In the automobile sector, digital twins are virtual copies of actual vehicles, procedures, or systems. Digital twins are created in the automotive industry by digitizing or replicating real vehicles, including every part and detail down to the smallest bolt. Because the digital image is meant to be identical to its physical counterpart, the term "twin" is utilized.
In addition, Japanese automobile collaborated with software companies to utilize digital twins for testing of new vehicle. For instance, in May 2022, UD Trucks partnered with PTC Inc. to implement a new data platform, which aims to improve its engineering and supply chain capabilities in the digital era. By partnering with PTC, UD Trucks is projected to enhance its data-sharing infrastructure, enabling the application of digital twin technology to prototype testing. This advancement will facilitate faster identification of issues and allow for prompt modifications and improvements in the development process.
Furthermore, global automotive companies in India adopted digital twin through their subsidiaries to cater to the requirements of the Indian automobile market. For instance, in June 2022, MG Motor India formed a strategic partnership with Siemens AG to harness the power of digital technologies, including the Internet of Things (IoT), data analytics, Plant Simulation, and MindSphere. Siemens AG developed a digital twin of production, a virtual replica of the manufacturing process, which drives improvements in productivity, cost savings, and emissions reduction. Therefore, this region provides numerus opportunity for digital twins in automotive market owing to continuous efforts from automotive companies to adapt the digital twins solutions to improve efficiency.
Moreover, the adoption of machine learning is increasing as software companies integrate ML in their digital twin software for autonomous vehicle development. For instance, in September 2020, Siemens and VSI Labs formed a partnership to accelerate the progress of self-driving car technology. As part of this collaboration, Siemens PAVE360 platform will be utilized to develop digital twin simulations for testing and validating the various processors, electronics, sensors, and systems that are crucial to the VSI Labs Capability Demonstrator. The use of digital twin simulations is expected to enable thorough testing and verification of the AV technology, contributing to its advancement and readiness for real-world deployment.
In addition, AI-powered digital twin is helping in development and testing of EV battery and its supporting system. For instance, in November 2022, Renault, the French automaker joined forces with Google to adopt a software-centric approach in developing its vehicles. Through the utilization of AI, the two companies aim to build a digital twin of a new vehicle. Moreover, the collaboration aims to personalize the user experience by adapting to frequently visited destinations, including electric vehicle charging stations. Therefore, many software and automotive companies increased utilization of AI in digital twin, which drives the growth of the digital twins in automotive market.
Furthermore, IoT is used in automotive digital twins to install sensors, exchange data, monitor and manage products and systems in real-time, provide real-time performance information, integrate with other technologies, provide real-time data, and monitor and model production vehicle fleets. The use of IoT in automotive digital twins can help reduce costs, improve efficiency, and optimize performance.
The global digital twins in automotive market is segmented into type, application, technology, and region. On the basis of type, it is bifurcated into system digital twin, product digital twin, and process digital twin. By Application, it is categorized into predictive maintenance, business optimization, product design & development, and others. On the basis of technology, it is segregated into internet of things (IoT), artificial intelligence (AI), machine learning (ML), simulation tools, and others. Region wise, it is analyzed across North America, Europe, Asia-Pacific, and LAMEA.
Key players profiled in the digital twins in automotive market report include Altair Engineering Inc., ANSYS, Inc, Bosch Rexroth AG, General Electric Company, IBM Corporation, PTC Inc., Rockwell Automation, Inc., SAP SE, Schneider Electric SE., and Siemens.
In addition, Japanese automobile collaborated with software companies to utilize digital twins for testing of new vehicle. For instance, in May 2022, UD Trucks partnered with PTC Inc. to implement a new data platform, which aims to improve its engineering and supply chain capabilities in the digital era. By partnering with PTC, UD Trucks is projected to enhance its data-sharing infrastructure, enabling the application of digital twin technology to prototype testing. This advancement will facilitate faster identification of issues and allow for prompt modifications and improvements in the development process.
