Digital Twins in Automotive Market By Type (System Digital Twin, Product Digital Twin, Process Digital Twin), By Application (Predictive Maintenance, Business Optimization, Product Design and Development, Others), By Technology (Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), Simulation tools, Others): Global Opportunity Analysis and Industry Forecast, 2023-2032
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.
Key Benefits For StakeholdersThis 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.
Key Market SegmentsBy TypeSystem Digital Twin
Product Digital Twin
Process Digital Twin
By TechnologyInternet of Things (IoT)
Artificial Intelligence (AI)
Machine Learning (ML)
Simulation tools
Others
By ApplicationPredictive Maintenance
Business Optimization
Product Design and Development
Others
By RegionNorth 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.
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