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Why is the IoT world ringing with this new buzzword?
By Pragati Verma, Contributing Editor, Straight Talk
Digital twins are multiplying, especially among those investing in the Internet of Things. Three in four organizations implementing IoT projects already use the technology or plan to use it within a year, according to a recent Gartner survey.
So, what is a digital twin in the first place? Jeff Hojlo, Program Director, Product Innovation Strategies at IDC Manufacturing Insights defines it as “a connected virtual replica of a physical product or asset that shows and predicts its real-time function and performance.”
Forrester analyst Nate Fleming likens it to a virtual mirror. “If you move one way – so does your reflection. Your reflection is also unique to you. If someone else stepped in front of the mirror, even a sibling, what appeared in the mirror would be different.” The same, he says, “applies to the digital twin — it’s a virtual representation of a single machine as it operates in the real world.”
What about other similar machines performing similar tasks? His explanation is simple: Think of other machines as siblings from the same factory, with the same core design and components but important differences. “These differences are incredibly relevant when managing machines is core to your business, like maintenance history, wear and tear from operations, and enterprise software that interacts with the machine,” he says.
These concepts, he says, are core to real digital twin implementations. “It’s machine specific, it’s a virtual representation that reflects real-time data from the field, and the data within the twin can be used to drive business decisions, improve operations, or even shift core business models.”
Entering the Mainstream
The concept of digital twins is not new. IT executives in large industrial operations have for some time used software-based replicas of sensor-enabled physical assets to monitor performance and help reduce costly unplanned equipment outages. Gartner has included it in top 10 strategic trends since 2017, when it predicted that “billions of things will be represented by digital twins” within three to five years. A year later, their survey revealed that nearly half of the organizations implementing IoT were using or were planning to use digital twin initiatives in 2018. As noted above, the latest Gartner survey found that three-quarters of survey respondents were using or planned to use the technology.
“The results — especially when compared with past surveys — show that digital twins are slowly entering mainstream use,” says Beniot Lheureux, research vice president at Gartner. “We [earlier] predicted that by 2022, over two-thirds of companies that have implemented IoT will have deployed at least one digital twin in production. We might actually reach that number within a year.”
Other analyst firms agree that the deployment of digital twins is on the rise. IDC predicts that 30 percent of global 2000 companies will have implemented advanced digital twins of their operational processes by 2020. These digital twins, according to Robert Parker, Senior Vice President, Enterprise Applications, Data Intelligence, Services, and Industry Research, will “enable flatter organizations with one-third fewer knowledge workers.”
How They Drive Business Value
Besides flatter organizations, digital twins open up other valuable possibilities. Hugh Ujhazy, associate VP for internet of things, IDC Asia-Pacific, lists a few, “By providing companies with a complete digital footprint of products from cradle to grave, the digital twin enables companies to detect physical issues sooner, predict outcomes more accurately, and build better products by maintaining a complete feedback loop from design to retirement."
Maria Terekhova, a Senior Research Analyst at HFS Research, explains these benefits of digital twins:
- Lower spending on asset repair and maintenance
- Predictive rather than responsive business decisions
- Improved regulatory and industrial standard compliance
- Better tracking of efficiency and productivity
All That Glitters is Not Gold
The business case might be obvious, but setting up a digital twin is far from simple. “Technology vendors from a range of backgrounds will tell you they can help you create a digital twin of your products today, but the legitimacy of their claims is left largely to the eyes of the beholder,” warns Fleming.
To explain what makes a good digital twin, he cites an example: a medical device firm retrofitting its equipment with sensors to provide value-added services to customers. “This new sensor data, streaming in real-time, can tip off customers to imminent equipment failures. These types of insights allow the customer to deploy maintenance techs prior to malfunction and even enable those technicians with an augmented reality (AR) experience that digitally contextualizes their job as they interact with the machine,” he added.
Jeff Hojlo, the IDC Manufacturing Insights analyst, seems to agree and insists that every virtual model is not a digital twin. He spells out the differences in a webinar: “They can be a unifying point for all related data about a product or asset. And this includes everything from customer insights information to social sentiment analytics to software performance within connected discrete products, IoT data, assets, factory and facility performance information, supply chain process data, and commercialization information. It’s viewing that data in context that provides a great amount of value.”
What happens when there are multiple digital twins in an organization? Gartner recommends integrating them. For example, in a power plant with IoT-connected industrial valves, pumps and generators, there is a role for digital twins for each piece of equipment, as well as a composite digital twin, which aggregates IoT data across the equipment to analyze overall operations. “What we see here is that digital twins are increasingly deployed in conjunction with other digital twins for related assets or equipment,” says Lheureux.
As per Gartner’s survey, 61 percent of companies that have implemented digital twins have already integrated at least one pair of digital twins with each other, and even more — 74 percent of organizations that have not yet integrated digital twins — will do so in the next five years.
This true integration, says Lheureux, is not easy and requires high-order integration and information management skills, but it might be crucial. “The ability of [organizations] to integrate digital twins with each other,” he says, “will be a differentiating factor in the future, as physical assets and equipment evolve.”