Furthermore, global automotive companies in India adopted digital twin through their subsidiaries to cater to the requirements of the Indian automobile market. For instance, in June 2022, MG Motor India formed a strategic partnership with Siemens AG to harness the power of digital technologies, including the Internet of Things (IoT), data analytics, Plant Simulation, and MindSphere. Siemens AG developed a digital twin of production, a virtual replica of the manufacturing process, which drives improvements in productivity, cost savings, and emissions reduction. Therefore, this region provides numerus opportunity for digital twins in automotive market owing to continuous efforts from automotive companies to adapt the digital twins solutions to improve efficiency.
Moreover, the adoption of machine learning is increasing as software companies integrate ML in their digital twin software for autonomous vehicle development. For instance, in September 2020, Siemens and VSI Labs formed a partnership to accelerate the progress of self-driving car technology. As part of this collaboration, Siemens PAVE360 platform will be utilized to develop digital twin simulations for testing and validating the various processors, electronics, sensors, and systems that are crucial to the VSI Labs Capability Demonstrator. The use of digital twin simulations is expected to enable thorough testing and verification of the AV technology, contributing to its advancement and readiness for real-world deployment.
In addition, AI-powered digital twin is helping in development and testing of EV battery and its supporting system. For instance, in November 2022, Renault, the French automaker joined forces with Google to adopt a software-centric approach in developing its vehicles. Through the utilization of AI, the two companies aim to build a digital twin of a new vehicle. Moreover, the collaboration aims to personalize the user experience by adapting to frequently visited destinations, including electric vehicle charging stations. Therefore, many software and automotive companies increased utilization of AI in digital twin, which drives the growth of the digital twins in automotive market.
Furthermore, IoT is used in automotive digital twins to install sensors, exchange data, monitor and manage products and systems in real-time, provide real-time performance information, integrate with other technologies, provide real-time data, and monitor and model production vehicle fleets. The use of IoT in automotive digital twins can help reduce costs, improve efficiency, and optimize performance.
The global digital twins in automotive market is segmented into type, application, technology, and region. On the basis of type, it is bifurcated into system digital twin, product digital twin, and process digital twin. By Application, it is categorized into predictive maintenance, business optimization, product design & development, and others. On the basis of technology, it is segregated into internet of things (IoT), artificial intelligence (AI), machine learning (ML), simulation tools, and others. Region wise, it is analyzed across North America, Europe, Asia-Pacific, and LAMEA.
Key players profiled in the digital twins in automotive market report include Altair Engineering Inc., ANSYS, Inc, Bosch Rexroth AG, General Electric Company, IBM Corporation, PTC Inc., Rockwell Automation, Inc., SAP SE, Schneider Electric SE., and Siemens.
Key Benefits For Stakeholders
- This report provides a quantitative analysis of the market segments, current trends, estimations, and dynamics of the digital twins in automotive market analysis from 2022 to 2032 to identify the prevailing digital twins in automotive market opportunities.
- The market research is offered along with information related to key drivers, restraints, and opportunities.
- Porter's five forces analysis highlights the potency of buyers and suppliers to enable stakeholders make profit-oriented business decisions and strengthen their supplier-buyer network.
- In-depth analysis of the digital twins in automotive market segmentation assists to determine the prevailing market opportunities.
- Major countries in each region are mapped according to their revenue contribution to the global market.
- Market player positioning facilitates benchmarking and provides a clear understanding of the present position of the market players.
- The report includes the analysis of the regional as well as global digital twins in automotive market trends, key players, market segments, application areas, and market growth strategies.
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Key Market Segments
By Type
- System Digital Twin
- Product Digital Twin
- Process Digital Twin
By Technology
- Internet of Things (IoT)
- Artificial Intelligence (AI)
- Machine Learning (ML)
- Simulation tools
- Others
By Application
- Predictive Maintenance
- Business Optimization
- Product Design and Development
- Others
By Region
- North America
- U.S.
- Canada
- Mexico
- Europe
- Germany
- France
- Italy
- UK
- Rest of Europe
- Asia-Pacific
- China
- Japan
- India
- South Korea
- Rest of Asia-Pacific
- LAMEA
- Latin America
- Middle East
- Africa
Key Market Players
- General Electric Company
- Altair Engineering Inc.
