数位孪生市场：技术、孪生类型、网路到实体解决方案、用例、产业、应用（2024-2029）

本报告对全球数位孪生市场进行了调查，概述了数位孪生产品和服务，包括数位孪生技术、解决方案、用例、研发、领先企业的初步实施努力评估以及应用开发和营运。行业的用例。我们也分析了支持数位孪生并从中受益的技术。此外，我们还提供了 2024 年至 2029 年跨多个细分市场和用例的数位孪生解决方案的详细预测，包括製造模拟和预测分析，以及全球、区域和主要国家的预测。

主要报告结果

• 47% 的 IT 决策者不瞭解数位孪生
• 到 2029 年，智慧城市的数位孪生解决方案将达到 59 亿美元
• 到 2029 年，超过 95% 的物联网平台将具备某种数位孪生功能
• 数位孪生将成为物联网应用支援的标准功能/功能
• 主要的数位孪生解决方案包括资产孪生、组件孪生、系统孪生、流程孪生、工作流孪生
• 96.5% 的供应商认识到 IIoT API 和平台与工业数位孪生功能整合的需求
• 47.2% 的各行业主管瞭解数位孪生的优势，其中 63% 的高阶主管计划在 2029 年将其纳入营运中

依行业划分的数位孪生技术：

数位孪生技术正在被各个行业采用，因为它可以创建实体资产、系统和流程的虚拟副本。以下是利用数位孪生的主要行业的范例。

製造业

• 预测性维护：监控设备以预测故障并安排维护
• 流程最佳化：简化并提高製造流程的效率
• 产品生命週期管理：追踪产品从设计到生产结束的整个流程

医疗保健

• 患者监控：创建患者的数位复製品以进行个人化治疗
• 医疗设备管理：医疗设备模拟与效能最佳化
• 医院管理：加强医院运作和病患流动

汽车/交通

• 车辆设计和测试：新车设计的模拟和性能测试
• 车队管理：监控和优化车队性能
• 智慧基础设施：智慧城市基础设施和车辆集成，以实现更好的交通管理

能源/公用事业

• 电网管理：配电网路监控与最佳化
• 资产管理：追踪和管理风力涡轮机和太阳能电池板等能源资产
• 预测性维护：防止关键基础设施故障

航空航太/国防

• 飞机设计与维护：模拟飞机性能并预测维修需求
• 任务规划：优化防御行动与任务规划
• 训练模拟：提供士兵真实的训练环境

房地产/建筑业

• 建筑资讯建模：创建建筑物的详细数字表示
• 施工专案管理：施工过程的监控与最佳化
• 设施管理：加强楼宇管理与运营

零售/消费品

• 供应链优化：提高供应链效率与反应能力
• 客户体验：基于消费者行为的数位复製品来个人化客户体验
• 库存管理：改进库存追踪和管理

智慧城市

• 城市规划：城市基础设施和服务的模拟和最佳化
• 公共安全：加强紧急应变和保全措施
• 永续发展：监控和管理环境影响和能源使用

沟通

• 网路优化：监控和优化通讯网路以提高效能
• 服务管理：加强对电信服务和客户体验的控制
• 基础设施管理：追踪和维护通讯基础设施

目录

第1章 内容提要

第2章 简介

• 概述
• 相关技术及对数位孪生的影响
  • 工业互联网与工业4.0
  • 配对技术
  • 网路实体系统
  • 扩增实境/虚拟实境/混合现实
  • 人工智慧和机器学习
  • 积层製造/3D列印
• 潜在用途和后果分析
  • MRO（维修/修理/大修）
  • 消费者资产的数位化身
  • 效能/服务监控
  • 检查/维修
  • 预测性维护
  • 产品设计/开发
  • 复合材料组装/製造
  • 潜在的业务成果
• 数位孪生服务生态系统
  • 物联网
  • 消费者物联网
  • 产业发展
  • Digital Twinning as a Service

