Digital Twin Market Report Analysis by Type (Product, System, Process), Technology (IoT, AI & ML, Blockchain, Big Data Analytics), Enterprise (Large Enterprises, SMEs), Application (Performance Monitoring, Predictive Maintenance, Product Design & Development, Business Optimization, Inventory Management), Industry (Manufacturing, Automotive, Healthcare, Energy & Utilities, Aerospace & Defense, Oil & Gas) – Global Industry Growth and Demand Forecast to 2030

Market Overview

The global digital twin market estimated size stood at $7,683.4 million in 2022, and it is expected to advance at a compound annual growth rate of 49.9% during 2022–2030, to reach $195,347.6 million by 2030.

The growth can be primarily ascribed to the increasing acceptance of the internet of things (IoT), artificial intelligence (AI), 5G, Industry 4.0, and machine learning (ML) technologies, rising focus of the manufacturing industry on digital twins to lower prices and enhance supply chain operations, growing solution demand in the healthcare sector, and surging preference for cloud services.

Small & Medium Enterprises To Hold Significant Share

The small & medium enterprises category held a significant share in 2022, and, further, it is expected to grow at a CAGR of 52.2% during the forecast period, primarily ascribed to the fast digital transformation. Moreover, the demand for virtual modeling solutions is growing among these enterprises to build better products, predict faults at an early stage, and schedule timely maintenance. This further helps significantly reduce downtime and improve product performance.

Additionally, as digital twins are becoming mainstream, SMEs are shifting their focus toward them to improve product quality and increase efficiency. Moreover, because SMEs employ fewer than 500 employees and generate revenue of less than $100 million a year, they require these solutions to sustain, better their offerings, and gain a competitive edge in the market.

North America Dominates Market due to Increasing Adoption of Advanced Technologies

North America held the largest market share, of 36%, in 2022. This growth is primarily ascribed to the early adoption of advanced technologies, such as IoT, AI, and ML, strong IT infrastructure, and a growing focus on Industry 4.0 standards, primarily in the manufacturing and automotive sectors. As per GSMA Intelligence, IoT revenue in the region is expected to reach $337 billion by the end of 2025, which will be almost thrice the revenue recorded in 2018.

In addition, the North American region has developed economies, where huge funds have been invested in R&D by large automotive & transportation, aerospace & defense, and oil & gas companies.

Product Category Is Expected To Contribute Highest Revenue

The product category generated the highest revenue in 2022, and it is expected to stay on its position in the coming years. This technology helps companies gather information on every aspect of a product, for enhanced visibility and to decrease the mean time between failure (MTBF) and mean time to repair (MTTR). This, in turn, enables enhanced system and cost efficiency and enterprise productivity. Furthermore, virtual modeling is the most-commonly used technology in product design. The investments for aerospace companies in part design and development are rather high, which is why they are using this technology to reduce the cost while creating new designs. Aerospace firms use these solutions to create many critical systems, such as avionics, thermal protection systems, and airframes.

Rising Usage of Common Platform for Multiple Digital Twins

Globally, the key trend being observed in the market is the use of digital twin aggregates for several applications. Organizations managing or monitoring multiple systems of the same type, for instance, a fleet of jet engines, are deploying a common platform for digital twins (with each engine having a separate twin) to gather data from all systems. In such cases, similar patterns and trends are easy to identify and analyze, for the refinement of the systems. By bringing all virtual representations on a common platform, an effective learning system for the physical world can be built. From this concept of building a computerized model of an object before an asset is built and analyzing the data from a cohort of such twins, a powerful digital construct can be developed that can provide important insights to asset-centric organizations.

Widespread Adoption of IoT

The shift to interconnected environments across industries is driving the demand for digital twin solutions across the world. Massive adoption of IoT is being witnessed, with over 41 billion connected IoT devices expected to be in use by 2025. For the successful implementation and functioning of IoT, increasing the throughput for every part, or “thing”, is necessary, which is made possible by this technology. Since the behavior and performance of a system over its lifetime depend on its components, the demand for the technology is increasing across the world for system improvement. Moreover, vendors and product owners are accepting digital representation solutions in order to speed up the time to market and reduce operational costs.

