Digital Twin Market Growth Rate Analysis 2020 to 2026
Global Digital Twin Market is poised to gain massive momentum over the projected timeframe of 2020 to 2026. This can be credited to rising adoption for digital twin technologies across various industries for optimizing processes, implementing economical operations and minimizing the time to market. According to Global Market Insights, Inc. report, digital twin market size is projected to surpass USD 35 billion by 2026.
Growing demand
for digital twin for asset management across several enterprises owing to its
ability to provide efficient management, control and simulation for
optimization of asset lifecycles is likely to drive the industry growth
significantly. The technology allows analysis and comparison of historical
performance data with current scenario. Additionally, digital twin utilizes
machine learning algorithms which helps in forecasting performance
requirements.
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Citing an instance, in 2019, Rosendahl Nextrom GmbH, one of the prominent leaders in battery, optical fiber and cable & wire production technologies announced that implementation of digital twin from Siemens for the simulation of systems and processes in a virtual environment enabled them to reduce the time-to-market from 24 months to 12 months. Also, cycle times for an enveloping machine were increased from 140 to 160 plates/minute. The company has further claimed that the system digitization helped them achieve a substantial machine efficiency of 95% coupled with an overall improvement in production output, quality and performance.
The overall digital twin market is fragmented into various segments based on application, end-use and regional landscape.
Based on application bifurcation, machines & equipment health monitoring segment is expected to register a significant growth rate of more than 34% over the analysis timeline, considering the elevating demand for real time equipment analysis and monitoring using IoT. As a result of this, several prominent enterprises are focused on deploying digital twin technology for collecting and analyzing significant equipment data. Moreover, usage of digital twin technology enables companies to obtain optimum business outputs through enhanced asset performance and reduced asset downtime which will substantially drive the industry growth.
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In terms of end-use, automotive segment is projected to observe an exponential growth over the forthcoming years attributing to rising adoption of digital twin technology for providing enhanced design, optimized performance and improved efficiency in the automobiles. Besides, growing preference for ADAD systems and autonomous vehicles has also encouraged the automotive enterprises to incorporate digital twin technologies for creating virtualized model of vehicles and analyzing their operational efficiency.
Speaking of regional landscape, digital twin market in Europe is estimated to acquire a market share of 26% by 2026 considering the growing adoption of IoT/IIoT and digitization across several industry verticals. Moreover, with the rising popularity of digital twin technology in the region, companies are focusing on collaborative approach for the development of solutions based on digital twin technology.
For instance, in May 2020, Atos SE announced its partnership with Siemens AG for developing digital twin solutions for improving production process in pharmaceutical industry. Further, the company has stated that their “Process Digital Twin” technology based on AI, IoT and Advanced analytics is an appropriate solution for improving flexibility and efficiency of the manufacturing process for pharmaceutical products.
Leading
industry players operating in digital twin market such as IBM Corporation,
General Electric, Microsoft Corporation, Dassault Systems, Siemens AG, SAP SE,
etc. are inclined on developing innovative products for strengthening their
product portfolio and their presence in the market. For instance, in 2020,
Microsoft Corporation announced the launch of its latest version of Azure Digital Twin with enhanced capabilities
and features such as OPEN Modeling Language, live execution environment and new
query APIs providing ease of integration with IoT Hub and Azure Services.
Apparently, this product launch would help the organization expand its product
offerings developed using digital twin technology.
Browse key industry insights spread across 221 pages with 256 market
data tables and 35 figures & charts from the report, Digital Twin Market
in detail along with the table of contents:
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Report Content
Chapter
3 Digital Twin Industry Insights
3.1 Introduction
3.2 Industry segmentation
3.3 Impact of COVID-19 outbreak on
digital twin industry
3.3.1 Impact by region
3.3.1.1 North America
3.3.1.2 Europe
3.3.1.3 Asia Pacific
3.3.1.4 LAMEA
3.3.2 Impact on
industry value chain
3.3.3 Impact on
competitive landscape
3.4 Industry ecosystem analysis
3.5 Digital twin evolution
3.6 Digital twin maturity model
3.7 Digital twin conceptual architecture
3.8 Digital twin hierarchy analysis
3.9 Technology & innovation
landscape
3.9.1 Augmented
Reality (AR), Virtual Reality (VR), and Mixed Reality (MR)
3.9.2 Artificial
Intelligence (AI) and Machine Learning (ML)
3.9.3 Internet of
Things (IoT) and Industrial Internet of Things (IIoT)
3.9.4 Blockchain
Technology
3.10 Use cases
3.10.1 Quality management
3.10.2 Logistics planning
3.10.3 Healthcare
3.10.4 Usage-based Insurance (UBI)
3.10.5 Smart cities
3.10.6 Partial optimization of
individual components in industrial plants
3.11 Regulatory landscape
3.11.1 ISO/IEC 270001
3.11.2 Federal Information Security
Management Act (FISMA)
3.11.3 Health Insurance Portability and
Accountability Act (HIPAA)
3.11.4 The General Data Protection
Regulation (GDPR) (EU)
3.11.5 The National Institute of
Standards and Technology (NIST), U.S.
3.12 Industry impact forces
3.12.1 Growth drivers
3.12.1.1 Growing adoption of
IoT, big data analytics, and cloud platform
3.12.1.2 Predominant use of
Industrial IoT for design and manufacturing
3.12.1.3 Growing adoption of
digital twin in Supply Chain Management (SCM)
3.12.1.4 Potential reduction
of time to market, cost efficient operation and elimination of unplanned
downtimes
3.12.1.5 Rapid adoption of
industry 4.0 coupled with increasing demand of connected devices
3.12.1.6 Innovations in the
field of Virtual Reality (VR) and Augmented Reality (AR)
3.12.2 Industry pitfalls and challenges
3.12.2.1 Cybersecurity and
other related risks due to the use of cloud platforms and IoT
3.12.2.2 Limited presence of
skilled workforce & technical knowledge
3.12.2.3 Lack of awareness
related to cost benefits of the adoption of digital twin
3.13 Growth potential analysis
3.14 Porter’s analysis
3.14.1 Bargaining power of suppliers
3.14.2 Bargaining power of buyers
3.14.3 Threat of new entrants
3.14.4 Threat of substitutes
3.15 PESTLE analysis
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