When organizations want to develop new products, modernize their supply chains, or gain greater visibility into their operations, disrupting and experimenting with existing processes and systems can be difficult, risky, and costly. There is.
Digital twins are emerging as a viable solution due to the rise of the Internet of Things (IoT), sensors, edge computing, cloud technology, wireless communications, and data.
What is digital twin technology?
A digital twin is a virtual representation or replica of a physical system or environment. This allows organizations to test whether operational changes or investments are right for them before deciding whether to proceed.
Digital Twin Consortium official definition describes a digital twin as “a virtual representation of real-world entities and processes synchronized at a specified frequency and fidelity.”
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A digital twin is an exact replica of a real-world asset, modeled to simulate how the original asset behaves in the physical world. These can include factory floor equipment, prototype vehicles, aircraft, manufacturing systems, and even entire supply chains.
A single replicated asset may seem insignificant, but a digital twin, used to create a digital network consisting of an organization’s full set of real-world assets, provides a realistic overview of equipment and systems and their performance.
These replica systems are generated by data collected from real-world assets and can be experimented with digitally without incurring real-world risks. Data is one of the most valuable currencies in the world today, and by implementing digital twin technology, businesses can leverage this information to generate actionable insights.
Types of digital twins
A digital twin can be as diverse as the assets it represents. Can be entity, system, or process-based. It can be built to simulate existing systems and supply chains, check asset interoperability, and test physical materials and components. This type of setup is known as a composite digital twin.
Many companies are now benefiting from digital twins, which were developed for predictive maintenance and act as virtual clones of complex systems. One of the main types of digital twins is used to conceive and refine new product lines, making them invaluable during product design and subsequent testing stages.
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Another potential application of digital twin technology is the creation of virtual representations of customers. According to gartnercreating a “digital twin of the customer” (DToC) can improve demand forecasting accuracy and behavioral analysis.
Benefits of digital twin
The benefits of digital twin technology are enormous.
Digital twins provide an environment in which organizations can design, test, and adjust product designs and operational processes without disrupting active supply chains or workflows.
Consider the following example. A manufacturer wants to see if changing a particular set of settings on their production line will improve results. Rather than stopping ground operations on the factory floor, manufacturers can use performance data and system status information from sensors embedded in equipment to run experiments and create virtual replicas for testing.
This allows companies to safely check whether changes work, while also saving costs associated with production pauses. The same premise applies to product design, allowing companies to evaluate prototypes without investing heavily in development or manufacturing.
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According to McKinsey researchsenior research and development leaders say digital twin technology is already having a “significant” impact on product development, often reducing total development time and spending by 20% to 50%. states.
The benefits of digital twin technology extend to remote monitoring of assets in real-time. Digital twins capture data from physical equipment, track performance, and alert users to potential problems so they can be remediated quickly.
Digital twins also play an important role in environmental design. Creating virtual product designs in systems such as CAD is not new, but digital twins can create realistic replicas to support urban planning and critical infrastructure development.
Potential downsides of digital twin technology
While digital twin technology can drive business growth and provide valuable data-driven insights into existing processes, it is not without potential drawbacks.
The implementation of digital twin technology should be considered in conjunction with the potentially high level of return on investment. Creating exact replicas of real-world assets can be a time-consuming process with high initial costs, and ROI may not be realized until organizations can derive useful information from digital twins and implement changes. There is.
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Additionally, creating the right environment for setting up a digital twin can be complex, especially when there are interoperability issues. These systems must also be constantly monitored and maintained.
Additionally, security risks must also be considered. Digital twins require backend access, cloud storage, a network of data, and typically an entry point into real-world assets and environments.
If an organization’s security posture is lacking, cyber attackers can infiltrate digital twin systems and learn all of a victim’s technologies and assets, stealing information or causing widespread destruction. .
Analyst insights and predictions
- gartner Analyst predictions The digital twin market is expected to reach a value of approximately $183 billion by 2031. According to the research firm, composite digital twins offer the greatest opportunity.