- SAP SE
- IBM Corporation
- Schneider Electric SE.
- ANSYS, Inc.
- Rockwell Automation, Inc.
- Siemens
- Bosch Rexroth AG
- PTC Inc.
Table of Contents
CHAPTER 1: INTRODUCTION
CHAPTER 2: EXECUTIVE SUMMARY
CHAPTER 3: MARKET OVERVIEW
CHAPTER 4: DIGITAL TWINS IN AUTOMOTIVE MARKET, BY TYPE
CHAPTER 5: DIGITAL TWINS IN AUTOMOTIVE MARKET, BY APPLICATION
CHAPTER 6: DIGITAL TWINS IN AUTOMOTIVE MARKET, BY TECHNOLOGY
CHAPTER 7: DIGITAL TWINS IN AUTOMOTIVE MARKET, BY REGION
CHAPTER 8: COMPETITIVE LANDSCAPE
CHAPTER 9: COMPANY PROFILES
List of Tables
List of Figures
Executive Summary
The Digital twins in automotive market is expected to experience a significant growth rate of 32.6% from 2023 to 2032 owing to rise in environmental regulations and legislationDigital twins in the automotive industry refer to non-physical replicas or virtual representations of physical objects, such as vehicles or robotic arms. These digital twins provide real-time access to relevant data collected from the physical objects through specific sensors, allowing for a comprehensive view of the system and its environment, including factors such as road conditions, weather, and surrounding objects or systems.
The primary value of utilizing digital twins in the automotive sector lies in conducting simulations. Simulating various scenarios, such as crash tests, autonomous driving, and other situations, may be achieved more easily and cost-effectively in a virtual environment compared to using physical vehicles.
Through analysis and simulation of manufacturing processes, digital twins may enhance production processes. It offers information on resource allocation, workflow optimization, and the effectiveness of production lines. Automotive businesses may optimize production schedules, reduce downtime, and boost overall productivity by locating bottlenecks, reducing cycle times, and improving processes in a virtual environment. This leads to cost savings through improved production cycle. For instance, in March 2023, BMW formed a partnership with Nvidia to develop a digital replica of its upcoming EV factory. This collaboration is highly advantageous, both in terms of cost savings and streamlining operations. The technology being utilized, known as Omniverse, enables BMW to connect its intricate design databases into one comprehensive database. This virtual factory serves as an exact digital twin of future plant of BMW in Debrecen, Hungary, which is expected to manufacture approximately 150,000 vehicles annually starting in 2025. The implementation of this virtual factory is expected to revolutionize manufacturing processes of BMW and pave the way for increased efficiency and productivity.
Moreover, major digital twins provider published the results of survey about adoption of digital twins in the automotive industry. For instance, in May 2023, Altair, a prominent player in the field of computational science and artificial intelligence (AI), has unveiled findings from an autonomous study showcasing the widespread utilization of digital twin technology within the automotive sector. The survey data highlights the automotive industry's prominent position as the second most fervent adopter of digital twin technology across the 11 industries surveyed, surpassed only by the heavy equipment sector. Notably, an impressive 92% of automotive respondents expressed how digital twin technology has significantly contributed to the development of sustainable products and processes within their respective organizations.
Furthermore, the complexity of vehicle systems is increasing significantly in the automotive industry as a result of technological advancements, electrification, and autonomous driving. Simulation tools are essential in modelling and simulating these complex systems, which allow automakers to analyze and optimize performance, safety, and efficiency. As automakers strive to develop and validate innovative technologies, the demand for simulation tools is anticipated to increase significantly.
Moreover, the adoption of machine learning is increasing as software companies integrate ML in their digital twin software for autonomous vehicle development. For instance, in September 2020, Siemens and VSI Labs formed a partnership to accelerate the progress of self-driving car technology. As part of this collaboration, Siemens PAVE360 platform will be utilized to develop digital twin simulations for testing and validating the various processors, electronics, sensors, and systems that are crucial to the VSI Labs Capability Demonstrator.