第三章 数位孪生企业评价

• ABB
• Allerin Tech Pvt. Ltd.
• Altair Engineering, Inc.
• Amazon Web Services
• ANSYS
• Aucotec AG
• Autodesk Inc.
• Bentley Systems, Incorporated
• CADFEM GmbH
• Cisco Systems
• Cityzenith
• Cosmo Tech
• Dassault Systems
• Digital Twin Consortium
• Digital Twin Technologies
• DNV GL
• DXC Technology
• Eclipse Foundation
• Emerson
• Emesent
• Faststream Technologies
• FEINGUSS BLANK GmbH
• Flowserve
• Forward Networks
• General Electric
• Google
• Hitachi Ltd.
• Honeywell
• HP
• IBM
• Industrial Internet Consortium
• Intellias
• Invicara
• KBMax
• Lanner Electronics
• Microsoft
• National Instruments
• NavVis
• Oracle
• PETRA Data Science
• Physical Web
• Pratiti Technologies
• Prodea System Inc.
• PTC
• QiO Technologies
• Robert Bosch
• SAP
• Schneider
• SenSat
• Siemens
• Sight Machine Inc.
• Simplifa GmbH
• Softweb Solutions Inc.
• Sogeti Group
• SWIM.AI
• Synavision
• Sysmex Corporation
• TIBCO Software
• Toshiba Corporation
• UrsaLeo
• Virtalis Limited
• Visualiz
• Wipro Limited
• XenonStack
• Zest Labs

第4章 数位孪生市场分析与预测

• 全球数位孪生市场趋势及预测
• 数位孪生市场：依孪生类型
• 数位孪生的应用
• 数位孪生市场：依行业分类
  • 製造：依类型
  • 智慧城市：依类型
  • 汽车：依类型
  • 医疗：依类型
  • 交通：依类型
• 数位孪生市场：依地区
  • 北美
  • 南美洲
  • 欧洲
  • 亚太地区
  • 中东/非洲

第5章 一般性意见/建议

Overview:

This report evaluates digital twinning technology, solutions, use cases, and leading company efforts in terms of R&D and early deployments. The report assesses the digital twin product and service ecosystem including application development and operations. This includes consideration of use cases by industry vertical.

The report also analyzes technologies supporting and benefiting from digital twinning. The report also provides detailed forecasts covering digital twinning solutions in many market segments and use cases including manufacturing simulations, predictive analytics, and more from 2024 to 2029 with global, regional, and major country forecasts.

Select Report Findings:

• We found 47% of IT decision makers have never heard of digital twins
• Digital twin supported solutions in smart cities will reach $5.9 billion by 2029
• Over 95% of all IoT Platforms will contain some form of digital twinning capability by 2029
• Digital twinning will become standard feature/functionality for IoT Application Enablement by 2028
• Leading digital twin solutions involve Asset Twinning, Component Twinning, System Twinning, Process and Workflow Twinning
• 96.5% of vendors recognize the need for IIoT APIs and platform integration with digital twinning functionality for industrial verticals
• 47.2% of executives across a broad spectrum of industry verticals understand the benefits of digital twinning and 63% of them plan to incorporate within their operations by 2029

A digital twin is a virtual object representation of a real-world item in which the virtual is mapped to physical things in the real world such as equipment, robots, or virtually any connected business asset. This mapping in the digital world is facilitated by IoT platforms and software that is leveraged to create a digital representation of the physical asset.

The digital twin of a physical asset can provide data about its status such as its physical state and disposition. Conversely, a digital object may be used to manipulate and control a real-world asset by way of teleoperation. The publisher of this report sees this form of cyber-physical connectivity, signaling, and control as a key capability to realize the vision for Industry 4.0 to fully digitize production, servitization, and the `as a service` model for products.

There are many potential use cases for digital twinning including monitoring, simulation, and remote control of physical assets with virtual objects. Solutions focus on Part, Product, Process, and System twinning. Leading digital twin solutions involve Asset Twinning, Component Twinning, System Twinning, Process and Workflow Twinning. We see digital twinning playing a key role in many related IoT operations processes including IoT application development, testing, and control.

The implementation of digital twins will also enable distributed remote control of assets, which will place an increasingly heavy burden on IoT Identity management, authentication, and authorization. IoT authentication market solutions are also important in support of the "things" involved in IoT, which vary from devices used to detect, actuate, signal, engage, and more. This will become particularly important with respect to digital twin solution integration.

As reflected by the Digital Twin Consortium, we see some of the key industries to lead cyber-to-physical integration and solutions include aerospace, healthcare, manufacturing, military, natural resources, and public safety sectors. In terms of integrating digital twin technology and solutions with telecommunications and enterprise infrastructure, we see a need for careful planning from a systems integration, testing, and implementation perspective. This will be especially important in the case of mission-critical applications.

