The real-world data-digital twins combined with digital simulations of products provide valuable insights that help companies identify and solve problems before prototypes go into production and operate products in the field, says Alberto Ferrari, senior director of model-based digital. Thread processing capacity center at Raytheon.
“As they say, ‘all the models are wrong, but some of them are useful’,” says Ferrari. “Digital twins, supported by data – as a matter of fact – are a way to identify really useful decision-making models.”
With the digital-twin technology and tools market growing 58% annually from $ 3.1 billion in 2020 to $ 48 billion by 2026, the concept has begun. Using technology to build digital prototypes saves resources, money and savings. Time. However technology is being used to further emulate everything from the urban population to the deployment of new services to energy systems.
Take manufacturers as diverse as Raytheon and Swedish distillery Absolute Vodka, who are using technology to design new products and streamline their production processes, ranging from product to supply chain and, finally, to recycling and disposal. Singapore, London and many Texas Gulf Coast cities have created digital twins in their communities to address aspects of city management, including modeling traffic patterns on city streets, analyzing building trends and predicting the impact of climate change. And companies like Bridgestone and drone-service provider Zipline are using paired technology with operational data to help launch new services.
Companies have adopted digital twins as part of their digital transformation, a way to simulate performance, identify vulnerabilities and manage services more efficiently. To gain an understanding of any company’s digital initiative one must explore whether certain aspects of its product, operation or environment can be emulated.
Design and production simulation
Today’s digital-twin technology is rooted in computer-aided design (CAD) and computer engineering tools that were developed more than three decades ago. Those software systems allowed engineers to create virtual simulations to test changes in product design. Engineers created a product component, such as an airfoil, on a computer and then assigned the task of making the object into clay, wood, or stock components for physical testing to a modeler or sculptor.
Today, the process has shifted the prototyping stage much later in the process, as the massive increase in computational power and storage allows not only to prototype the entire product but also to integrate other information, such as raw supply information. Materials, components required for production and production operations in the field.
“If you look at those CAD and engineering tools from 30 years ago and your eyes are a little bit like a tiny tiny tiny tiny tiny tiny tiny tiny tiny tiny tiny tiny tiny tiny tiny tiny tiny tiny tiny tiny tiny tiny tiny tiny tiny tiny tiny tiny tiny tiny. And as storage grew, so did the ability to do useful simulations, and we moved from low-fidelity rendering to high-fidelity simulation. ”
The result is that digital-twin technology has taken various industries by storm. Manufacturers of expensive vehicles and infrastructure products benefit from all the early adoption of aerospace companies, car manufacturers and city planning agencies by shortening the design and development cycle. Yet startups are also adopting a simulate-first mindset to quickly repeat product improvements.
One big advantage: the digital twins have pushed the physical construction of prototypes further down the design pipeline. Nand Kochhar, vice president of the automotive and transportation industry at Siemens Digital Industries Software, says some of the companies pursuing the zero-prototype initiative aim to completely eliminate prototype measures and direct-to-manufacturing efforts.
It’s a huge shift from the past. “The typical product development life cycle was six to eight years,” says Kochhar about automobile manufacturing. “The industry is working on it, and now they have an 18-month or 24-month life cycle. Now, more reliance is placed on automaking software, which is becoming a crucial factor in the life cycle.
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