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數位孿生市場：技術、孿生類型、網路到實體解決方案、用例、產業、應用（2024-2029）
市場調查報告書
商品編碼
1498820

數位孿生市場：技術、孿生類型、網路到實體解決方案、用例、產業、應用（2024-2029）

Digital Twins Market by Technology, Twinning Type, Cyber-to-Physical Solutions, Use Cases and Applications in Industry Verticals 2024 - 2029
出版日期: | 出版商: Mind Commerce | 英文 157 Pages | 商品交期: 最快1-2個工作天內

價格

本報告對全球數位孿生市場進行了調查，概述了數位孿生產品和服務，包括數位孿生技術、解決方案、用例、研發、領先企業的初步實施努力評估以及應用開發和營運。行業的用例。我們也分析了支持數位孿生並從中受益的技術。此外，我們還提供了 2024 年至 2029 年跨多個細分市場和用例的數位孿生解決方案的詳細預測，包括製造模擬和預測分析，以及全球、區域和主要國家的預測。

主要報告結果

  • 47% 的 IT 決策者不瞭解數位孿生
  • 到 2029 年，智慧城市的數位孿生解決方案將達到 59 億美元
  • 到 2029 年，超過 95% 的物聯網平台將具備某種數位孿生功能
  • 數位孿生將成為物聯網應用支援的標準功能/功能
  • 主要的數位孿生解決方案包括資產孿生、組件孿生、系統孿生、流程孿生、工作流孿生
  • 96.5% 的供應商認識到 IIoT API 和平台與工業數位孿生功能整合的需求
  • 47.2% 的各行業主管瞭解數位孿生的優勢，其中 63% 的高階主管計劃在 2029 年將其納入營運中

依行業劃分的數位孿生技術：

數位孿生技術正在被各個行業採用，因為它可以創建實體資產、系統和流程的虛擬副本。以下是利用數位孿生的主要行業的範例。

製造業

  • 預測性維護：監控設備以預測故障並安排維護
  • 流程最佳化：簡化並提高製造流程的效率
  • 產品生命週期管理：追蹤產品從設計到生產結束的整個流程

醫療保健

  • 患者監控：創建患者的數位複製品以進行個人化治療
  • 醫療設備管理：醫療設備模擬與效能最佳化
  • 醫院管理：加強醫院運作和病患流動

汽車/交通

  • 車輛設計和測試：新車設計的模擬和性能測試
  • 車隊管理：監控和優化車隊性能
  • 智慧基礎設施：智慧城市基礎設施和車輛集成，以實現更好的交通管理

能源/公用事業

  • 電網管理：配電網路監控與最佳化
  • 資產管理：追蹤和管理風力渦輪機和太陽能電池板等能源資產
  • 預測性維護：防止關鍵基礎設施故障

航空航太/國防

  • 飛機設計與維護：模擬飛機性能並預測維修需求
  • 任務規劃：優化防禦行動與任務規劃
  • 訓練模擬：提供士兵真實的訓練環境

房地產/建築業

  • 建築資訊建模：創建建築物的詳細數字表示
  • 施工專案管理：施工過程的監控與最佳化
  • 設施管理：加強樓宇管理與運營

零售/消費品

  • 供應鏈優化：提高供應鏈效率與反應能力
  • 客戶體驗：基於消費者行為的數位複製品來個人化客戶體驗
  • 庫存管理：改進庫存追蹤和管理

智慧城市

  • 城市規劃：城市基礎設施和服務的模擬和最佳化
  • 公共安全：加強緊急應變和保全措施
  • 永續發展：監控和管理環境影響和能源使用

溝通

  • 網路優化：監控和優化通訊網路以提高效能
  • 服務管理：加強對電信服務和客戶體驗的控制
  • 基礎設施管理：追蹤和維護通訊基礎設施

目錄

第1章 內容提要

第2章 簡介

  • 概述
  • 相關技術及對數位孿生的影響
    • 工業互聯網與工業4.0
    • 配對技術
    • 網路實體系統
    • 擴增實境/虛擬實境/混合現實
    • 人工智慧和機器學習
    • 積層製造/3D列印
  • 潛在用途和後果分析
    • MRO（維修/修理/大修）
    • 消費者資產的數位化身
    • 效能/服務監控
    • 檢查/維修
    • 預測性維護
    • 產品設計/開發
    • 複合材料組裝/製造
    • 潛在的業務成果
  • 數位孿生服務生態系統
    • 物聯網
    • 消費者物聯網
    • 產業發展
    • Digital Twinning as a Service

第三章 數位孿生企業評價

  • 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 數位孿生市場分析與預測

  • 全球數位孿生市場趨勢及預測
  • 數位孿生市場：依孿生類型
  • 數位孿生的應用
  • 數位孿生市場：依行業分類
    • 製造：依類型
    • 智慧城市：依類型
    • 汽車：依類型
    • 醫療：依類型
    • 交通：依類型
  • 數位孿生市場：依地區
    • 北美
    • 南美洲
    • 歐洲
    • 亞太地區
    • 中東/非洲

第5章 一般性意見/建議

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:

  • 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

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