Press Release Description
Digital Twins Market to Boom as Industries in the UK Emphasize on Increased Efficiency & Productivity
A recent research study published by MarkNtel Advisors has projected that the UK Digital Twin Market is set to record around 30% CAGR during 2022-27. The growing end-user requirements for asset monitoring to enhance productivity, the rising adoption of Industry 4.0, and various ongoing & upcoming smart building construction projects across the UK are the prime aspects likely to drive the digital twin industry.
Many end-user verticals, especially the automotive & transportation, and manufacturing sectors, are increasingly utilizing digital twin models for different purposes like factory optimization, energy management, & remote monitoring, among others, in order to minimize costs & downtime, optimize workflows, and boost productivity.
Furthermore, the increasing utilization of digital twins in the retail & automotive sectors to provide personalized customer services and the growing trend of automation in many industries are creating remunerative prospects for the UK Digital Twin Market through 2027.
Automotive & Transportation Sector to Provide Endless Opportunities for the Digital Twin Market
Companies operating in the automotive & transportation industry across the UK are increasingly adopting digital twins in order to analyze the performance & efficiency of connected vehicles & their abilities before they are made for real by gathering their operational & behavioral insights using a virtual model.
Moreover, automobile manufacturers are offering personalized services to their customers, like interactive dashboards on websites, where they can customize their vehicles in the desired manner. Autonomous, electric, & connected cars that are excessively becoming popular & witnessing high demand in the UK are also infusing the utilization of vehicle simulation software and, in turn, boosting the demand for digital twins.
Furthermore, automakers are making substantial investments in enhancing vehicle performance & efficiency of production processes, thereby augmenting the demand for digital twins and fueling the overall growth of the UK digital twin industry across the automotive & transportation sector.
Predictive Maintenance to Remain the Most Prominent Application of Digital Twins
Various companies in the UK are actively focusing on enhancing their business productivity and thus adopting predictive maintenance models based on digital twins to avoid or mitigate system or process failures. Real-time equipment monitoring offered by digital twins helps them identify the lifetime of different components of an asset and perform maintenance on them before any breakdown occurs.
Moreover, the advent of IoT in digital twins has enabled an optimized maintenance cycle with fewer equipment costs, maintenance activities, & downtime. It is done simply by immediately replacing parts/components that may fail soon and prolonging their life by reducing unscheduled maintenance activities & labor costs. Hence, as a large number of organizations are leveraging these benefits of digital twin-based predictive maintenance models and achieving notable cost savings & competitive advantages, it clearly cites a pool of profitable prospects for the UK Digital Twin Industry in the coming years.
The major companies in the UK Digital Twin Market include Google Siemens AG, General Electric Company, IBM Corporation, SAP SE, Microsoft Corporation, PTC Inc., ANYSYS, Inc., Oracle Corporation, and Robert Bosch, among others.
Key Questions Answered in the Research Study
- What are the current & future trends in the UK Digital Twin Market?
- How has the industry been evolving in terms of geography & service adoption?
- How has the competition been shaping across the UK, followed by their comparative factorial indexing?
- What are the key growth drivers & challenges for the UK Digital Twin Market?
- What are the customer orientation, purchase behavior, and expectations from digital twin solution providers across the UK?
- By Type (Parts Twin, Product Twin, Process Twin, System Twin)
- By Technology (DTS-Si, Predix, APDV, Other)
- 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)
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