Digital Twin Market was valued at USD5.715 billion in 2020 and is expected to grow at a CAGR of 33.28% during the forecast period owing to the increasing adoption of 3D printing, increased usage of IoT devices, the introduction of ADAS in automobiles across the globe.
Technological advancements across the manufacturing and healthcare sector are further propelling the market. However, concerns related to data encryption, interaction with digital and physical things are expected to hamper the market growth during the forecast period.
The global digital twin market can be segmented based on type, technology, application, end user, and region. Based on type, the market can be segmented into process, product and system. The process segment held a major share in 2020 and is expected to continue to do so in the forecast period as well. Process digital twins assist in the creation of new customer and enterprise value through personalized service, the advancement of product quality, the prevention of breakdowns before they occur, and the reimagining of knowledge-sharing in a people-machine environment. In terms of technology, the market can be segmented into the internet of things, artificial intelligence and machine learning, blockchain, big data analytics, extended reality and 5G. The internet of things segment accounted for the highest growth in the market and is expected to dominate in the forecast period as well, primarily because the physical world experience of the digital twins is captured through sensors and IoT are a fundamental requirement of a digital twin. Based on applications, the market is segmented into manufacturing process planning, product design, predictive maintenance, and others including business optimization, inventory management, etc. The manufacturing process planning accounted for the highest market share in 2020, capturing 37.34% of the market. Usage of digital twins in the manufacturing process planning helps manufacturers to reduce the time and cost associated with assembling, installing, and validating factory production systems. Based on the end user, the market is bifurcated into manufacturing, automobile and transportation, healthcare and life sciences, energy and utilities, aerospace and defense and others including retail and consumer goods, agriculture, logistics, etc. The manufacturing segment held a majority of the share capturing 25.49% of the market share in the year 2020. Digital twins act as virtual prototypes during the product designing stage and before investing in a solid prototype, it can be adjusted to test different simulations or designs which in turn reduces the cost and time by reducing the number of iterations required to get the product into production.
Key players in the global digital twin market include: Dassault Systems Inc, PTC Inc,Siemens AG, General Electric Company, Aveva Inc., Oracle Corporation, Microsoft Corporation, IBM Corporation, Honeywell International Inc., Robert Bosch GmbH, ABB Group, Rockwell Automation, ai, Inc.,Bentley Systems Incorporated,Bosch Rexroth AG,
Dassault Systems Inc is headquartered in France and operates on a global scale. The company’s goal is to develop leadership in life sciences and healthcare, as well as to make continuous advancements in manufacturing industries, infrastructure, and cities. In late 2019, the company acquired Medidata, which enabled it to provide a combination of virtual technologies, analytics, and artificial intelligence to the healthcare and life sciences sectors, allowing it to visualize the molecular structure of a virus and achieve innovation in clinical trials.
According to TechSci Research “A digital twin is a virtual/digital replica of a physical entity such as a device, person, process, or system that assists businesses in making model-driven decisions. Digital twins are transforming the way people work in a variety of industries and business applications. Digital twins are most popularly used in the manufacturing industry. Manufacturing relies on high-cost equipment that generates a large amount of data, making it easier to create digital twins. Businesses can use digital twins to create various permutations of a product in order to provide personalized products and services to their customers. Engineers can use digital twins to test the feasibility of upcoming products before they are released. Engineers begin production or shift their focus to creating a viable product based on the test results. Though digital twin practices can be used in traditional automotive manufacturing, they are especially useful for autonomous vehicle companies. Some applications of digital twins in the automotive industry are road testing and vehicle maintenance. As IoT implementations expand access to big data and vast digital ecosystems, high-fidelity digital twins are becoming easier to create and maintain. Digital twin technology is quickly becoming one of the most important software tools for revolutionizing product development.”, said Mr. Karan Chechi, Research Director with TechSci Research, a research-based global management consulting firm.