A virtual version of a real-world physical object, procedure, or system that mimics its appearance and behavior is called a digital twin. It builds simulations that forecast the performance of a process or product using real-world data. Organizations can benefit from using digital twins in the following ways: monitoring operations, predictive maintenance, process improvement, simulating situations that would be too costly or time-consuming to test with physical assets, and decision-making.
A virtual representation of a real object is called a digital twin. Throughout the object's lifecycle, it simulates behavior and keeps an eye on processes using real-time data supplied from the object's sensors.
In 2022, the global digital twin market was estimated to be worth USD 10.42 million. It is anticipated to increase at a CAGR of 39.2% over the projected period (2023–2031) to reach USD 204.56 million by 2031.
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Here are the latest trends in digital twins for 2024:
The use of digital twins has increased; as of 2023, 29% of multinational manufacturing organizations had either fully or partially implemented their digital twin strategy, up from 20% in 2020. Comparing October 2023 to two years earlier, the number of job ads citing digital twin climbed by 11%, whereas the majority of other tech-related themes saw a fall in vacancies.
Artificial intelligence (AI) is being used to enable hybrid digital twins, which integrate database analytics with reduced order modeling, and to speed up simulation times. Simulations now run significantly faster than they did with the conventional finite element or finite volume method because to the application of AI and machine learning techniques.
There is a focus on leveraging digital twins to achieve sustainability objectives; 57% of firms view digital twin technology as a key instrument for enhancing sustainability. Digital twins can be used to model sustainable cities, monitor and optimize energy use, evaluate the sustainability of materials used in production, and evaluate the financial and environmental effects of initiatives.
Adoption of cloud-based digital twin platforms to facilitate data access and storage, enhance teamwork, and expedite the creation and maintenance of virtual duplicates. 92% of companies have lately used cloud computing.
Use cases for digital twins are being extended beyond manufacturing to sectors like the automotive industry, where leading producers like GM and BMW mimic crash tests and optimize designs using digital twins and AI. Between 2023 and2027, the global digital twin market is anticipated to expand at a CAGR of 30%.
Benefits of digital twin technology in 2024:
Enhanced Productivity and Efficiency: Organizations can improve decision-making and efficiency by streamlining operations and procedures with the help of digital twins. They can identify problems and lead groups to the appropriate fixes, doing away with the need for speculation. Through the identification of improvement opportunities and the application of data-driven decision-making, digital twins enable firms to optimize the utilization of physical assets.
Lower Expenses and Dangers: Because digital twins minimize downtime and take a proactive approach to maintenance, they assist save operating expenses. Additionally, by simulating and mitigating risks, they help firms find and stop problems that could result in large losses of income. By anticipating potential failures, digital twins expedite the risk assessment process and direct businesses toward better results.
Improved Tracking and Prognostic Data: Digital twins give businesses real-time insights into the behavior and performance of their assets, allowing them to monitor trends, health, and possible failures. This makes it possible to optimize physical objects and processes as well as resolve issues proactively.
Quicker Time-to-Market and Innovation: Digital twins reduce the need for extensive testing by enabling enterprises to immediately evaluate the impact of new systems and products and make necessary adjustments by replicating them. This helps businesses maintain their competitiveness and quickly introduce new products.
Enhanced Ecological and Social Impact: Through modeling and optimization of resource consumption, waste reduction, and energy utilization, digital twins help sustainability initiatives. This encourages a favorable social and environmental impact and aids businesses in meeting their ESG objectives.
Market Segmentation:
As a result of the Digital Twin market segmentation, the market is divided into sub-segments based on product type, application, as well as regional and country-level forecasts.
By Type
Parts Twin
Products Twin
Process Twin
System Twin
By Outlook
Iot And IIot
5G
Big Data Analystics
Blockchain
AI
By End-User
Manufacturing
Agriculture
Automotive and Transport
Energy and Utilities
Healthcare and Life Sciences
Residential and Commercial
Retail and Consumer Goods
Aerospace
Telecommunication
By Solution
Component
Process
System
By Application
Manufacturing Process Planning
Product Design
Top Keyplayers of Digital Twin Market
ABB Group
Amazon Web Services, Inc.
ANSYS, Inc.
Autodesk Inc.
AVEVA Group plc
Bentley Systems Inc.
Dassault Systemes
General Electric
Hexagon AB
International Business Machines Corporation
Microsoft Corporation
PTC Inc.
Robert Bosch GmbH
Rockwell Automation
SAP SE
Siemens AG
Conclusion:
Digital twins are virtual copies of actual systems or objects that are used to simulate operations and optimize workflows with real-time data. Increased output, lower expenses and risks, better tracking and forecasting capabilities, faster time to market, and favorable environmental effects are some of their advantages. The market for digital twins, which was estimated to be worth USD 10.42 million in 2022, is expected to rise rapidly due to advances in artificial intelligence (AI), cloud computing, and their growing range of uses outside of manufacturing. Important players in this market include Siemens, IBM, Microsoft, and other tech giants. The increasing prevalence of digital twins is revolutionizing various sectors by offering crucial insights and promoting efficiency.
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