Digital Twin: What It Is and How It's Driving the Future of IT
Nov 9, 2020
We’re moving deeper into the fourth wave of the industrial revolution—or Industry 4.0, as some call it. To this end, we’re seeing rapid advancements taking place in connectivity, mobility, artificial intelligence (AI), and machine learning (ML).
This is a time of great innovation. But it’s also a time of great risk—especially as mission-critical security, environmental, transportation, and manufacturing systems continue to become IP-enabled and automated, heightening the need for reliability and stability.
On top of that, the average IoT deployment can cost anywhere from $10,000 to $50,000 or more. As such, organizations have less tolerance for risk and need to actively try to reduce errors large and small. This requires finding new methods to streamline technology creation and distribution.
To mitigate IT problems and enable faster deployments, a growing number of organizations are using a technique called a digital twin.
This concept is a fundamental part of Industry 4.0. In fact, it’s flipping the “build and then tweak” script on its head.
Developers used to bring products and services to market, analyze performance, and then make changes to improve outcomes. This process was inefficient and expensive. It also resulted in lengthy outages and delays, angry end users, and lost profits all too often.
Digital twins are changing this process. This is because digital twins give developers the ability to understand how systems will operate using advanced computer models. In this light, digital twins are far more effective for product and service development than the traditional approach.
With all this in mind, let’s take a closer look at this popular trend. We'll examine how it works and why it's helping usher in a new era in computing.
What Is a Digital Twin?
In layman’s terms, a digital twin is a model of a system or device created specifically for testing, research, and learning purposes.
“A digital twin is an abstraction of something in the real world,” explains the Digital Twin Consortium, an industry group that’s furthering digital twin technologies. “It may be physical (a device, product, system, or another asset) or conceptual (a service, process, or notion). A digital twin captures the behavior and attributes of its physical sibling with data and life cycle state changes.”
According to the Digital Twin Consortium, digital twins can also help with simulations, serving as a prototype to help us better understand behavior. It can also "capture real-world behavior" so that analytics and learning can occur. In addition, the technology supports virtual reality and augmented reality use cases.
NASA first used the concept of a digital twin during the Apollo program in the 1970s. NASA was interested in testing how rockets would perform in space under various conditions. You may recall the portrayal of NASA’s digital twin in the movie Apollo 13, starring Tom Hanks. The space agency used digital twins so that scientists on Earth could monitor, diagnose, and fix hardware issues on spacecraft. Digital twins also helped train astronauts. In fact, NASA’s digital twin played a critical role in enabling NASA to bring their astronauts home during the failed Apollo 13 mission.
To be sure, the IT landscape has changed significantly since the 1970s. Still, digital twins are more important than ever—particularly as more digital technologies continue to roll out. Today’s digital twins are fully virtualized.
How a Digital Twin Works
To create a digital twin of a physical asset, engineers pull data from many sources. The most common approach is to attach sensors to physical products and transmit data back to the digital twin.
After the team collects and processes data, they then merge it with AI and ML algorithms. Once that’s done, they run it through virtual models that provide a robust testing ground for experimentation and analysis.
If executed properly, a digital twin can produce a near-perfect replica of a system. This allows data science teams and engineers to test products and ideas before moving forward with deployments. It also helps them improve operations.
Why Digital Twins Are the Future of IT
Today, digital twins are commonly used for systems of all sizes—from small-scale IoT deployments to smart cities and even global economies. Looking forward, they will continue to play a massive role in IT and manufacturing. In fact, over the next few years, experts expect that digital twins will help folks study hundreds of millions of processes and products across the world.
This is especially true in manufacturing. Gartner predicts that "by 2021, half of large industrial companies will use digital twins." This will result in a 10 percent improvement in effectiveness.
There are a few reasons digital twins are rising in popularity. First, digital twins are effective for planning, managing, and optimizing IT deployments. Digital twins also enable network and data science teams to predict outcomes and identify issues before they happen, enabling a higher level of efficiency and accuracy. What’s more, digital twins require data. And unless you’ve been living under a rock, you know there’s a ton of data out there these days. After all, businesses are collecting data at an unfathomable rate. IDC expects global data creation to reach 163 zettabytes by 2025, which is 10 times the amount of data produced in 2017.
