디지털 트윈 시장 : 산업 동향 및 세계 예측(-2035년) - 응용 분야, 트윈 유형, 최종 사용자 및 주요 지역별 분석

Digital Twin Market: Industry Trends and Global Forecasts, till 2035 - Distribution by Application Area, Type of Twin, End Users and Key Geographical Regions

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한글목차

디지털 트윈 시장 규모는 2024년 128억 달러에 이르고, 2024-2035년의 예측 기간 동안 41%의 연평균 성장률(CAGR)로 확대될 것으로 예상됩니다.

디지털 트윈은 실제 사물, 시스템, 프로세스를 가상으로 복제하여 실시간 데이터로 지속적으로 업데이트하여 실제 기능을 모니터링, 분석, 시뮬레이션하는 것을 말합니다. 디지털 트윈은 IoT, AI, 데이터 분석 등의 기술을 활용해 데이터를 수집하고 처리합니다. 디지털 트윈은 제조업, 헬스케어, 운송, 에너지, 인프라 등 다양한 산업 분야에 적용되고 있습니다. 예를 들어, 제조업에서 디지털 트윈은 제품 수명주기 관리, 예지보전, 공정 최적화를 지원하고, 헬스케어에서는 개인 맞춤형 의료, 환자 모니터링, 수술 시뮬레이션을 돕습니다. 마찬가지로 교통 분야에서도 디지털 트윈은 교통 관리와 인프라 유지보수 예측을 돕습니다.

전체적으로 디지털 트윈은 업무 효율성을 높이고, 의사결정을 개선하며, 비용을 절감하는 데 기여합니다. 디지털 트윈은 실제 시나리오를 시각화하고 시뮬레이션하여 이해관계자들이 정보에 입각한 의사결정을 내리고, 위험을 관리하고, 자원 활용을 최적화할 수 있도록 돕습니다. 기술이 발전하고 각 산업이 디지털 솔루션을 채택함에 따라 디지털 트윈 분야는 당분간 큰 성장을 이룰 것으로 예상됩니다.

이 보고서는 세계 디지털 트윈 시장에 대해 조사했으며, 시장 개요와 함께 응용 분야별/트윈 유형별/최종 사용자별/주요 지역별 동향, 시장 진출기업 프로파일 등의 정보를 제공합니다.

목차

제1장 서문

제2장 조사 방법

제3장 경제 및 기타 프로젝트 특유의 고려사항

제4장 주요 요약

제5장 서론

제6장 기업 개요

• 본 장의 개요
• Ansys
• Azure
• Bosch
• Cisco
• Dassault Systemes
• General Electric
• IBM
• Oracle
• Siemens

제7장 특허 분석

제8장 SWOT 분석

제9장 사례 연구 : 디지털 트윈 응용

제10장 세계의 디지털 트윈 시장

• 본 장의 개요
• 전제와 조사 방법
• 세계의 디지털 트윈 시장, 과거 동향(2018년-2023년) 및 예측(2024년-2035년)

제11장 디지털 트윈 시장, 응용 분야별

제12장 디지털 트윈 시장, 트윈 유형별

제13장 디지털 트윈 시장, 최종사용자별

제14장 디지털 트윈 시장, 지역별

제15장 결론

제16장 주요 인사이트

제17장 부록 I 표 형식 데이터

제18장 부록 II 기업 및 단체 리스트

LSH

영문 목차

영문목차

Digital Twin Market: Industry Trends and Global Forecasts, till 2035 - Distribution by Application Area (Business Optimization, Predictive Maintenance, Production Design and Development, and Others), Type of Twin (Parts Twin, Product Twin, Process Twin, and System Twin), End Users (Aerospace and Defense, Automotive and Transportation, Healthcare, Manufacturing, Retail, Energy and Utilities, Real Estate, IT and Telecommunication, and Others) and Key Geographical Regions (North America, Europe, Asia, Latin America, Middle East and North Africa, and Rest of the World)

The Digital Twin Market is valued at USD 12.8 billion in 2024 growing at a CAGR of 41% during the forecast period 2024-2035.

