
UK Digital Twin Market Research Report: Forecast (2022-2027)
By Type (Parts Twin, Product Twin, Process Twin, System Twin), By Technology (DTS-Si, Predix, APDV, Others), By Application (Product Design and Development, Machine & Equipment Hea......lth Monitoring, Predictive Maintenance, Dynamic Optimization), By Deployment Type (Cloud, On-Premises, Hybrid), By End-User (Manufacturing, Agriculture, Automotive & Transportation, Energy & Utilities, Healthcare & Life Sciences, Residential & Commercial, Retail & Consumer Goods, Others), By Region (England, Scotland, Wales, Northern Ireland), By Company (ANYSYS, Inc., General Electric Company, Google, IBM Corporation, Microsoft Corporation, Oracle Corporation, PTC Inc., Robert Bosch, SAP SE, Siemens AG) Read more
- ICT & Electronics
- Oct 2022
- Pages 112
- Report Format: PDF, Excel, PPT
Market Definition
A digital twin is a virtual model of an object or system that uses machine learning, simulations, and data analytics capabilities to predict the performance characteristics of its physical companion before it gets manufactured for real. In this technology-driven era, digital twins are continuously learning new skills to generate better insights for making products more innovative & processes more efficient.
Market Insights
The UK Digital Twin Market is anticipated to grow at around 30% CAGR during the forecast period, i.e., 2022-27. The growth of the market is likely to be propelled mainly by the increasing requirement for asset monitoring in industries, the mounting prevalence of Industry 4.0, and the rising construction of smart buildings for optimum energy consumption in the UK. Besides, the increasing utilization of digital twin models in manufacturing sectors to reduce costs & improve supply chain efficiency is another prominent aspect projected to drive the industry in the coming years.
Report Coverage | Details |
---|---|
Study Period | Historical Data: 2017-20 |
Base Year: 2021 | |
Forecast Period: 2022-27 | |
CAGR (2022-2027) | 30% |
Key Companies Profiled | ANYSYS, Inc., General Electric Company, Google, IBM Corporation, Microsoft Corporation, Oracle Corporation, PTC Inc., Robert Bosch, SAP SE, Siemens AG |
Unit Denominations | USD Million/Billion |
Digital twins are predictive models that help companies virtually see physical prototypes of their assets before they get developed in real-time, thereby improving process workflow throughout a product's lifecycle. Several industries in the UK, specifically automotive & transportation, manufacturing, healthcare, and aerospace & defense, are increasingly utilizing digital twin technology in multiple applications, such as remote monitoring, energy management, & factory optimization, among others, in order to optimize their operational workflows & supply chains, enhance overall productivity & efficiency, design better products, & thus reduce downtime.
Furthermore, the surging penetration of automation in various end-user verticals, coupled with the growing utilization of digital twins in the retail & automotive sectors in order to provide personalized customer services, are other prominent aspects creating new directions for the UK Digital Twin Market to expand significantly through 2027.
Latest Trend in the UK Digital Twin Market
The aerospace & defense sector is projected to create remunerative prospects for the Digital Twin Market in the UK. The aviation industry is increasingly adopting digital twin technology to overcome the shortcomings of current fleet management practices and save resources with predictive & prescriptive analytics. By creating the digital twin of aircraft & feeding them with real-time data, airlines are able to reduce maintenance costs, enhance reliability, and optimize their overall performance.
On the other hand, there's increasing utilization of digital twins in the defense sector to enhance the efficiency & performance of weapons and ensure less causality by diagnosing & avoiding faults in real-time using digital twin-based predictive maintenance models. Hence, these aspects are projected to create a pool of profitable opportunities for the UK Digital Twin Market to witness considerable growth in the aerospace & defense sector over the coming years.