Digital Twins Technology in Industry Verticals

The technology is being increasingly adopted across a variety of industry verticals due to its ability to create virtual replicas of physical assets, systems, or processes. Here are some key industry verticals leveraging digital twins:

Manufacturing:

• Predictive Maintenance: Monitoring equipment to predict failures and schedule maintenance
• Process Optimization: Streamlining production processes and improving efficiency
• Product Lifecycle Management: Tracking products from design to end-of-life

Healthcare:

• Patient Monitoring: Creating digital replicas of patients for personalized treatment
• Medical Device Management: Simulating and optimizing the performance of medical devices
• Hospital Management: Enhancing hospital operations and patient flow

Automotive and Transportation:

• Vehicle Design and Testing: Simulating new vehicle designs and testing performance
• Fleet Management: Monitoring and optimizing the performance of vehicle fleets
• Smart Infrastructure: Integrating vehicles with smart city infrastructure for better traffic management

Energy and Utilities:

• Power Grid Management: Monitoring and optimizing power distribution networks
• Asset Management: Tracking and managing energy assets such as wind turbines and solar panels
• Predictive Maintenance: Preventing failures in critical infrastructure

Aerospace and Defense:

• Aircraft Design and Maintenance: Simulating aircraft performance and predicting maintenance needs
• Mission Planning: Optimizing defense operations and mission planning
• Training Simulations: Providing realistic training environments for personnel

Real Estate and Construction:

• Building Information Modeling: Creating detailed digital representations of buildings
• Construction Project Management: Monitoring and optimizing construction processes
• Facility Management: Enhancing the management and operation of buildings

Retail and Consumer Goods:

• Supply Chain Optimization: Enhancing supply chain efficiency and responsiveness
• Customer Experience: Personalizing customer experiences based on digital replicas of consumer behavior
• Inventory Management: Improving inventory tracking and management

Smart Cities:

• Urban Planning: Simulating and optimizing city infrastructure and services
• Public Safety: Enhancing emergency response and public safety measures
• Sustainability: Monitoring and managing environmental impact and energy usage

Telecommunications:

• Network Optimization: Monitoring and optimizing telecom networks for better performance
• Service Management: Enhancing the management of telecom services and customer experience
• Infrastructure Management: Tracking and maintaining telecom infrastructure

These are just a few examples, and the applications of digital twins are continuously expanding as technology advances and more industries recognize the potential benefits.

Companies in Report:

Table of Contents

1.0. Executive Summary

2.0. Introduction

• 2.1. Overview
  • 2.1.1. Understanding Digital Twinning
  • 2.1.2. Cognitive Digital Twining
  • 2.1.3. Digital Thread
  • 2.1.4. Convergence of Sensors and Simulations
  • 2.1.5. IoT APIs
  • 2.1.6. Software Modules and Elements
  • 2.1.7. Types of Digital Twinning
  • 2.1.8. Digital Twinning Work Processes
  • 2.1.9. Role and Importance of Digital Twinning
• 2.2. Related Technologies and Impact on Digital Twinning
  • 2.2.1. Industrial Internet and Industry 4.0
  • 2.2.2. Pairing Technology
  • 2.2.3. Cyber-to-Physical Systems
  • 2.2.4. AR, VR, and Mixed Reality
  • 2.2.5. Artificial Intelligence and Machine Learning
  • 2.2.6. Additive Manufacturing and 3D Printing
• 2.3. Potential Application and Outcome Analysis
  • 2.3.1. Maintenance, Repair and Overhaul Operation
  • 2.3.2. Digital Avatar of Consumer Assets
  • 2.3.3. Performance/Service Monitoring
  • 2.3.4. Inspection and Repairs
  • 2.3.5. Predictive Maintenance
  • 2.3.6. Product Design & Development
  • 2.3.7. Composite Assembling/Manufacturing
  • 2.3.8. Potential Business Outcomes
• 2.4. Digital Twinning Service Ecosystem
  • 2.4.1. Industrial IoT
  • 2.4.2. Consumer IoT
  • 2.4.3. Industry Development
  • 2.4.4. Digital Twinning as a Service