Simply put, the more data that you have at your disposal, the more predictions you can make using digital twins. This can lead to significant savings—and fewer mistakes when developing and rolling out products and services.
Digital Twin: An Example
Suppose a city needs to redesign a major intersection.
A program can create a digital twin of the intersection and use it to study changing traffic patterns, economic activity, weather conditions, population movement, and so on. These data sets can help city planners create systems that are efficient and meaningful before design and development takes place. City planners can take the data they glean from digital twins and then approach different vendors about requests for proposals (RFPs).
Another reason digital twins are becoming more effective and popular is due to edge computing. Increasingly, enterprises are using edge computing workflows to collect and process data without having to first move it to cloud data centers for processing and analytics. That’s because edge computing enables enterprises to collect and process data on-site, resulting in leaner and faster analysis.
How Digital Twins Enable Digital Transformation
Businesses everywhere are pushing forward digital transformation initiatives in an effort to modernize and improve operations. Yet many lack the vision to execute digital transformation properly. As a result, digital transformation projects often turn into lengthy and expensive ordeals that yield relatively poor results.
Digital twins can help businesses achieve tactical digital transformation, driven by careful planning and testing. In other words, a business may identify a possible use case for digital transformation, construct a model, and then study it before moving forward with a project, such as an application or data center virtualization. Digital twins can help keep digital transformation projects under budget while preventing costly missteps.
In addition, department heads can use digital twin data to better understand the potential benefits of using new technologies—such as apps and digital services. Digital twins can also help capture buy-in and move projects forward to achieve true digital transformation.
Now that you have a better understanding of the ins and outs of digital twins, let’s take a closer look at how they’re helping organizations across multiple industries.
What Are the Benefits of Digital Twins?
Digital twins are helping organizations across all industries work more effectively. Here’s how.
1. Creating Better Products
Product engineers can use digital twins to test ideas and determine whether they're worth moving to the prototyping stage. For example, a tire manufacturer may use a digital twin to test different materials and predict their on-road performance. Whatever way you look at it, digital twins help companies create better products.
2. Training Workers in Advance
As the early Apollo missions show, certain use cases require additional training for operators—like space travel, underwater exploration, and military deployments (for instance, a combat simulation).
Digital twins can provide safe and cost-effective training simulation environments. This keeps organizations from placing operators in potentially harmful situations while preparing them for actual deployments.
3. Optimizing Retail Customer Experience (CX)
Retailers can use digital twins to create virtual models of customers and use them to help with everything from in-store management and product placement to security implementation and more. Digital twins can also help retailers create environments that are easier to navigate and more pleasing for customers.
What’s more, digital twins are helping retailers navigate the new normal of COVID-19. For example, retailers are studying the most effective ways to social distance in checkout lines and customer service areas to keep customers feeling safe and prevent them from leaving.
4. Modernizing Healthcare
Doctors and healthcare facilities are using digital twins to create accurate and realistic patient models. These models are helping with preventive maintenance. They also help healthcare facilities deliver personalized healthcare experiences. This trend is accelerating due to the steady stream of data that wearable devices generate and collect.
5. Improving Manufacturing Efficiency
Digital twins can help engineers and architects identify potential production issues early on. These experts can then adjust their approach accordingly.
Digital twins are particularly common in additive manufacturing (also known as 3D printing), where parts often need to be carefully inspected and qualified before being built. Digital twins can help simulate manufacturing processes, letting production teams identify and eliminate discrepancies in advance.
6. Reducing Costs
Currently, businesses are facing tight IT budgets due to the pandemic. This means that every penny counts. Companies can’t afford to make errors when deploying, upgrading, or replacing systems.
Digital twins can play a major role in reducing costs for organizations when rolling out IT systems.
For example, a business may use a digital twin to assess how an application or system will perform in a certain geographical area deploying it. The digital twin can take into account approximate user volumes, environmental conditions, and other conditions that could affect system performance.
What Are the Challenges of Digital Twins?
