Real-world data combined with digital simulations of digital twin products provide valuable insights that help 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 Thread Processing Center at Raytheon.
“As the saying goes, ‘All models are wrong, but some are useful,'” Ferrari said. “Data-backed digital twins – as real facts – are a way to identify models that are really useful for decision-making.
The concept began to evolve, with the digital twin technology and tools market growing by 58% annually to reach $ 48 billion by 2026, up from $ 3.1 billion in 2020. Using digital prototyping technology saves resources, money and time. However, the technology is also used to simulate much more – from urban populations to energy systems to the introduction of new services.
Take as many diverse manufacturers as Raytheon and the Swedish distillery Absolut Vodka, which use technology to design new products and streamline their production processes, from the supply chain through production and ultimately to recycling and disposal. Singapore, London and several cities on the Gulf of Texas have created digital twins of their communities to address aspects of city governance, including modeling city traffic patterns, analyzing construction trends and forecasting the impact of climate change. Both companies such as Bridgestone and drone service provider Zipline are using technology combined with operational data to help launch new services.
Companies have adopted digital twins as part of their digital transformations, a way to simulate productivity, identify weaknesses and manage services more effectively. Each company’s digital initiative must explore whether certain aspects of its product, operations or environment can be simulated to gain an idea.
Simulation of design and production
Modern digital twin technologies have their foundations in computer-aided design (CAD) and computer engineering tools developed more than three decades ago. These software systems allow engineers to create virtual simulations to test changes in product design. Engineers designed a component of the product, such as an airfoil, on a computer and then commissioned a modeler or sculptor to make the item from clay, wood, or basic components for physical testing.
Today, the process has shifted the prototyping phase to much later in the process, as the massive growth in computing power and storage allows not only the entire product to be prototyped, but other information to be integrated, such as raw material delivery information, components required for the production and operation of the product in the field.
“If you look at these CAD and engineering tools from 30 years ago and close your eyes a little, you’ll see that these things are digital twins,” said Scott Buchholz, chief technology officer of government and public services and emerging director of technology research at Deloitte. Consulting. “With the increase in power calculation and storage, the ability to do useful simulations has increased, and we’ve moved from low-precision imaging to high-precision simulations.
The result is that digital twin technology has taken over various industries with a storm. Manufacturers of expensive vehicles and infrastructure products are taking advantage of shortening the design and development cycle, making aerospace companies, carmakers and urban planning agencies all early consumers. Yet startups are also adopting a simulation mentality in the first place to quickly replicate product improvements.
A major advantage: the digital twins pushed the physical construction of the prototypes much lower in the design process. Some companies chasing zero prototype initiatives aim to completely eliminate the steps of prototyping and allow direct production efforts, said Nand Kochhar, vice president of automotive and transportation at Siemens Digital Industries Software.
This is a huge change from the past. “The typical product development lifecycle was anywhere from six to eight years,” Kochhar said of the automotive industry. “The industry is working on that and now they have an 18-month or 24-month life cycle. Automotive production is now more dependent on software, which is becoming a determining factor in the life cycle. “
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