The global digital twin market value stood at $3,210.1 million in 2020, and it is predicted to surge to $184,517.4 million by 2030. According to the estimates of the market research company, P&S Intelligence, the market will advance at a CAGR of 50.0% from 2020 to 2030 (forecast period).
Additionally, many product owners and vendors are requiring digital representation for reducing the marketing time period and operational costs. Depending on application, the digital twin market is classified into performance monitoring, inventory management, product design and development, predictive maintenance, and business optimization.
Out of these, the predictive maintenance category is predicted to exhibit the fastest growth during the forecast period. Enterprises can collect real-time information, estimate downtime, schedule maintenance by developing a digital twin of a system, process, or a product, and automate operations. Thus, the demand for digital twin solutions will shoot up all over the world in the years to come
The ballooning adoption of machine learning (ML), 5G, artificial intelligence (AI), and the internet of things (IoT) technologies, growing popularity of Industry 4.0 standards, and the burgeoning requirement for cloud services are the major factors propelling the advancement of the market across the globe. With the rising penetration of the internet, the adoption of the IoT is surging sharply, with more than 41 billion IoT-connected devices predicted to be in usage by 2025.
To ensure the successful functioning and implementation of IoT, growing the throughput for every component is critical, which can be done by the adoption of the digital twin technology. As the performance and behavior of a system during its lifespan rely heavily on its parts, the requirement for the digital twin technology is mushrooming rapidly around the world in order to facilitate rapid system improvements.
Additionally, many product owners and vendors are requiring digital representation for reducing the marketing time period and operational costs. Depending on application, the digital twin market is classified into performance monitoring, inventory management, product design and development, predictive maintenance, and business optimization.
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