Digital twins: 5 success stories

Digital twins: 5 success stories

Humans have always gathered data to better understand the physical world around us. Today, companies are increasingly seeking to meld the digital world of data with the physical world through digital twins. Digital twins serve as a bridge between the two domains, providing a real-time virtual representation of physical objects and processes.

These virtual clones of physical operations can help organizations simulate scenarios that would be too time-consuming or expensive to test with physical assets. They can help organizations monitor operations, perform predictive maintenance, and provide insight for capital purchase decisions, creating long-range business plans, identifying new inventions, and improving processes.

In a forecast released in June 2022, research firm MarketsandMarkets said the global digital twin market is expected to grow from $6.9 billion in 2022 to $73.5 billion by 2027, a compound annual growth rate (CAGR) of 60.6% over the period.

Here are five examples of how organizations are using digital twins effectively today.

NTT Indycar puts fans behind the wheel

The NTT Indycar Series, comprised of five races including the Indianapolis 500, is using a combination of digital twin, data analytics, and artificial intelligence (AI) capabilities to give fans access to in-depth, real-time insights about races, including head-to-head overtaking, pit predictions, and other elements.

Partner NTT creates a digital twin for every car in the series. Historical data provides a foundation, and each car is equipped with more than 140 sensors that collect millions of points of data during each race to feed the digital twin. The data includes everything from speed to oil pressure to tire wear and G forces. NTT uses AI and predictive analytics on the digital-twin data to deliver fans insights that previously would only have been available to race team engineers, including race strategies and predictions, intercepts and battles for position, pit-stop performance impact, and effects of fuel levels and tire wear.

Analytics, Artificial Intelligence, Digital Transformation, Machine Learning, Predictive Analytics

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