3.0. Digital Twins Company Assessment

• 3.1. ABB
• 3.2. Allerin Tech Pvt. Ltd.
• 3.3. Altair Engineering, Inc.
• 3.4. Amazon Web Services
• 3.5. ANSYS
• 3.6. Aucotec AG
• 3.7. Autodesk Inc.
• 3.8. Bentley Systems, Incorporated
• 3.9. CADFEM GmbH
• 3.10. Cisco Systems
• 3.11. Cityzenith
• 3.12. Cosmo Tech
• 3.13. Dassault Systems
• 3.14. Digital Twin Consortium
• 3.15. Digital Twin Technologies
• 3.16. DNV GL
• 3.17. DXC Technology
• 3.18. Eclipse Foundation
• 3.19. Emerson
• 3.20. Emesent
• 3.21. Faststream Technologies
• 3.22. FEINGUSS BLANK GmbH
• 3.23. Flowserve
• 3.24. Forward Networks
• 3.25. General Electric
• 3.26. Google
• 3.27. Hitachi Ltd.
• 3.28. Honeywell
• 3.29. HP
• 3.30. IBM
• 3.31. Industrial Internet Consortium
• 3.32. Intellias
• 3.33. Invicara
• 3.34. KBMax
• 3.35. Lanner Electronics
• 3.36. Microsoft
• 3.37. National Instruments
• 3.38. NavVis
• 3.39. Oracle
• 3.40. PETRA Data Science
• 3.41. Physical Web
• 3.42. Pratiti Technologies
• 3.43. Prodea System Inc.
• 3.44. PTC
• 3.45. QiO Technologies
• 3.46. Robert Bosch
• 3.47. SAP
• 3.48. Schneider
• 3.49. SenSat
• 3.50. Siemens
• 3.51. Sight Machine Inc.
• 3.52. Simplifa GmbH
• 3.53. Softweb Solutions Inc.
• 3.54. Sogeti Group
• 3.55. SWIM.AI
• 3.56. Synavision
• 3.57. Sysmex Corporation
• 3.58. TIBCO Software
• 3.59. Toshiba Corporation
• 3.60. UrsaLeo
• 3.61. Virtalis Limited
• 3.62. Visualiz
• 3.63. Wipro Limited
• 3.64. XenonStack
• 3.65. Zest Labs

4.0. Digital Twins Market Analysis and Forecasts 2024 to 2029

• 4.1. Global Digital Twins 2024-2029
• 4.2. Digital Twins Market by Type of Twinning 2024-2029
• 4.3. Digital Twins Applications 2024-2029
• 4.4. Digital Twins by Industry 2024-2029
  • 4.4.1. Digital Twins in Manufacturing by Type 2024-2029
  • 4.4.2. Digital Twins in Smart City by Type 2024-2029
  • 4.4.3. Digital Twins in Automotive by Type 2024-2029
  • 4.4.4. Digital Twins in Healthcare by Type 2024-2029
  • 4.4.5. Digital Twins in Transport by Type 2024-2029
• 4.5. Digital Twins by Region 2024-2029
  • 4.5.1. North America Digital Twins 2024-2029
  • 4.5.2. South America Digital Twins 2024-2029
  • 4.5.3. Europe Digital Twins 2024-2029
  • 4.5.4. APAC Digital Twins 2024-2029
  • 4.5.5. MEA Digital Twins 2024-2029

