A digital twin is a digital replica of a physical entity— a product, process, person, or place. It uses real-world information using its data analytics, machine learning, & multi-physics simulation capabilities to predict the performance characteristics of their physical companions. Sensors installed on objects or assets demonstrate their real-time performance, operating scenarios, & changes over time, which ensure accurate modeling over a product's entire lifetime. Thus, it eliminates the need for physical prototypes, minimizes production time, & enhances the quality of the final product or process.
The Global Digital Twin Market is projected to grow at a whopping 58% CAGR during the forecast period, i.e., 2023-28. The growth of the market expansion would be propelled mainly by the ever-increasing demand for asset monitoring, rising penetration of Industrial IoT (IIoT), and the growing number of smart building infrastructures to ensure optimum energy consumption. Digital twins help create predictive models to identify the possibility of success of physical prototypes before they are actually built. Hence, they allow for improved workflow across different stages of a product's lifecycle— design, engineering, maintenance, & sales.
|Study Period||Historical Data: 2018-21|
|Base Year: 2022|
|Forecast Period: 2023-2028|
|Regions Covered||North America: US, Canada, Mexico|
|Europe: Germany, UK, France, Italy, Spain|
|Asia-Pacific: China, Japan, India, South Korea, Australia, Singapore|
|South America: Brazil, Argentina, Columbia|
|Middle East & Africa: Turkey, UAE, Saudi Arabia, South Africa, Qatar|
|Key Companies Profiled||
Siemens AG, General Electric Company, IBM Corporation, SAP SE, Microsoft Corporation, PTC Inc., Ansys, Inc., Oracle Corporation, Dassault Systems, Robert Bosch, Google
|Unit Denominations||USD Million/Billion|
Consequently, there's a surging inclination of various industries like aviation, automotive, healthcare, logistics, retail, telecom, real estate, and manufacturing, among others, for multiple applications, including but not limited to remote monitoring, factory optimization, & energy management, among others, in order to enhance their overall productivity & efficiency by designing better products while minimizing downtime, thereby driving the digital twin market globally. Several enterprises are actively working on implementing digital twin solutions to optimize their operational workflows & supply chains, which got hampered due to the Covid-19 pandemic. For instance:
Furthermore, the advent of such innovations and the mounting adoption of automation across various end-user verticals are predicted to create new directions for the key companies in the digital twin market to witness significant business growth opportunities over the forecast years.
Key Driver: Rising Penetration of IIoT across Industries
The Industrial Internet of Things (IIoT) is an amalgamation of physical objects, platforms, systems, & applications that consist of embedded technology to communicate, transfer, and share intelligence, consumers, and the external environment. The high adoption rate of IIoT is driven mainly by the affordability & improved availability of sensors, processors, platforms, and other integrated technologies that have helped facilitate access to real-time information.
Besides, to optimize the performance of industrial assets, IIoT platforms are integrated into digital twin models used by many end-user industries to understand the operational behavior of assets before they get installed in real-time. Other applications of digital twin technology using IIoT include product integration, smart monitoring, and remote diagnosis that provide enhanced operational efficiency, high productivity, and the utmost performance of the equipment.
Growth Restraint: Increasing Data Security Risks owing to Rising Use of IoT Sensors
The world is witnessing evolving requirements for digital twin solutions across different industries. However, since the development of these solutions involves the use of multiple IoT sensors & other technologies like Big Data, cloud, Artificial Intelligence, etc., there are globally increasing risks of security, compliance, & data protection, & legislation. Hence, these aspects are hampering the demand for digital twins, owing to rising privacy concerns, especially across data-critical sectors like healthcare, government institutions, etc.
Based on Application:
Of them all, the predictive maintenance application holds a noteworthy share in the global digital twin market. A large number of enterprises operating in different industries, including but not limited to oil & gas, power utilities, etc., are creating predictive maintenance models using digital twin technology to evade failures by real-time monitoring of equipment.
With advancements in the IoT, these models are able to optimize the equipment maintenance cycle, which extends the life of a component/machinery and significantly reduces maintenance activities & costs, and downtime. As a result, there's an increasing demand for digital twin technology across various companies to build predictive maintenance models and achieve dramatic cost savings & strategic developments, i.e., propelling the overall market growth.
Based on End-User:
Here, the manufacturing sector holds a significant share in the Global Digital Twin Market. With the rising need to optimize manufacturing processes by maintaining optimum equipment health & production schedule, there’s a mounting demand for digital transformations in equipment and manufacturing processes. Smart manufacturing is an emerging solution that involves internet-connected equipment that responds in real-time to monitor manufacturing processes in a factory.
Using the digital twin can help optimize the entire manufacturing process through a virtual model of the physical asset, thereby increasing overall productivity. As any disruption in the manufacturing process or unplanned downtime can bring the entire production line to a standstill & introduce substantial losses to businesses, more & more organizations are increasingly deploying digital twin technology within their manufacturing facilities.
Of all regions globally, North America holds a significant share in the Digital Twin Market, with the ever-increasing penetration of digital twin technology, especially in the US & Canada. The region is an early adopter of advanced technologies and home to industry leaders like Google, IBM Corporation, PTC, and Microsoft Corporation, among other companies, who are investing massively in the market.
Several end-user verticals like healthcare, home & commercial, among others, in the US & Canada are increasingly adopting parts twin & products twins, owing to their stated benefits that help enhance the overall productivity & efficiency. Moreover, the well-established IT infrastructure and the increasing prevalence of technologies like AI, IoT, & ML across different industries are also paving the way for the North America Digital Twin Market to expand significantly in the coming years.
Recent Developments in the Global Digital Twin Market
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Frequently Asked Questions
A. The Digital Twin Market is expected to record around 53% CAGR during 2023-28.
A. The rising demand for process optimization across industries like manufacturing, automotive, aviation, energy & utilities, healthcare, & logistics is the prime factor projected to drive the Digital Twin Market during 2023-28.
A. Siemens AG, General Electric Company, IBM Corporation, SAP SE, Microsoft Corporation, PTC Inc., Ansys Inc., Oracle Corporation, Dassault Systems, Robert Bosch, and Google are the key players operating in the Global Digital Twin Market.
A. The ever-increasing risks of data security due to burgeoning use of IoT Sensors might hinder the growth of the Digital Twin Market in the forecast period.
A. The predictive maintenance application would create lucrative prospects for the leading companies in the Digital Twin Market during 2023-28.
A. North America is expected to emerge as a promising region for the Digital Twin Market to witness profitable opportunities over the forecast years.