Real-world data combined with digital product simulations (digital twins) provide valuable information that helps companies identify and solve problems before prototypes go into production and manage products in the field, says Alberto Ferrari, senior director of Model-Based Digital Threading Capability Center at Raytheon.
“As they say, ‘All the models are bad, but some of them are useful,'” says Ferrari. “Digital twins, backed up with data, like real events, are a way to identify models that are really useful for decision making.”
The concept has started to take off, with the market for digital twins technology and tools growing rapidly. 58% annually to reach $ 48 billion by 2026, up from $ 3.1 billion in 2020. Using technology to create digital prototypes saves resources, money, and time. However, the technology is also being used to simulate much more, from urban populations to energy systems and the deployment of new services.
Take manufacturers as varied as Raytheon and swedish distillery Absolute vodka, who use technology to design new products and optimize their manufacturing processes, from supply chain to production and ultimately recycling and disposal. Singapore, London, Y various cities on the Texas Gulf Coast They have created digital twins of their communities to address facets of city management, including modeling traffic patterns on city streets, analyzing construction trends, and predicting the impact of climate change. And companies like Bridgestone and drone service provider Zipline are using the technology alongside operational data to help launch new services.
Businesses have embraced digital twins as part of their digital transformations, a way to simulate performance, identify weaknesses, and operate services more efficiently. The digital initiative of any company must explore if any facet of its product, operations or environment can be simulated to obtain information.
Simulating design and manufacturing
Today’s digital twin technologies have their foundations in computer-aided design (CAD) and computer engineering tools developed more than three decades ago. Those software systems allowed engineers to create virtual simulations to test changes to product designs. Engineers designed a product component, such as an airfoil, on a computer and then commissioned a modeler or sculptor to craft the item out of clay, wood, or stock components for physical testing.
Today, the process has moved the prototyping stage to a much more advanced stage of the process, as the massive growth in computational and storage capacity allows not only to prototype the entire product, but also to integrate other information, such as information on the supply of raw materials. materials, components necessary for the manufacture and operation of the product in the field.
“If you look at those CAD and engineering tools from 30 years ago and squint a bit, you’ll see that those things were digital twins,” says Scott Buchholz, chief technology officer for government and utilities and director of emerging technologies research at Deloitte. . Consultant. “As computation and energy storage increased, the ability to perform useful simulations increased and we went from low-fidelity renderings to high-fidelity simulations.”
The result is that digital twin technology has taken a variety of industries by storm. Manufacturers of expensive vehicles and infrastructure products benefit by shortening the design and development cycle, making aerospace companies, automakers, and urban planning agencies early adopters. However, startups are also embracing the pretend-first mindset to quickly iterate on product improvements.
One major advantage: digital twins have gone much further in the physical construction of prototypes in the design process. Some companies pursuing zero prototyping initiatives are aiming to eliminate prototyping steps entirely and enable direct efforts to manufacturing, says Nand Kochhar, vice president of automotive and transportation industry at Siemens Digital Industries Software.
That is a massive change from times past. “A typical product development life cycle was six to eight years,” says Kochhar of car manufacturing. “The industry has been working on that and now they have a life cycle of 18 or 24 months. Now, car manufacturing is more reliant on software, which is becoming the determining factor in the life cycle. “
Download the full report.