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Digital Twin
Overview
Digital Twins (DT) bring a data-driven approach to asset management. They can be applied across multiple industries, including real estate development, manufacturing, energy and utilities, and pharmaceuticals and healthcare. DTs enable users to scale up the use of data and simulations in relation to the operation of physical assets, with exponential benefits in terms of the number of simulations that can be run at the same time and the accuracy of such simulations.
As a result, users are able to identify potential maintenance risks and failures and take corrective action, reducing the level of expenses and the risk of time-consuming failures and serious repairs. Another use case is in the energy sector, where DTs can be used to identify optimal operating conditions and layouts for varying energy generation plants, including wind farms, solar power plants, and thermal power plants.
Industry Updates
Market Sizing
The US Digital Twin market could reach USD 10.8 billion–14.6 billion by 2028
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Use cases
Since the days of the Apollo program, the application of DTs has spread to other sectors, including automotive, construction, industrials, and power and utilities. The main appeal of DTs is their ability to assist companies to enhance process efficiency to drive down operational costs and time to market and stay on top of evolving consumer needs.
We have identified key DT use cases below:
Market Mapping
The incumbents were early movers in the industry and traditionally dominated the market; however, we have seen several startups entering the space in recent times, primarily focusing on the digital twin modeling segment. These new startups offer data capture and analytical solutions for modeling across various industries. The maintenance and monitoring segment is also prevalent, especially among the incumbents as it caters to several industries.
Maintenance and monitoring
Digital twin modeling
Predictive assessment
Planning and management
Building and design
The Disruptors
The Digital Twin (DT) market consists of large and diversified players such as Matterport and Hayden AI. In terms of pure play companies, Cognite and Nexar remain the highest funded companies (as of April 2024) and operate in the DT modeling segment.
From a segmental perspective, digital twin modeling, which offers data capture and analytical solutions, is the largest segment in terms of funding, followed by maintenance and monitoring. Other segments receive less attention, primarily due to the increasing maturity of DT technology for modeling purposes and the relatively lower adoption costs. This stands in contrast to segments such as building and design, which require broader adoption across campuses and cities.
Funding History
Competitive Analysis
Incumbents
Most incumbents in the Digital Twin space have been focused on maintenance and monitoring segment, and are already offering solutions to customers in this segment. General Electric and Siemens stand out as two of the leading players in this space, supported by Big Tech companies such as IBM and Microsoft which offer technology services in support of DTs.
In terms of activity types, incumbents primarily rely on partnerships for innovation in their products and services, followed by investments and acquisitions to bring innovative companies under their internal innovation units. The impact of this can be seen in the in-house development at key incumbents, which are developing the tools that can be used by customers seeking to implement DTs.
Notable Investors