- market sand market According to the study, the global digital twin market is expected to grow from an estimated $10.1 billion in 2023 to $110.1 billion by 2028, driven by growing interest in the medical industry and the need to reduce manufacturing costs.
- Comparatively, Fortune Business Insights predicts that the global digital twin market, valued at $12.91 billion in 2023, will grow to $17.73 billion in 2024 and $259.32 billion by 2032.
- IDC prediction By 2027, 35% of G2000 companies are expected to adopt supply chain orchestration tools with digital twin capabilities.
- McKinsey & Company survey data Nearly 75% of companies indicate they have already implemented digital twin technology at at least a medium complexity level.
Examples of digital twin implementation
Awareness of digital twin technology is rapidly spreading across industries such as manufacturing, aerospace, transportation, retail, and healthcare.
a investigation Research conducted by IDC reveals that there is growing awareness of digital twin technology in these and other industries. In total, 52% of respondents in Resources & Construction said they were familiar with the technology, followed by 40% in Manufacturing & Professional Services, 37% in Transportation & Logistics & Energy, and 36% in Finance .
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Digital twin technology appears to be growing fastest in asset-intensive industries such as manufacturing, oil and gas, aerospace, and automotive. However, digital twin technology is also being used in retail, healthcare, and smart city pilot schemes.
Examples of current digital twin technology in action include:
- swisscom: Swisscom collaborated with Ericsson Deploy a project that leverages network digital twins to make network recommendations. This enabled the Swiss telecommunications company to reduce its overall transmission power by 20%, reducing base station power consumption and increasing speeds for its customers.
- mayo clinic: Healthcare provider Mayo Clinic uses data from digital imaging, genetics, wearable devices, and more to using a digital twin Create custom patient models for diagnosis and treatment.
- siemens: German high-tech conglomerate Siemens uses the A virtual power plant digital twin for planning power plant infrastructure, including components such as solar panels and wind turbines.
- NTT IndyCar: U.S. auto racing organization NTT IndyCar Series Uses digital twin technologycombines AI (artificial intelligence) and data analysis to generate real-time racing insights.
- E.ON: German energy company E.ON, Appointed to DNV Implement digital twins to monitor assets and collect performance data.
- BMW:Car manufacturer BMW Cooperation with SAP Create a virtual model of all active factories.
- Orlando Economic Partnership Agreement: OEP is a nonprofit economic and community development organization. SAP helps you deploy your digital twin Develop an urban planning tool (OEP) that includes a 3D representation of a metropolitan area.
Back in 2018, Deloitte looked at real-world implementations. report“Companies are using these ‘digital twins’ in a growing number of industries, making it easier to design and operate complex products and processes, from wind turbines to supermarket aisles. We are accelerating product and process development, optimizing performance, and enabling predictive maintenance.”
of 2018 Deloitte Survey Here’s an overview of how these companies are benefiting from digital twins.
- maserati: Automakers are using digital twin technology to accelerate product design. Virtual modeling and simulation not only reduces the number of expensive real-world prototypes required, but also reduces the need for physical wind tunnel testing and commissioning, reducing vehicle development time by 30% .
- G.E.: The tech giant is using digital twins to model its supply chain and factory processes at its Nevada facility to improve inventory management.
- Dassault Systèmes: The healthcare company is building a library of realistic human heart simulations that doctors can reference to better understand their patients’ conditions in real time.
Along with cloud, AI, machine learning, and data analytics, digital twin technology has the potential to significantly improve production, manufacturing, and supply chains. Digital twins are not static. Instead, many modern technologies can be integrated to provide enterprises with a holistic and transparent overview of their assets and how they work together, improving business outcomes and enabling informed decision-making. and improve efficiency.
As interest and understanding of digital twin technology grows each year, we expect more organizations to create and leverage their own digital twins in the future.