Digital twins are virtual replicas of physical objects, systems, or processes that are continuously updated with real-time data to monitor, analyze, or simulate real-world functions. These digital counterparts utilize technologies like IoT, AI, and data analytics to collect and process data. They find applications across various industries such as manufacturing, healthcare, transportation, energy, and infrastructure. For example, in manufacturing, digital twins support product lifecycle management, predictive maintenance, and process optimization, while in healthcare, they assist in personalized medicine, patient monitoring, and surgical simulation. Similarly, in transportation, digital twins aid in traffic management and infrastructure maintenance prediction.

Overall, digital twins contribute to improved operational efficiency, better decision-making, and cost savings. They empower stakeholders to make informed decisions, manage risks, and optimize resource utilization by providing visualizations and simulations of real-world scenarios. As technology advances and industries embrace digital solutions, the digital twins domain is poised for significant growth in the foreseeable future.

Key Market Segments

Application Area

• Business Optimization
• Predictive Maintenance
• Production Design and Development
• Others

Type of Twin

• Parts Twin
• Product Twin
• Process Twin
• System Twin

End Users

• Aerospace and Defense
• Automotive and Transportation
• Energy and Utilities
• Healthcare
• IT and Telecommunication
• Manufacturing
• Real Estate
• Retail
• Others

Key Geographical Regions

• North America
• Europe
• Asia
• Latin America
• Middle East and North America
• Rest of the World

Research Coverage:

• An overview is provided on key concepts pertaining to digital twins, encompassing different types of digital twins and their primary applications across diverse domains. Additionally, the chapter highlights recent advancements within this market space.
• In-depth profiles are presented for several notable digital twin companies. Each profile includes a comprehensive overview of the company, covering details such as its establishment year, employee count, headquarters location, and key members of the executive team. Financial information, if available, is also provided to offer insights into the company's financial standing. Furthermore, the profiles delve into recent developments within each company, highlighting significant milestones, partnerships, or innovations. Additionally, an informed future outlook is provided, offering perspectives on the company's trajectory and potential growth prospects in the digital twin market.
• A thorough analysis is conducted on patents filed or granted related to digital twins from 2020, considering several pertinent parameters. These parameters include the type of patent (granted patents, patent applications, and others), publication year, geographical region of origin, CPC symbols, leading industry players based on the number of patents filed or granted, and patent valuation. This analysis offers valuable insights into the patent landscape surrounding digital twins and highlights notable trends, key players, and potential areas of innovation within the field.
• An exploration is conducted on associated trends, key drivers, and challenges within the digital twin industry, utilizing a SWOT framework. This discussion aims to identify factors likely to influence the industry's evolution. Additionally, a Harvey ball analysis is employed to depict the relative impact of each SWOT parameter on the overall digital twin industry, providing a visual representation of their significance.
• A concise case study is presented, illustrating the application of digital twins across diverse industries including aerospace and defense, automotive and transportation, healthcare, energy and utilities, real estate, and IT and telecommunication. This chapter showcases success stories of digital twin technologies in these domains, highlighting their impact and benefits.
• A comprehensive analysis is conducted to estimate the current market size, existing opportunity, and future growth potential of the digital twin market over the next decade. Drawing on various parameters including likely adoption trends and revenue generation, an informed estimate is provided for the market evolution during the forecast period from 2024 to 2035. The report also outlines the expected distribution of current and forecasted opportunities within the digital twin industry. To address future uncertainties and enhance the robustness of our model, three forecast scenarios are presented: conservative, base, and optimistic scenarios, each representing different trajectories of industry growth.
• Thorough projections are presented for both the current and future market sizes across various types of application areas within the digital twin industry. These areas include business optimization, predictive maintenance, production design and development, among others.
• Comprehensive projections are provided for the current and future digital twins market across various types of twins, including parts twin, product twin, process twin, and system twin.
• Thorough projections are outlined for the current and future digital twin market across various types of end users, encompassing sectors such as aerospace and defense, automotive and transportation, energy and utilities, healthcare, IT and telecommunication, manufacturing, real estate, retail, and others.
• Comprehensive projections of the current and future digital twin industry across various geographies, such as North America (US, Canada), Europe (Austria, Denmark, France, Germany, Ireland, Italy, Norway, Spain, Sweden, UK, Rest of Europe), Asia (China, India, Indonesia, Japan, Malaysia, Singapore, South Korea, Rest of Asia), Latin America (Brazil, Chile, Colombia, Mexico, Paraguay, Peru, Portugal, Rest of Latin America), Middle East and North Africa (Egypt, Jordan, Kenya, Mauritania, Morocco, Saudi Arabia, South Africa, UAE, Rest of Middle East and North Africa) and Rest of the World (Australia, New Zealand).

