90-page report detailing insights from the Digital Twin market including:
- Detailed Digital Twin definition
- 15 Detailed vendor profiles
- 6 Deep-dives into aspects affecting Digital Twin technology
- 6 Key trends shaping the Digital Twin market
- 4 Key challenges facing the Digital Twin market
- Digital Twin adoption analysis including ROI and budget analysis
- Analysis of end user Digital Twin sentiment (based on survey results)
- Database of 90+ Digital Twin technology vendors
- Database of 35 Digital Twin projects
The ‘Digital Twin Insights Report 2020’ is part of IoT Analytics' ongoing coverage of the IoT Platforms/Software Research Workstream. The main purpose of this report is to help our readers understand the current Digital Twin landscape by defining and analyzing the market.
- What is a Digital Twin (definition)?
- Who are the key players offering Digital Twin technology and what is their offering?
- What are examples of successful Digital Twin implementations?
- What are the main trends shaping the Digital Twin market?
- What are the key challenges associated with building digital twins?
- What standardization efforts exist for digital twins?
- How are Digital Twins being used to tackle Covid-19?
- What is the end-user view of Digital Twins in terms of adoption, ROI, budgeting, and use with IoT platforms?
AT A GLANCE
A digital twin is a digital abstraction or representation of a physical system's attributes and/or behavior on 3 distinct dimensions. This report includes a detailed definition of digital twins, key vendors, case study analysis, key trends & challenges, and insights from relevant surveys.
A cube analysis is used to frame the various digital twin offerings in the market. The 3 dimensions include 1.Hierarchical levels, 2. Lifecycle phases, 3. Most common uses and input data types, and results in over 250 Digital Twin classifications.
The report includes 10 detailed case studies and a database of 35 digital twin case studies that have been identified across variety of industries and analyzed for this research.
6 deep dives are provided in the report including one on standardization, interoperability, funding/investment, patent analysis, market commentary and a special analysis undertaken to see how digital twins are being used to tackle Covid-19.
15 detailed company profiles are provided in the report as well a company database classifying details of 90+ digital twin vendors.
Results of an (manufacturing focused) end-user survey are presented showing digital twin adoption rates, ROI, and budgets analysis.
SELECTED COMPANIES FROM THE REPORT:
ABB, Ansys, Autodesk, AWS, Bosch, Dassault Systemes, Emerson, ESRI, General Electric, IBM, Microsoft, Oracle, PTC, SAP, Schneider Electric, Seebo, Siemens, Twaice, Willow, among 70+ others.
Table of Contents
2. Topic at a glance
- 2.1 Digital Twin evolution
- 2.2 Definition
- 2.3 6 Hierarchical levels of a digital twin
- 2.4 6 Lifecycle phases of a digital twin
- 2.5.1 7 Most common uses of a digital twin
- 2.5.2 3 Most common input data types
- 2.6 Digital twin cube analysis - overview
- 2.7 More than 250 digital twin scenarios
- 2.8 Digital Twin implementation example
- 2.9 How different companies define Digital Twin
3. Competitive landscape
- 3.1 Competitive landscape overview
- 3.2 Overview of 15 of the most prominent vendors and their capabilities by lifecycle phase
- 3.2.1 Digital Twin vendor: Vendor X
- 3.2.2 Digital Twin vendor: Vendor X
- 3.2.3 Digital Twin vendor: Vendor X
- 3.2.4 Digital Twin vendor: Vendor X
- 3.2.5 Digital Twin vendor: Vendor X
- 3.2.6 Digital Twin vendor: Vendor X
- 3.2.7 Digital Twin vendor: Vendor X
- 3.2.8 Digital Twin vendor: Vendor X
- 3.2.9 Digital Twin vendor: Vendor X
- 3.2.10 Digital Twin vendor: Vendor X
- 3.2.11 Digital Twin vendor: Vendor X
- 3.2.12 Digital Twin vendor: Vendor X
- 3.2.13 Digital Twin vendor: Vendor X
- 3.2.14 Digital Twin vendor: Vendor X
- 3.2.15 Digital Twin vendor: Vendor X
4. Case studies
- 4.1 Digital Twin case studies - Overview
- 4.1.1 Case Study: Case Study X
- 4.1.2 Case Study: Case Study X
- 4.1.3 Case Study: Case Study X
- 4.1.4 Case Study: Case Study X
- 4.1.5 Case Study: Case Study X
- 4.1.6 Case Study: Case Study X
- 4.1.7 Case Study: Case Study X
- 4.1.8 Case Study: Case Study X
- 4.1.9 Case Study: Case Study X
- 4.1.10 Case Study: Case Study X
- 4.2 List of other case studies
5. Trends & challenges
- 5.1 Trends & Challenges overview
- 5.2 Trend 1
- 5.3 Trend 2
- 5.4 Trend 3
- 5.5 Trend 4
- 5.6 Trend 5
- 5.7 Trend 6
- 5.8 Challenges
- 6.1 Overview
- 6.2 Deep-dive: Standardization
- 6.3 Deep-dive: Interoperability
- 6.4 Deep-dive: Patent analysis
- 6.5 Deep-dive: Funding / investment
- 6.6 Deep-dive: Covid-19
- 6.7 Deep-dive: Commentary on Market Sizing
7. End-user view
- 7.1 Digital Twin adoption
- 7.2 Digital Twin ROI
- 7.3 Digital Twin Budgets
- 7.4 Digital Twin Challenges
- 7.5 Digital Twin Vendors: Companies most often mentioned
- 7.6 Digital Twin Use Cases: Most common industrial applications
- 7.7 IoT Platforms & Digital Twins