5.0. Conclusions and Recommendations

Figures

• Figure 1: Digital Twinning Model
• Figure 2: Building Blocks of Cognitive Digital Twinning
• Figure 3: Digital Thread Model in Digital Manufacturing Transformation Processes
• Figure 4: Example of Types of Digital Twinning
• Figure 5: Industrial Internet Building Block and Digital Twinning
• Figure 6: Additive Manufacturing Path and Goals
• Figure 7: Digital Thread for Additive Manufacturing in AM Process
• Figure 8: Data Fusion for MRO Operation
• Figure 9: Composite Manufacturing Model
• Figure 10: Digital Twinning Application and Outcomes
• Figure 11: Global Digital Twins 2024 - 2029
• Figure 12: Digital Twins Types 2024 - 2029
• Figure 13: Digital Twins Applications 2024 - 2029
• Figure 14: Digital Twins by Industry 2024 - 2029
• Figure 15: Digital Twins in Manufacturing by Type 2024 - 2029
• Figure 16: Digital Twins in Manufacturing by Application 2024 - 2029
• Figure 17: Digital Twins in Smart City by Type 2024 - 2029
• Figure 18: Digital Twins in Smart City by Application 2024 - 2029
• Figure 19: Digital Twins in Automotive by Type 2024 - 2029
• Figure 20: Digital Twins in Automotive by Application 2024 - 2029
• Figure 21: Digital Twins in Healthcare by Type 2024 - 2029
• Figure 22: Digital Twins in Healthcare by Application 2024 - 2029
• Figure 23: Digital Twins in Transport by Type 2024 - 2029
• Figure 24: Digital Twins in Transport by Application 2024 - 2029
• Figure 25: Digital Twins by Region 2024 - 2029
• Figure 26: North America Digital Twins by Country 2024 - 2029
• Figure 27: North America Digital Twins by Industry 2024 - 2029
• Figure 28: United States Digital Twins 2024 - 2029
• Figure 29: Canada Digital Twins 2024 - 2029
• Figure 30: Mexico Digital Twins 2024 - 2029
• Figure 31: South America Digital Twins by Country 2024 - 2029
• Figure 32: South America Digital Twins by Industry 2024 - 2029
• Figure 33: Argentina Digital Twins 2024 - 2029
• Figure 34: Brazil Digital Twins 2024 - 2029
• Figure 35: Chile Digital Twins 2024 - 2029
• Figure 36: Europe Digital Twins by Country 2024 - 2029
• Figure 37: Europe Digital Twins by Industry 2024 - 2029
• Figure 28: U.K. Digital Twins 2024 - 2029
• Figure 39: Germany Digital Twins 2024 - 2029
• Figure 40: France Digital Twins 2024 - 2029
• Figure 41: Spain Digital Twins 2024 - 2029
• Figure 42: Italy Digital Twins 2024 - 2029
• Figure 43: Poland Digital Twins 2024 - 2029
• Figure 44: Russia Digital Twins 2024 - 2029
• Figure 45: APAC Digital Twins by Country 2024 - 2029
• Figure 46: APAC Digital Twins by Industry 2024 - 2029
• Figure 47: China Digital Twins 2024 - 2029
• Figure 48: Japan Digital Twins 2024 - 2029
• Figure 49: South Korea Digital Twins 2024 - 2029
• Figure 50: Australia Digital Twins 2024 - 2029
• Figure 51: India Digital Twins 2024 - 2029
• Figure 52: MEA Digital Twins by Country 2024 - 2029
• Figure 53: MEA Digital Twins by Industry 2024 - 2029
• Figure 54: Qatar Digital Twins 2024 - 2029
• Figure 55: Kuwait Digital Twins 2024 - 2029
• Figure 56: Saudi Arabia Digital Twins 2024 - 2029
• Figure 57: South Africa Digital Twins 2024 - 2029

Tables

• Table 1: Global Digital Twins 2024 - 2029
• Table 2: Digital Twins Market by Type of Twinning 2024 - 2029
• Table 3: Digital Twins Applications 2024 - 2029
• Table 4: Digital Twins by Industry 2024 - 2029
• Table 5: Digital Twins in Manufacturing by Type 2024 - 2029
• Table 6: Digital Twins in Manufacturing by Application 2024 - 2029
• Table 7: Digital Twins in Smart City by Type 2024 - 2029
• Table 8: Digital Twins in Smart City by Application 2024 - 2029
• Table 9: Digital Twins in Automotive by Type 2024 - 2029
• Table 10: Digital Twins in Automotive by Application 2024 - 2029
• Table 11: Digital Twins in Healthcare by Type 2024 - 2029
• Table 12: Digital Twins in Healthcare by Application 2024 - 2029
• Table 13: Digital Twins in Transport by Type 2024 - 2029
• Table 14: Digital Twins in Transport by Application 2024 - 2029
• Table 15: Digital Twins by Region 2024 - 2029
• Table 16: North America Digital Twins by Country 2024 - 2029
• Table 17: North America Digital Twins by Industry 2024 - 2029
• Table 18: South America Digital Twins by Country 2024 - 2029
• Table 19: South America Digital Twins by Industry 2024 - 2029
• Table 20: Europe Digital Twins by Country 2024 - 2029
• Table 21: Europe Digital Twins by Industry 2024 - 2029
• Table 22: APAC Digital Twins by Country 2024 - 2029
• Table 23: APAC Digital Twins by Industry 2024 - 2029
• Table 24: MEA Digital Twins by Country 2024 - 2029
• Table 25: MEA Digital Twins by Industry 2024 - 2029