The global digital twins in automotive market is segmented into type, application, technology, and region. On the basis of type, it is bifurcated into system digital twin, product digital twin, and process digital twin. By Application, it is categorized into predictive maintenance, business optimization, product design & development, and others. On the basis of technology, it is segregated into internet of things (IoT), artificial intelligence (AI), machine learning (ML), simulation tools, and others. Region wise, it is analyzed across North America, Europe, Asia-Pacific, and LAMEA.
Asia-Pacific is a major hub for automotive manufacturing, with countries such as China, Japan, and South Korea being significant players. This manufacturing strength, coupled with the need for operational efficiency and technological advancements, drives the growth of digital twin adoption.
The focus on intelligent transportation systems, smart cities, and connected vehicles of the region presents significant opportunities for digital twin adoption. Digital twins may enable real-time monitoring of traffic, predictive maintenance for vehicles, and optimized routing for logistics operations.
Moreover, as connected and autonomous vehicles become more prevalent, the utilization of digital twins presents promising prospects for enhancing smart transportation systems. Digital twins may facilitate real-time monitoring of vehicle performance, enabling proactive maintenance and the identification of potential issues before they escalate. For instance, in September 2022, China Mobile Research Institute and Rohde & Schwarz formed a partnership to collaborate on research and validation of joint communication and sensing (JCAS) for 6G digital twin simulation in China. In their efforts to advance JCAS technology and prepare it for widespread use, they are expected to utilize Rohde & Schwarz advanced R&S AREG800A automotive radar echo generator as an object simulator in a JCAS testing solution. The R&S AREG800A is specifically designed for scenario generation and functional safety testing of radar-based advanced driver assistance systems (ADAS), autonomous driving, and related applications
The key players profiled in the report include Altair Engineering Inc., ANSYS, Inc, Bosch Rexroth AG, General Electric Company, IBM Corporation, PTC Inc., Rockwell Automation, Inc., SAP SE, Schneider Electric SE., and Siemens.
Key Market Insights
By type, the system digital twin segment was the highest revenue contributor to the market, with $1.2 billion in 2022, and is estimated to reach $20.07 billion by 2032, with a CAGR of 33.2%.By application, the product design and development segment was the highest revenue contributor to the market, with $0.42 billion in 2022, and is estimated to reach $7.25 billion by 2032, with a CAGR of 33.5%.
By technology, the simulation tools segment dominated the global market, and is estimated to reach $13.03 billion by 2032, with a CAGR of 31.8%. However, the artificial intelligence (AI) segment is expected to be the fastest growing segment with a CAGR of 35.9% during the forecast period.
Based on region, North America was the highest revenue contributor, accounting for $0.72 billion in 2022, and is estimated to reach $11.24 billion by 2032, with a CAGR of 32.2%.
Companies Mentioned
- General Electric Company
- Altair Engineering Inc.
- SAP SE
- IBM Corporation
- Schneider Electric SE.
- ANSYS, Inc.
- Rockwell Automation, Inc.
- Siemens
- Bosch Rexroth AG
- PTC Inc.
Methodology
The analyst offers exhaustive research and analysis based on a wide variety of factual inputs, which largely include interviews with industry participants, reliable statistics, and regional intelligence. The in-house industry experts play an instrumental role in designing analytic tools and models, tailored to the requirements of a particular industry segment. The primary research efforts include reaching out participants through mail, tele-conversations, referrals, professional networks, and face-to-face interactions.
They are also in professional corporate relations with various companies that allow them greater flexibility for reaching out to industry participants and commentators for interviews and discussions.
They also refer to a broad array of industry sources for their secondary research, which typically include; however, not limited to:
- Company SEC filings, annual reports, company websites, broker & financial reports, and investor presentations for competitive scenario and shape of the industry
- Scientific and technical writings for product information and related preemptions
- Regional government and statistical databases for macro analysis
- Authentic news articles and other related releases for market evaluation
- Internal and external proprietary databases, key market indicators, and relevant press releases for market estimates and forecast
Furthermore, the accuracy of the data will be analyzed and validated by conducting additional primaries with various industry experts and KOLs. They also provide robust post-sales support to clients.
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