Key Benefits of Buying this Report

• The report offers market leaders and newcomers valuable insights into revenue estimations for both the overall market and its sub-segments.
• Stakeholders can utilize the report to enhance their understanding of the competitive landscape, allowing for improved business positioning and more effective go-to-market strategies.
• The report provides stakeholders with a pulse on the Digital Twin Market, furnishing them with essential information on significant market drivers, barriers, opportunities, and challenges.

Leading Market Companies

• Ansys
• Azure
• Bosch
• Cisco
• Dassault Systemes
• General Electric

IBM

• Oracle
• Siemens

TABLE OF CONTENTS

Table Of Contents

1. PREFACE

• 1.1. Digital Twin Market: Market Overview
• 1.2. Market Share Insights
• 1.3. Market Segmentation Overview
• 1.4. Key Market Insights
• 1.5. Report Coverage
• 1.6. Key Questions Answered
• 1.7. Chapter Outlines

2. RESEARCH METHODOLOGY

• 2.1. Chapter Overview
• 2.2. Research Assumptions
• 2.3. Project Methodology
• 2.4. Forecast Methodology
• 2.5. Robust Quality Control
• 2.6. Key Market Segmentations
• 2.7. Key Considerations
  • 2.7.1. Demographics
  • 2.7.2. Economic Factors
  • 2.7.3. Government Regulations
  • 2.7.4. Supply Chain
  • 2.7.5. COVID Impact / Related Factors
  • 2.7.6. Market Access
  • 2.7.7. Regulatory Policies
  • 2.7.8. Industry Consolidation

3. ECONOMIC AND OTHER PROJECT SPECIFIC CONSIDERATIONS

• 3.1. Chapter Overview
• 3.2. Market Dynamics
  • 3.2.1. Time Period
    • 3.2.1.1. Historical Trends
    • 3.2.1.2. Current and Forecasted Estimates
  • 3.2.2. Currency Coverage
    • 3.2.2.1. Overview of Major Currencies Affecting the Market
    • 3.2.2.2. Impact of Currency Fluctuations on the Industry
  • 3.2.3. Foreign Exchange Impact
    • 3.2.3.1. Evaluation of Foreign Exchange Rates and their Impact on Market
    • 3.2.3.2. Strategies for Mitigating Foreign Exchange Risk
  • 3.2.4. Recession
    • 3.2.4.1. Historical Trends Analysis of Past Recessions and Lessons Learnt
    • 3.2.4.2. Assessment of Current Economic Conditions and Potential Impact on the Market
  • 3.2.5. Inflation
    • 3.2.5.1. Measurement and Analysis of Inflationary Pressures in the Economy
    • 3.2.5.2. Potential Impact of Inflation on the Market Evolution

4. EXECUTIVE SUMMARY

5. INTRODUCTION

• 5.1. Chapter Overview
• 5.2. Overview of Digital Twins
• 5.3. Types of Digital Twins
  • 5.3.1. Parts Twin
  • 5.3.2 Product Twin
  • 5.3.3 System Twin
  • 5.3.4. Process Twin
• 5.4. Applications of Digital Twins
• 5.5. Challenges Associated with the Adoption of Digital Twins
• 5.6. Concluding Remarks

