The digital twin technology is driving sustainability goals forward

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  • Widespread adoption of digital twins across industries is having a transformative business impact on product development, risk assessment and sustainability, an Altair survey of more than 2,000 IoT and software engineering specialist, among other IT roles.

Respondents said digital twin technology will help them achieve their sustainability goals for resource efficiency (76%), energy savings and operating cost savings (74%). and reduce waste (60%).

The majority (68%) of management responses said their company uses digital twins to achieve their sustainability goals, compared with just 43% of user-level responses.

“The main driver of any manufacturer is to save time and money,” said Keshav Sundaresh, global director of product management for Altair’s digital twin. “Manufacturers are always looking for effective ways to track and monitor products to improve reliability and performance.”

From a sustainability standpoint, less physical prototyping equals less waste, says Sundaresh. About two-thirds of respondents expect digital twins to make physical prototypes obsolete in the next few years. “That alone has had a significant impact on sustainability,” says Sundaresh.

Impact of physical prototyping on durability

Digital twins allow users to comprehensively understand and measure what is happening in a department, subsystem, product or process (in conjunction with the environment in which it operates) by combining multiple data sources and can also be used as a guide for future prediction and virtual execution of many simulation studies.

“This means a significant reduction in building operating costs through reduced energy consumption, maintenance, planning and operating costs,” he said.

For example, the digital twins in banking, financial services and insurance (BFSI) have been able to dramatically reduce the number of printers in an organization, not to mention saving millions of cartons of paper – and trees. Sundaresh adds: “Digital twins can help reduce the cost of raw materials, reduce product development costs, and reduce CO2 emissions from physical prototypes and test vehicles. Digital twins also improve quality and accuracy

Equally important, he said, is the improved quality and connectivity through the use of digital twins. “Digital twins integrated with AI algorithms offer the potential for highly efficient simulations with higher accuracy than traditional virtual prototyping methods,” he explains.

In addition, digital twin models can be deployed on live data from physical sensors to predict current and future performance of system components, subsystems, and systems. or process.

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