Digital twins are optimizing supply chains and more. Here’s why businesses should care

When organizations develop a new product, improve their supply chain, or want more information about their operations, disrupting existing processes and systems for testing can be difficult, risky, and disruptive. risky and expensive.

Now they can mitigate these risks with digital twins, which have emerged as a viable solution due to the rise of the Internet of Things (IoT), sensors, edge computing, cloud, wireless communications and data.

What is digital twin technology?

A digital twin is a virtual representation or copy of a physical system or environment. It allows organizations to test whether an operational change or investment is right for them before deciding whether to proceed.

Digital Twin Association official definition describes a digital twin as “a virtual representation of real-world entities and processes, synchronized at a given 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 real world. These can include equipment on the factory floor, prototype vehicles, aircraft, manufacturing systems and even entire supply chains.

A replicated asset may seem insignificant but used to create a digital network that encompasses an organization’s entire real-world assets, a digital twin can provide a business with a A realistic overview of existing equipment and systems — as well as their performance.

These replica systems, created through data collected from real-world assets, can be tested digitally without real-world risks. Data is one of the most valuable currencies in the world today, and implementing digital twin technology allows businesses to harness this information to generate actionable insights.

Types of digital twins

Digital twins can be as diverse as the assets they represent. They can be entity, system or process based. They can be built to simulate existing systems and supply chains, test asset interoperability, or test physical materials and components. This type of setup is called a composite digital twin.

Many businesses today benefit from digital twins developed for predictive maintenance and to act as virtual copies of complex systems. A major type of digital twin is used to visualize and innovate new product lines, which can be valuable in product design and subsequent testing phases.

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Another potential application of digital twin technology is to create virtual representations of customers. According to Gartnercreating a “digital twin of the customer” (DToC) can improve the accuracy of demand forecasting and behavioral analytics.

Benefits of digital twins

The benefits of digital twin technology are huge.

Digital twins provide an environment for organizations to design, test, and adapt product designs or operational processes without disrupting active supply chains and workflows.

Consider the following example: a manufacturer wants to see whether changing a specific set of settings on a production line will improve results. Instead of pausing ground operations at the factory, manufacturers can run tests using performance data and system status information – obtained from sensors built into the device – to create virtual copies for testing.

This provides companies with a safe way to determine whether changes are effective, while also saving on costs associated with having to pause production. The same premise can be applied to product designs, where businesses can evaluate prototypes without fully investing in developing or manufacturing them.

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According to McKinsey researchSenior research and development leaders say digital twin technology is making a “significant” impact on product development, often cutting total development time by 20% to 50% and reduce costs.

The benefits of digital twin technology extend to real-time remote asset monitoring. Digital twins can pull data from physical devices, monitor performance, and alert users to potential problems so they can be fixed quickly.

Digital twins also have an important role to play in environmental design. While creating virtual product designs in systems such as CAD is nothing new, digital twins can create physical copies to support urban planning and infrastructure development. important floor.

Potential disadvantages of digital twin technology

Digital twin technologies can drive business growth and provide valuable, data-driven insights into existing processes, but they are not without potential limitations.

The adoption of digital twin technology must be considered in conjunction with the potentially high return on investment. Creating exact replicas of real-world assets can be a time-consuming process with high initial costs, and ROI may not materialize until the organization can extract useful information from the replica. your digital twin and put the changes into practice.

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Furthermore, creating the right environment for a digital twin setup can be complicated, especially if interoperability is problematic. These systems must also be continuously monitored and maintained.

Furthermore, there are security risks to consider. Digital twins require a backend access network, cloud storage, and data, and will often require access points to real-world assets and environments.

If an organization lacks security posture, cyber attackers can infiltrate the digital twin system to learn about the entire victim’s technology and assets, steal information or cause havoc. widespread destruction.

Analyst insights and predictions

• Gartner analysts estimate that the digital twin market will be worth around $183 billion by 2031. According to the research firm, composite digital twins present the biggest opportunity.
• MarketsandMarkets Research shows that the global digital twin market will grow from an estimated USD 10.1 billion in 2023 to USD 110.1 billion in 2028, driven by the need to reduce production costs coupled with increased interest in growing interest in the healthcare industry.
• Relatively, Fortune Business Insights predicts that the global digital twin market, worth $12.91 billion in 2023, will grow to $17.73 billion in 2024 and $259.32 billion in 2032.
• IDC forecast that by 2027, 35% of G2000 companies will use supply chain orchestration tools with digital twin capabilities.
• McKinsey & Company survey data indicates that nearly 75% of companies have adopted digital twin technology with at least a “moderate” level of complexity.

Real-world examples of digital twin adoption

Awareness of digital twin technology is rapidly spreading across industries, including manufacturing, aerospace, transportation, retail and healthcare.

ONE survey by IDC shows growing familiarity with digital twin technologies in these and other industries. In total, 52% of respondents in the resources and construction sectors said they were familiar with the technology, followed by 40% in manufacturing and professional services, 37% in transportation and logistics as well as energy and 36% in the financial sector.

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Digital twin technology appears to be growing fastest in asset-intensive industries, including manufacturing, oil and gas, aerospace and automotive. However, digital twin technology is also used in retail, healthcare and smart city pilot programs.

Real-life cases of digital twin technology today include:

• Swisscom: Swisscom worked with Ericsson to launch a project that uses network digital twins to make network recommendations. It helped the Swiss telecommunications company reduce its total transmission capacity by 20%, lower base station power consumption, and improve customer speeds.
• Mayo Clinic: Through data including digital imaging, genetics and wearables, healthcare provider Mayo Clinic used digital twins to create customized patient models for diagnosis and treatment.
• Siemens: German technology group Siemens is using it a digital twin of a virtual power plant that maps out the power plant’s infrastructure, including components such as solar panels and wind turbines.
• NTT Indycar: United States auto racing authority NTT Indycar Series using digital twin technologycombined with AI (artificial intelligence) and data analytics to generate real-time racing insights.
• E.ON: E.ON, a German energy company, Appointed by DNV to deploy digital twins to monitor its assets and collect performance data.
• BMW: The automobile manufacturer BMW is work with SAP to create virtual models of all its operating plants.
• Orlando Economic Association: OEP, a nonprofit economic and community development organization, participated SAP’s help to deploy the digital twin to develop an urban planning tool (OEP), which includes 3D representations of urban areas.

Since 2018, Deloitte has been exploring real-world use cases in a reportsaid: “Companies are using these ‘digital twins’ in a growing number of industries, helping to design and operate complex products and processes from wind turbines to walkways in the supermarket just got easier. Digital twins are accelerating product and process development, optimizing performance, and enabling predictive maintenance.”

the Deloitte Research 2018 outlines how these companies benefit from digital twins:

• Maserati: Automakers are using digital twin technology to speed up product design. Virtual modeling and simulation is reducing the number of expensive real-world prototypes, as well as the need to conduct tests and drives in physical wind tunnels, cutting vehicle development time by 30%. convenient.
• GE: The tech giant is using digital twins to model supply chains and factory processes at its Nevada facility to improve inventory management.
• Dassault system: 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.

In addition to 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, they can integrate a range of modern technologies to give businesses a comprehensive, transparent, and comprehensive overview of their assets and how they work together — thereby improving their bottom line. business performance, enabling informed decision making and increased efficiency.

With interest and understanding of digital twin technology growing every year, we can expect that more organizations will create and leverage their own digital twins in the future .