6. COMPANY PROFILES

• 6.1. Chapter Overview
• 6.2. Ansys
  • 6.2.1. Company Overview
  • 6.2.2. Financial Information
  • 6.2.3. Recent Developments and Future Outlook
• 6.3. Azure
  • 6.3.1. Company Overview
  • 6.3.2. Financial Information
  • 6.3.3. Recent Developments and Future Outlook
• 6.4. Bosch
  • 6.4.1. Company Overview
  • 6.4.2. Financial Information
  • 6.4.3. Recent Developments and Future Outlook
• 6.5. Cisco
  • 6.5.1. Company Overview
  • 6.5.2. Financial Information
  • 6.5.3. Recent Developments and Future Outlook
• 6.6. Dassault Systemes
  • 6.6.1. Company Overview
  • 6.6.2. Financial Information
  • 6.6.2. Recent Developments and Future Outlook
• 6.7. General Electric
  • 6.7.1. Company Overview
  • 6.7.2. Financial Information
  • 6.7.2. Recent Developments and Future Outlook
• 6.8. IBM
  • 6.8.1. Company Overview
  • 6.8.2. Financial Information
  • 6.8.2. Recent Developments and Future Outlook
• 6.9. Oracle
  • 6.9.1. Company Overview
  • 6.9.2. Financial Information
  • 6.9.2. Recent Developments and Future Outlook
• 6.10. Siemens
  • 6.10.1. Company Overview
  • 6.10.2. Financial Information
  • 6.10.2. Recent Developments and Future Outlook

7. PATENT ANALYSIS

• 7.1. Chapter Overview
• 7.2. Scope and Methodology
• 7.3. Digital Twins: Patent Analysis
  • 7.3.1. Analysis by Patent Publication Year
  • 7.3.2. Analysis by Patent Application Year
  • 7.3.3. Analysis by Patent Jurisdiction
  • 7.3.4. Analysis by Type of Player
  • 7.3.5. Analysis by CPC Symbols
  • 7.3.6. Leading Industry Players: Analysis by Number of Patents
  • 7.3.7. Leading Non-Industry Players: Analysis by Number of Patents
  • 7.3.8. Leading Individual Assignees: Analysis by Number of Patents
  • 7.3.9. Patent Benchmarking Analysis
    • 7.3.9.1. Analysis by Patent Characteristics
    • 7.3.9.2. Patent Valuation
    • 7.3.9.3. Leading Patents by Number of Citations

8. SWOT ANALYSIS

• 8.1. Chapter Overview
• 8.2. Strengths
• 8.3. Weaknesses
• 8.4. Opportunities
• 8.5. Threats
• 8.6. Comparison of SWOT Factors

9. CASE STUDY: APPLICATIONS OF DIGITAL TWINS

• 9.1. Chapter Overview
• 9.2. Digital Twins: Applications Across Domains
  • 9.2.1. Aerospace and Defense
    • 9.2.1.1. Key Applications
    • 9.2.1.2. Success Stories
  • 9.2.2. Automotive and Transportation
    • 9.2.2.1. Key Applications
    • 9.2.2.2. Success Stories
  • 9.2.3. Healthcare
    • 9.2.3.1. Key Applications
    • 9.2.3.2. Success Stories
  • 9.2.4. Energy and Utilities
    • 9.2.4.1. Key Applications
    • 9.2.4.2. Success Stories
  • 9.2.5. Real Estate
    • 9.2.5.1. Key Applications
    • 9.2.5.2. Success Stories
  • 9.2.6. IT and Telecommunication
    • 9.2.6.1. Key Applications
    • 9.2.6.2. Success Stories
• 9.3. Concluding Remarks

10. GLOBAL DIGITAL TWIN MARKET

• 10.1. Chapter Overview
• 10.2. Assumptions and Methodology
• 10.3. Global Digital Twin Market, Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
  • 10.3.1. Scenario Analysis
    • 10.3.1.1. Conservative Scenario
    • 10.3.1.2. Optimistic Scenario
  • 10.3.2. Key Market Segmentations

