Digital twins market By type 2022 | IndustryARC
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Digital Twins Market
Digital Twins Market: By Type (Design and Development, Performance Monitoring, Predictive Maintenance and Others); By End User (Aerospace & Defense, Automotive & Transportation, Smart Home & Commercial, Manufacturing, Energy & Utilities and Others) & Geography - Forecast (2017-2022)
Report Code : ITR 0117
Published: 11 September, 2017   20% discount on this report

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Digital Twins represent one concept, where we may use tools and technologies to “map” data and information from atoms to bits. It helps in gaining momentum because the “map” can act as a “compass” to reveal the status of atoms (things, devices, components, parts, machines), hence, real-time transparency and visibility is gained. Due to lack of semantic interoperability between architectures, standards and ontologies to acceptance of digital proxies or digital duplicates faces hurdles. These technologies are necessary for automated discovery. Convergence of information technology, operational technology and protocol-agnostic telecommunications are fields in which progression has been growing rapidly. Making sense of the data, ability to curate data, and perform data analytics, at the edge (or mist, rather than in the fog or cloud) is key to value.

Based on various types wherein digital twins find its use, the market is segmented into by type which includes: product design and development, machine and equipment health monitoring, predictive maintenance and dynamic optimization. The growth of the market is driven by various factors such as growing adoption of Internet of things (IoT) by various end user industries and reduction in manufacturing process time and cost. However, the risks associated with data security due to the use of IoT and cloud platforms are one of the factors restraining the market growth. Various techniques are used for different treatment depending up on the usage. 



Digital Twins market is scrutinized by segments including type, end- users and geography. The report also comprises of the region wise study of the global digital twins market including Europe, Americas, Asia-Pacific and Rest of the World. Digital twins market is poised to dominate this market during 2017-2023. 

Sample Companies profiled in this Report are:
  • General Electric
  • IBM Corporation
  • Siemens A
  • Microsoft Corporation
  • SAP SE
  • 10+

The research methodology followed includes initial scope definition of the global digital twins market by type and end-users and geography. This was followed by market revenue of various types of digital twins, by region tunneling into the industries present in those regions. Further by bottom up approach the market size was estimated and forecast was done for the required period. The data and supporting insights so mined were validated by primary research process by various manufacturers, distributors, suppliers, regulatory bodies and associations.
1. Digital Twins Market Overview
2. Digital Twins Market Executive Summary
3. Digital Twins Market Landscape 
   3.1. Market Share Analysis
   3.2. Comparative Analysis
   3.3. Product Benchmarking
   3.4. End User Profiling
   3.5. Top 5 Financials Analysis
4. Digital Twins Market Forces
   4.1. Drivers
   4.2. Restraints
   4.3. Challenges
   4.4. Porter’s Five Forces Analysis
      4.4.1. Bargaining Power of Suppliers
      4.4.2. Bargaining Power of Buyers
      4.4.3. Threat of New Entrants
      4.4.4. Threat of Substitutes
      4.4.5. Degree of Competition
5. Digital Twins Market– Strategic Analysis
   5.1. Value Chain Analysis
   5.2. Pricing Analysis
   5.3. Opportunities Analysis
   5.4. Product/Market Life cycle Analysis
   5.5. Suppliers & Distributors
6. Digital Twins Market– By Type
   6.1. Introduction
   6.2. Product Design and Development 
   6.3. Machine and Equipment Health Monitoring
      6.3.1. Structural Health
      6.3.2. Conditional Monitoring
   6.4. Predictive Maintenance
   6.5. Dynamic Optimization
7. Digital Twins Market– By End-Users 
   7.1. Introduction
   7.2. Aerospace and Defense
      7.2.1. Aircraft Engine Design and Production
      7.2.2. Space-Based Monitoring
   7.3. Automotive and Transportation
      7.3.1. Vehicle Designing and Simulation
      7.3.2. Ship Control Systems
      7.3.3. Fleet Management
   7.4. Home and Commercial
      7.4.1. Enterprise Infrastructure Management
      7.4.2. Waste Management
      7.4.3. Home Automation
   7.5. Electronics & Electrical/Machine Manufacturing 
      7.5.1. Industrial Equipment Design and Simulation
   7.6. Healthcare 
      7.6.1. Medical Device Simulation
      7.6.2. Patient Monitoring
   7.7. Energy and Utilities 
      7.7.1. Wind Turbines
      7.7.2. Gas Turbines
      7.7.3. Power Infrastructure
   7.8. Retail and Consumer Goods 
   7.9. Others
      7.9.1. Chemicals and Materials
      7.9.2. Agriculture
8. Digital Twins Market– By Geography
   8.1. Introduction
   8.2. Americas
      8.2.1. U.S.
      8.2.2. Canada
      8.2.3. Mexico
      8.2.4. Brazil
      8.2.5. Rest of Americas
   8.3. Europe
      8.3.1. U.K.
      8.3.2. Germany
      8.3.3. France
      8.3.4. Spain
      8.3.5. Italy
      8.3.6. Rest of Europe
   8.4. Asia-Pacific
      8.4.1. China
      8.4.2. Japan
      8.4.3. India
      8.4.4. South Korea
      8.4.5. Rest of Asia-Pacific
   8.5. RoW
      8.5.1. Middle-East
      8.5.2. Africa
9. Digital Twins Market Entropy
   9.1. Introduction
   9.2. Expansion
   9.3. Technological Developments
   9.4. Merger & Acquisitions, and Joint Ventures
   9.5. Supply- Contract
10. Company Profiles 
   10.1. Introduction
   10.2. General Electric 
   10.3. IBM Corporation
   10.4. Siemens AG
   10.5. PTC, Inc. 
   10.6. Microsoft Corporation
   10.7. ANSYS, Inc.
   10.8. SAP SE 
   10.9. Oracle Corporation
   10.10. Robert Bosch GmbH 
   10.11. Dassault Systèmes
*More than 10 Companies are profiled in this Research Report*
"*Financials would be provided on a best efforts basis for private companies"
11. Appendix
   11.1. Abbreviations
   11.2. Sources
   11.3. Research Methodology
   11.4. Bibliography
   11.5. Compilation of Expert Insights
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