion by 2030.

Accenture:     BBC:     BBC:     Nokia:    Stanford Law School:    FSStudio:    Dell:    IBM:   

ASITE:    Time:    ReWorked:   

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