Before the Apollo 13 mission launch, one of the many questions that NASA engineers brainstormed was, "How do we operate and maintain our system even though it is miles away?" This question laid the foundation of the paper Mirror Worlds, published by David Gelernter. Eventually, NASA's John Vickers coined the term Digital Twin. Let's dive into the fascinating world of Digital Twin technology to see how it changes how industries build, manufacture, and produce.

What is Digital Twin Technology?

A digital twin is a digital representation of a physical object, a service, or even a process. The primary aim of creating a digital twin is to virtually process and monitor any issues with the physical thing. For example, a wind turbine embedded with sensors can stream performance data such as weather conditions, energy output, etc. This data is fed to the digital twin, which then simulates the working conditions virtually, studies performance, and provides possible solutions that are applied back to the physical object.

Digital twins are divided into three categories: Product Twins, Process Twins, and System Twins. Product twin simulates physical objects (e.g., wind turbine). A process twin simulates an entire process, for example, a virtual environment with possibilities of how the physical object will behave in different situations. Similarly, a system twin replicates a whole ecosystem (e.g., a factory) that provides an even better environment for simulation.

How is it different from simulations?

Computer-based simulations may look similar to digital twins; however, a simulation runs a particular process and works on a smaller scale. Digital twins, on the other hand, can simulate entire ecosystems. Unlike simulations, digital twins use streaming analytics to generate deeper insights using real-time data from the physical asset.

How does it work?

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Data Collection:

First, data analysts and researchers collect historical and real-time data by taking attributes such as physical properties, appearance, and behavior under certain conditions.

Data Homogenization:

This is followed by homogenizing the data - creating the digital representation of the physical object using the collected data. A 3D model is created which is identical to the most delicate details.

Data Integration:

Once the model is created, sensors, tracking devices, etc., are integrated into the physical object to stream real-time data.

Data Analysis:

After the data is integrated into the model, machine learning models create actionable insights using algorithms and visualizations from the digital twin model. Digital traces present from the twin model are used to diagnose problems.

Digital twin processes can be overwhelming and complex, so organizations must ask the right questions to get the insights they want. There are three primary functions of digital twins, and not every organization needs to perform all of them. The first function (Level I) - "To See," involves basic level monitoring and visualization of the data; the second function (Level II) - "To think," involves what-if models that find out the best possible scenarios and process configurations. Lastly, the third function (Level III) - "To do," uses advanced algorithms and finds the most appropriate solution and long-term risk assessment and prevention.

How it benefits the industry

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Improved R&D

Digital Twins enable improved research & development before the designing phase, especially with access to real-time data.

Streamlined Design

Virtual modeling using digital twins nips many design issues in the bud, thus restricting the problems in the initial prototype stage and preventing future problems that may arise in the design stage.

Cost Cutting

Virtual simulations allow engineers to run every possible scenario online, thus identifying problems before mass production. It enables the physical objects to perform as expected, thus saving labor and costs. Remote maintenance is also maintained virtually, further providing cost-reduction opportunities.

Greater Efficiency

Continuous monitoring helps manufacturers gain insights into the production systems, helping them understand how to reach peak manufacturing efficiency.

Reduced Time-to-Market

Digital twins significantly reduce the product life cycle, as most optimizations happen virtually. It allows companies to hit the market before competitors.

Predictive Maintenance

Predictive analysis paired with digital twins helps manufacturers improve overall equipment effectiveness (OEE), predict possible breakdowns, and reduce severe downtimes by ensuring any physical damage is curbed in time.

Use Cases

Digital twins are handy for large physical projects such as buildings, bridges, power equipment, industrial manufacturing projects, automobiles, medical equipment, aircraft production, oil & gas offshore platforms, wind farms, smart cities, and space exploration.

Chevron expects to save millions of dollars in maintenance costs by deploying digital twin technology for its oil fields [1]. Simens plans to reduce product defects by prototyping objects that have not been manufactured yet [2].

Meanwhile, GE utilized digital twin technology to create a "digital wind farm" [3]. GE plans to generate 20% gains in efficiency by analyzing data from each virtual wind turbine. In the healthcare sector, GE is actively building band-aid-sized sensors to send health information to a digital twin in order to predict a patient's well-being better. [4].

Conclusion

Although the idea of a digital doppelganger has been around since Apollo 13, its potential is being realized now after innovations in the Internet of Things, Virtual Simulations, Streaming Analytics, and Artificial Intelligence.

Many call automation and data exchange the new industrial revolution, and the digital twin is in its thick. With an exciting future at the helm, modern businesses have put traditional practices of building first and fixing later on the backburner and are gleefully embracing digital twin technologies to gain a competitive advantage. The question is, are you ready to embrace your digital doppelganger?

References:
[1] Chevron Partners with Microsoft to Fuel Digital Transformation from the Reservoir to the Retail Pump, https://bit.ly/3JvfUMX
[2] Digital Twins: Faster, easier, and reusable, https://sie.ag/3sHGKL7
[3] Digital Solutions for Wind Farm, https://invent.ge/352dzKn
[4] Healthcare innovation could lead to your digital twin, https://bit.ly/3sEIWmy