Like any other piece of technology, digital twins have their challenges. Let’s briefly explore some of the bigger ones.
1. Slower Time to Market
Creating a digital twin isn’t as fast or easy as it may seem. It’s a multistep process that requires many important considerations—from planning to ongoing management and augmentation.
For example, it’s important to select the right technology for enabling real-time data flows and integrations with IoT endpoints. Businesses also need to determine the size and scope of their digital twin project beforehand and figure out whether they have the ability to handle it.
2. Data Issues
It’s also necessary to have a framework in place to process, analyze, clean, and store data as it streams in from IoT devices. Rushing into a digital twin project can lead to issues with data integrity and storage, and this can slow down testing and delay completion times. Many businesses lack the ability to manage IoT data, and therefore they aren’t yet in a position to use digital twins.
3. Extra Management
Running a digital twin project can be a major burden on IT teams—especially in companies that are short-staffed or overworked due to the pandemic.
Companies should consider whether they have the bandwidth ahead of time. If they don’t, they should look into whether it makes sense to partner with a third-party managed service provider (MSP) to provide efficient management with performance guarantees backed by service-level agreements (SLAs).
Using Value Stream Mapping (VSM) With Digital Twins
As you can see, managing digital twins can be challenging from a workflow perspective. They require taking specific steps at the right time in order to ensure accurate and efficient results. At the same time, teams need to continuously review their processes to make sure they're maximizing results.
To streamline digital twin management and reduce complexities, companies can use a strategy called value stream management (VSM).
What Is VSM?
According to Plutora, a value stream is a series of steps that must occur to provide a certain product or service outcome. In the case of a digital twin, the value stream extends from the initial creation of the digital twin through advanced growing and scaling stages.
VSM involves outlining each step, determining where value exists, and figuring out how to improve the entire process. It’s a way of tracking digital twin management—and helping team members visualize and understand what’s happening along every step of the way.
The Benefits of VSM for Digital Twins
1. Improved Collaboration
Teams can often change during lengthy IT projects. Current team members may move onto other roles, and new team members may come on board.
Using a VSM service can help team members quickly get up to speed with digital twin management. With a VSM in place, employees can see where the project currently is. This enables them to eliminate confusion and mistakes. In this light, VSM can provide greater visibility for all stakeholders in a digital twin project.
2. Improved Time Management
Digital twins are ultimately just for testing and monitoring purposes. Team members shouldn’t be spending more time trying to create or manage digital twins than their real-life models. The process needs to happen quickly and efficiently.
A VSM platform can help team members break down specific tasks into recommended time frames, allowing teams to keep up with customer demand. This process is commonly referred to as takt time.
For example, a team of engineers working on an application may have 150 feature requests per month and 9,000 working hours to test and complete them. The total takt time would therefore be 60 minutes or less for each feature in order to stay on track.
The team could then take this information and budget time for digital twin management. This information can also be useful when approaching management about hiring third-party MSPs to manage digital twin development.
3. Easier Planning
Organizations often use digital twins for troubleshooting purposes. For example, a team may have a project that’s riddled with performance issues, requiring rapid analysis and remediation.
A VSM platform can enable a team to partake in a process called a Kaizen burst or improvement burst. This is a three-to-five day issue resolution challenge, with the goal of addressing issues and bringing a system to a state of operational efficiency. A successful Kaizen burst can help remove barriers, improve workflows, and better align teams and processes.
Ready To Bring VSM To Your Organization?
Plutora offers a powerful VSM platform that organizations can use to track and manage digital twin projects.
By using Plutora, companies can eliminate many of the backend challenges that can derail digital twins—such as issues with communication, collaboration, and time management.
So if you’re thinking about using a digital twin to manage an upcoming IT initiative, make sure you go about it the right way. We may be a bit biased, but we recommend using a VSM platform to oversee operations.
It can make all the difference, especially if you’re working with many stakeholders spread out across different areas. In any environment, a VSM solution can bring everyone together and keep them aligned—enabling you to get better results.
For more information on the promise of value stream management, check out Plutora today. Also, you may be interested in "Digital Transformation in Depth: A Savvy Leader's Guide."
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