11. DIGITAL TWIN MARKET, BY APPLICATION AREA

• 11.1. Chapter Overview
• 11.2. Assumptions and Methodology
• 11.3. Digital Twin Market: Distribution by Application Area, 2018, 2024 and 2035
  • 11.3.1. Business Optimization: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
  • 11.3.2. Predictive Maintenance: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
  • 11.3.3. Production Design and Development: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
  • 11.3.4. Other Application Areas: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
  • 11.3.5. Data Triangulation and Validation

12. DIGITAL TWIN MARKET, BY TYPE OF TWIN

• 12.1. Chapter Overview
• 12.2. Assumptions and Methodology
• 12.3. Digital Twin Market: Distribution by Type of Digital Twins, 2018, 2024 and 2035
  • 12.3.1. Parts Twin: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
  • 12.3.2. Product Twin: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
  • 12.3.3. Process Twin: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
  • 12.3.4. System Twin: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
  • 12.3.5. Data Triangulation and Validation

13. DIGITAL TWIN MARKET, BY END USERS

• 13.1. Chapter Overview
• 13.2. Assumptions and Methodology
• 13.3. Digital Twin Market: Distribution by End Users, 2018, 2024 And 2035
  • 13.3.1. Aerospace and Defense: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
  • 13.3.2. Automotive and Transportation: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
  • 13.3.3. Energy and Utilities: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
  • 13.3.4 Healthcare: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
  • 13.3.5. IT and Telecommunication: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
  • 13.3.6. Manufacturing: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
  • 13.3.7. Real Estate: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
  • 13.3.8. Retail: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
  • 13.3.9. Other End Users: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
  • 13.3.10. Data Triangulation and Validation

14. DIGITAL TWIN MARKET, BY GEOGRAPHY

• 14.1. Chapter Overview
• 14.2. Assumptions and Methodology
• 14.3. Digital Twins Market: Distribution by Key Geographies, 2018, 2024 And 2035
  • 14.3.1. North America: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.1.1. US: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.1.2. Canada: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
  • 14.3.2. Europe: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.2.1. Austria: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.2.2. Denmark: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.2.3. France: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.2.4. Germany: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.2.5. Ireland: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.2.6. Italy: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.2.7. Norway: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.2.8. Spain: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.2.9. Sweden: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.2.10. UK: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.2.11. Rest of Europe: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
  • 14.3.3. Asia: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.3.1. China: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.3.2. India: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.3.3. Indonesia: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.3.4. Japan: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.3.5. Malaysia: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.3.6. Singapore: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.3.7. South Korea: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.3.8. Rest of Asia: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
  • 14.3.4. Latin America: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.4.1. Brazil: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.4.2. Chile: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.4.3. Colombia: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.4.4. Mexico: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.4.5. Paraguay: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.4.6. Peru: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.4.7. Portugal: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.4.8. Rest of Latin America: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
  • 14.3.5. Middle East and North Africa: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.5.1. Egypt: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.5.2. Jordan: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.5.3. Kenya: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.5.4. Mauritania: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.5.5. Morocco: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.5.6. Saudi Arabia: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.5.7. South Africa: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.5.8. UAE: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.5.9. Rest of Middle East and North Africa: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
  • 14.3.10. Rest of the World: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.10.1. Australia: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
    • 14.3.10.2. New Zealand: Historical Trends (2018-2023) and Forecasted Estimates (2024-2035)
  • 14.3.11. Data Triangulation and Validation

15. CONCLUSION

16. EXECUTIVE INSIGHTS

• 16.1. Chapter Overview
• 16.2. Company 1
  • 16.2.1. Company Snapshot
  • 16.2.2. Interview Transcript: Key Executive 1
• 16.3. Company 2
  • 16.3.1. Company Snapshot
  • 16.3.2. Interview Transcript: Key Executive 2
• 16.4. Company 3
  • 16.4.1. Company Snapshot
  • 16.4.2. Interview Transcript: Key Executive 3

17. APPENDIX I: TABULATED DATA

18. APPENDIX II: LIST OF COMPANIES AND ORGANIZATIONS

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