3 Key Insights on the US$ 70 Bn Opportunity in Global Digital Twin Market: Ken Research

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The report covers Worldwide Digital Twin Market, Leading Players in Digital Twin Market, Global Players in Digital Twin Market.

Driven by the Increasing Usage of Digital Twins in the Manufacturing Sectors, The Global Digital Twin Market is forecasted to Cross US$ 40 Bn By 2028 says Ken Research Study.

A digital twin is a digital representation of a real-world entity or system. The implementation of the digital twin is an encapsulated software object or model that reflects a unique physical object, process, organization, person, or other abstraction. Data from multiple digital twins can be used for composite views across different real-world entities, such as power plants or cities and their associated processes. For instance, wind turbines are equipped with various sensors related to important functional areas. These sensors generate data on various aspects of physical object performance, such as energy output, temperature, and weather conditions.

“Ken Research shares 3 key insights on this high-opportunity market from its latest research study”

1. Increasing Focus on Cutting-edge Real-Time Data Analytics Provides an Opportunity for the Market Growth

According to Ken Research Analysis, the Global Digital Twin Market was valued at ~US$ 2 billion in 2017. It is estimated to be ~US$ 8 billion in 2022 and is forecasted to reach a market size of ~US$ 40 billion by 2028, growing at a CAGR of ~30% from 2022 to 2028.

The digital twin technology can represent a complete manufacturing plant, an assembly line, a specific component, or a group of employees. There are many ways to generate solutions using digital twin technology, depending on the sources and different data. The foundation of a complete digital twin technology is data analytics that provides the ability to model and monitor real-world objects. Digital twin capabilities reflect real-time data analysis to improve the capabilities of a company or organization's digital twin technology. Established digital twins and analytics enable more accurate diagnostics, optimal and predictive operations.

In 2022, the European Commission announced its ambition to work with the European Space Agency and other organizations to create a digital twin of the earth called Destination Earth. The primary goal of this project is to develop digital twins focused on floods, heatwaves, and droughts, in addition to natural disasters, by the end of 2024.

After realizing the advantages of data analytics & AI, governments and organizations have started understanding the potential importance of digital twins.

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2. Increasing Usage of Digital Twins in Manufacturing Sectors to Cut Costs and Enhance Supply Chain Efficiency is Fuelling the Market Worldwide

Unplanned downtime and wasted production are issues that greatly affect manufacturers. Manufacturers are looking for systems that can predict potential errors and malfunctions so that losses can be effectively prevented. The advantage of using a digital twin is the reduction of additional costs and time associated with manufacturing. Digital twins help engineers improve product performance by analyzing and modifying the physical design of prototypes that change at each stage of the design process. Engineers can use the digital twin to simulate a digital prototype designed and modify the prototype's design with little effort and cost.

Operational digital twins blend and correlate real-time streaming IoT data with other inputs. Machine learning, AI, and advanced modeling techniques are then applied to create a dynamic virtual representation of the entire facility. Machine learning technology is the foundation on which digital twins work.

The manufacturing sector is slowly taking its steps toward using digital twin technology, but the 2D designing process is still predominantly used in the construction sector. As a result of digital twin technology, off-site building and construction professionals now have clear on-site visualization of a specific project.

The graph below represents the top areas for Machine Learning Technology adoption:

3. High Costs Associated with the Implementation of Digital Twin Technology is the Major Challenge Faced by the Market

Digital twins & its related technologies such as manufacturing operations management (MOM), product lifecycle management (PLM), manufacturing process management (MPM), computer-aided design (CAD), model-based system engineering (MBSE), enterprise resource planning (ERP), and augmented reality (AR)/virtual reality (VR)/extended reality requires very high capital for Implementation. The cost of production and implementation of a digital twin technology rises considerably and becomes more expensive if the organization or the firm lacks the necessary support infrastructure and technological foundation. Therefore, the high cost of implementation is a barrier for organizations in implementing digital twin technology.

The table below represents the cost models for implementing digital twin technology in various different types of infrastructures:

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Key Topics Covered in the Report

Snapshot of Global Digital Twin Market
Industry Value Chain and Ecosystem Analysis
Market size and Segmentation of the Global Digital Twin Market
Historic Growth of Overall Global Digital Twin Market and Segments
Competition Scenario of the Market and Key Developments of Competitors
Porter’s 5 Forces Analysis of Global Digital Twin Industry
Overview, Product Offerings, Strengths, & Weaknesses of Key Competitors
Covid-19 Impact on the Overall Global Digital Twin Market
Future Market Forecast and Growth Rates of the Total Global Digital Twin Market and Segments
Analysis of Global Digital Twin Market
Major Production/Supply and Consumption/Demand Hubs within Each Region
Major Country-wise Historic and Future Market Growth Rates of the Total Market and Segments
Overview of Notable Emerging Competitor Companies within Each Region