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Digital Twins Market by Technology, Twinning Type, Cyber-to-Physical Solutions, Use Cases and Applications in Industry Verticals 2024 - 2029

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    Report

  • 157 Pages
  • June 2024
  • Region: Global
  • Mind Commerce
  • ID: 5308850
1h Free Analyst Time

Leading digital twin solutions involve Asset Twinning, Component Twinning, System Twinning, Process and Workflow Twinning

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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.

With the purchase of this report at the Multi-user License or greater level, you will have access to one hour with an expert analyst who will help you link key findings in the report to the business issues you're addressing. This will need to be used within three months of purchase.

This report also includes a complimentary Excel file with data from the report for purchasers at the Site License or greater level.

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
List of 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

List of 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

Companies Mentioned

  • 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

Methodology

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