In addition, the emergence of Industry 4.0 and communication channels in smart organizations is propelling the market for digital twins. Hence, organizations adopting IoT are expanding their capabilities with the use of these solutions, to enable advanced simulation, operation, and analysis.

Moreover, data from IoT devices is massive and unstructured, and data sharing between devices from different vendors results in a considerably complex ecosystem of technologies. Thus, for the monitoring of such devices, organizations are preferring the virtualization of the entire process to investing into physical product innovation. The installed base of the associated software is expected to grow to over 500 by 2025. Furthermore, the integration and aggregation of digital twins for specific projects, such as traffic infrastructure, smart buildings, water management, and energy grids, are already resulting in improved outcomes.

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Growing Focus on Intelligent Maintenance

With the growing complexity of manufacturing processes and related machinery, the concept of intelligent maintenance is gaining prominence among the stakeholders. Intelligent maintenance involves the usage of data analysis and decision support tools for predicting and mitigating the potential failure of machines. This system of data collection, storage, analysis, and decision-making for smart maintenance is called the intelligent maintenance system (IMS). The developments in the IT and electronics industries in the last 10 years have encouraged and facilitated the design and implementation of such systems across industries. Thus, for achieving the intelligent maintenance of manufacturing processes and machinery, for optimized asset performance, the use of digital twins is being focused upon.

By leveraging virtual models, sensory data can be combined with historical data, human expertise, and simulation techniques, for improving business outcomes. Digital twins gather information from both cloud and on-premises assets, including cloud integration platforms, enterprise resource planning (ERP) business suites, data management systems, and collaboration asset management and digital innovation platforms.

Moreover, during the historical period, the market for business continuity management, enterprise asset management, ERP, and cloud advanced at a substantial rate, and the same trend is projected for the forecast period. Thus, organizations are heavily adopting advanced measures for mitigating risks and streamlining and optimizing their operations. For instance, Chevron Corporation expects to save several million dollars in maintenance costs from the virtual modeling technology it will have deployed by 2024 on equipment in its oil fields and refineries. Hence, complex prognostics and IMS platforms are necessitating the use of these solutions for improving productivity and identifying potential system issues, thereby catalyzing the market growth.

Key Players in Digital Twin Market Are:

• General Electric Company
• IBM Corporation
• Siemens AG
• Robert Bosch GmbH
• Microsoft Corporation
• Honeywell International Inc.
• Oracle Corporation
• XenonStack Pvt. Ltd.
• PTC Inc.
• Wipro Limited
• Ansys Inc.

Digital Twin Market Size Breakdown by Segment

The study uncovers the biggest trends and opportunities in the market, along with offering segmentation analysis at the granular level for the period 2017 to 2030.

Based on Type

• Product
• System
• Process

Based on Technology

• Internet of Things (IoT)
• Artificial Intelligence (AI) & Machine Learning (ML)
• Blockchain
• Big Data Analytics

Based on Enterprise

• Large Enterprises
• Small & Medium Enterprises (SMEs)

Based on Application

• Performance Monitoring
• Predictive Maintenance
• Product Design & Development
• Business Optimization
• Inventory Management

Based on Industry

• Manufacturing
• Automotive
• Healthcare
• Energy & Utilities
• Aerospace & Defense
• Oil & Gas

Geographical Analysis

• North America
  • U.S.
  • Canada
• Europe
  • Germany
  • U.K.
  • France
  • Italy
  • Spain
• Asia-Pacific
  • Japan
  • China
  • India
  • South Korea
  • Australia
• Latin America
  • Brazil
  • Mexico
• Middle East & Africa
  • U.A.E.
  • Saudi Arabia
  • South Africa