Market Segmentation
Based on Application:
- Product Design & Development
- Machine & Equipment Health Monitoring
- Predictive Maintenance
- Dynamic Optimization
Of them all, predictive maintenance is among the key application areas of digital twin technology and holds a prominent share in the UK Digital Twin Market. More & more businesses operating in the country are adopting digital twin-based predictive maintenance models to avoid system or process failures through real-time equipment monitoring. By using these models, companies are able to determine the lifetime of different parts/components of an asset and perform maintenance on them before any failure surfaces. In addition, with the integration of the IoT into digital twins, organizations can now enjoy an optimized equipment maintenance cycle with reduced maintenance activities, costs, & downtime.
Furthermore, predictive maintenance-based digital twin models allow for immediate replacement of components that are approaching failure while extending their lifetime by minimizing unscheduled maintenance as well as labor costs. Hence, a large number of companies, especially those operating in sectors like oil & gas, power utilities, etc., are adopting these modes to achieve significant cost savings & competitive advantages and, consequently, fueling the growth of the digital twin market in the UK.
Based on End-User:
- Agriculture
- Manufacturing
- Automotive & Transportation
- Energy & Utilities
- Healthcare & Life Sciences
- Residential & Commercial
- Retail & Consumer Goods
Here, the automotive & transportation sector is projected to acquire the majority share in the UK Digital Twin Market during 2022-27. Digital twin technology is being adopted increasingly in the automotive & transportation sector to analyze the complete performance of a connected vehicle & its connected abilities by capturing its operational & behavioral data through a virtual model.
Through digital twins, automakers are offering customized services to their customers by using interactive dashboards on websites, where customers can personalize vehicles as per their preferences, thereby enhancing customer engagement. In addition, the mounting popularity of autonomous, electric, & connected cars and the ever-increasing utilization of vehicle simulation software are also stimulating the demand for digital twin technology.
Furthermore, the surging utilization of 3D simulation & 3D printing software in fleet management and vehicle designing & simulation applications and massive R&D investments by automakers in improving vehicle performance & enhancing the efficiency of production processes are further creating new avenues for the digital twin industry to expand across the automotive & transportation sector in the UK.
Market Dynamics:
Key Driver: Mounting Adoption of Industrial IoT (Internet of Things)-based Digital Twins across different Industries
With the growing affordability & improved availability of sensors, processors, platforms, & other integrated technologies, many industries in the UK, to access real-time insights into their assets, are increasingly adopting IIoT-based digital twin models, i.e., the unification of physical assets, systems, platforms, & applications, to attain benefits like reduced errors, improved quality & safety control, enhanced productivity, massive profits, and significant cost savings.
These platforms allow companies to understand the operational behavior of assets before they get installed for real and, consequently, facilitate product integration, remote diagnosis, and smart monitoring, which helps them achieve enhanced operational efficiency, exceptional productivity, and optimized performance of equipment. These benefits of digital twin models integrated with IIoT are likely to surge their demand significantly and, in turn, fuel the growth of the UK Digital Twin Market during 2022-27.
Growth Challenge: High Costs of Implementing Digital Twin Technology
Digital twins comprise high-end technologies PLM (Product Lifecycle Management), 3D CAD, ERP (Enterprise Resource Planning), AR/VR/ER, ML, AI, etc., which all incur high initial capital. This cost gets further high if an enterprise lacks the necessary support infrastructure & technological foundation. Hence, the adoption of digital twins is limited to large-scale end-users like the automotive & transportation sector and manufacturing industries, i.e., a significant growth restraint for the UK Digital Twin Market to grow during 2022-27.
Key Questions Answered in the Market Research Report:
- What are the overall statistics or estimates (Overview, Size- By Value, Forecast Numbers, Segmentation, Shares) of the UK Digital Twin Market?
- What are the region-wise industry size, growth drivers, and challenges?
- What are the key innovations, opportunities, current & future trends, and regulations in the UK Digital Twin Market?
- Who are the key competitors, their key strengths and weaknesses, and how do they perform in the UK Digital Twin Market based on a competitive benchmarking matrix?
- What are the key results derived from surveys conducted during the UK Digital Twin Market study?
Frequently Asked Questions
- Introduction
- Assumption
- Research Process
- Market Definition
- Market Segmentation
- Preface
- Executive Summary
- Expert Verbatim- What our Experts Say?
- Impact of Covid-19 on the UK Digital Twin Market
- UK Digital Twin Market Trends & Insights
- UK Digital Twin Market Dynamics
- Drivers
- Challenges
- UK Digital Twin Market Regulations & Policies
- UK Digital Twin Market Supply Chain Analysis
- UK Digital Twin Market Hotspots & Opportunities
- UK Digital Twin Market Outlook, 2017-2027F
- Market Size & Analysis
- By Revenues (USD Million)
- Market Share & Analysis
- By Type
- Parts Twin
- Product Twin
- Process Twin
- System Twin
- By Technology
- DTS-Si
- Predix
- APDV
- Others
- By Application
- Product Design and Development
- Machine & Equipment Health Monitoring
- Predictive Maintenance
- Dynamic Optimization
- By Deployment Type
- Cloud
- On-Premises
- Hybrid
- By End-User
- Manufacturing
- Agriculture
- Automotive & Transportation
- Energy & Utilities
- Healthcare & Life Sciences
- Residential & Commercial
- Retail & Consumer Goods
- Others
- By Region
- England
- Scotland
- Wales
- Northern Ireland
- By Company
- Revenue Shares
- Competition Characteristics
- Market Share of Leading Companies, By Revenues
- By Type
- Market Size & Analysis
- UK Digital Twin Market Key Strategic Imperatives for Growth & Success
- Competition Outlook
- Competition Matrix
- Brand Specialization
- Target Markets
- Target End-Users
- Research & Development
- Strategic Alliances
- Strategic Initiatives
- Company Profiles
- ANYSYS, Inc.
- General Electric Company
- IBM Corporation
- Microsoft Corporation
- Oracle Corporation
- PTC Inc.
- Robert Bosch
- SAP SE
- Siemens AG
- Competition Matrix
- Disclaimer

MarkNtel Advisors follows a robust and iterative research methodology designed to ensure maximum accuracy and minimize deviation in market estimates and forecasts. Our approach combines both bottom-up and top-down techniques to effectively segment and quantify various aspects of the market. A consistent feature across all our research reports is data triangulation, which examines the market from three distinct perspectives to validate findings. Key components of our research process include:
1. Scope & Research Design At the outset, MarkNtel Advisors define the research objectives and formulate pertinent questions. This phase involves determining the type of research—qualitative or quantitative—and designing a methodology that outlines data collection methods, target demographics, and analytical tools. They also establish timelines and budgets to ensure the research aligns with client goals.
2. Sample Selection and Data Collection In this stage, the firm identifies the target audience and determines the appropriate sample size to ensure representativeness. They employ various sampling methods, such as random or stratified sampling, based on the research objectives. Data collection is carried out using tools like surveys, interviews, and observations, ensuring the gathered data is reliable and relevant.
3. Data Analysis and Validation Once data is collected, MarkNtel Advisors undertake a rigorous analysis process. This includes cleaning the data to remove inconsistencies, employing statistical software for quantitative analysis, and thematic analysis for qualitative data. Validation steps are taken to ensure the accuracy and reliability of the findings, minimizing biases and errors.

4. Data Forecast and FinalizationThe final phase involves forecasting future market trends based on the analyzed data. MarkNtel Advisors utilize predictive modeling and time series analysis to anticipate market behaviors. The insights are then compiled into comprehensive reports, featuring visual aids like charts and graphs, and include strategic recommendations to inform client decision-making