In March 2020, it was announced in Malaysia that digital twin technology was used in the development of the Pan Borneo Highway.
The technology was used to build accurate 3D models of the project, while integrating road information, maintenance systems and other details to manage data and enable a complete visualisation of the highway for the government to monitor and be involved in the process.
Malaysia isn't unique. Digital twins is a tried-and-true technology that can help government agencies collaborate, test-bed new technology, and support policy decisions, within a true-to-life model of the city. It has been utilised by many city planners to facilitate innovation and operations.
For example, in Shanghai, specialists created a complete virtual clone of the city to help monitor everything from traffic and building operations to bridge maintenance. They can even use predictive data to simulate floods for disaster planning.
What is perhaps lesser known is that digital twins are opening up new possibilities — not just for government applications, but also for other sectors like facilities management, manufacturing and transportation.
It is time for business leaders to familiarise themselves with the idea of digital twins, its applications for business and consider whether a digital twin is right for their organisation.
So, how do digital twins work? Simply put, a digital twin is a 3D model of a physical entity. The twist is that the 3D model's animation is driven by the real entity's live data.
For instance, in manufacturing, digital twins can come in handy to optimise a factory's assembly line to see if manufacturing time or costs can be reduced. As a first step, companies can build a 3D model of the factory that includes everything involved in production —machines, robots, raw materials, conveyor belts, forklifts, carts, and even people.
Then, in the physical factory itself, the machines and robots would be configured to send live data on their operations, such as the length of time to complete a particular process. Sensors are also placed in key areas to tell you when changes occur, such as the arrival of a pallet of raw materials or the filling of a container with finished products.
Next, a software interface is set up to process the live data and update the 3D model in real time. With this, the company now has an up-to-date representation of the factory, visible on a computer screen or even in VR — a digital twin of the factory.
Digital twins provide ways to optimise time and money through monitoring and analysis of assets, processes, and workflows.
In the manufacturing example above, at any time, executives and engineers can "see" the factory floor by looking at the digital twin. They can even interact with it by zooming in to see what a specific process is doing or zooming out to see the bigger picture. The captured data can also be analysed further through mathematical models and tools.
Digital twins provide information, both numerical and visual, that help designers, architects, engineers, and other stakeholders visualise structures in ways never before possible. Discernable patterns that cannot typically be seen with traditional analysis can emerge through the use of digital twins, leading to insights on how to improve efficiency.
With the factory digital twin, for instance, engineers may notice that if certain raw materials or robots were positioned closer to a specific machine, production time could be substantially reduced.
The tools to create digital twins have existed for quite some time. But until recently, the barrier to entry for digital twins was high — initial setup required a proficient coder, and then a User Experience (UX) designer needed to come in to make the digital twin accessible to non-technical personnel. In short, a digital twin took a great deal of time and effort to create and maintain, resulting in low take up often limited to the public sector.
However, the availability of real-time technology today has virtually eliminated these barriers. Real-time technology via game engines makes setting up and maintaining a digital twin much easier and faster than programming from scratch, with intuitive interfaces that are easy to navigate and require no coding or technical expertise. Some real-time software tools even come with built-in features for live data processing, enabling users to build and access 3D models easily. The end-result is a digital representation that is easy for anyone to navigate, thus lowering the barriers to adoption for many sectors.
The global digital twin market size is projected to grow by more than 15 times from 2020 to 2026 — from US$3.1 billion to US$48.2 billion. During this time, Asia Pacific is expected to record the highest growth, due to the dense population, growing per capita income, and the increasing adoption of the IoT in the region.
A key area for the future is supply chains, where a manufacturing process relies on parts delivered for just-in-time manufacturing. A digital twin of a supply chain consists of many items and warehouses, tracking the inventory and potential delivery times. Such a digital twin can simulate and evaluate performance of many different supply-chain scenarios, giving managers the means to make decisions that will optimise the manufacturing process.
Another area where digital twins can come in handy is in the autonomous vehicles sector. Here, data from sensors, combined with the car's speed, stops, starts, and swerves, is applied to a 3D model for a view of what the car is doing at any given time. Using the digital twin, engineers can gain insights to improve vehicle function and safety that would be difficult to glean from streams of numbers alone.
As adoption continues to grow, we expect to see more uses of digital twins in many sectors from city planning to product development and factory simulation. Companies that get ahead of the game, and invest time developing digital twins, in line with their business goals, will gain a much-needed competitive advantage.
The writer is Business Director, India-SEA at Epic Games