No doubt about it, twins are fascinating. Think Luke and Leia. The Doublemint Twins. The Grady twins from Stanley Kubrick’s The Shining. (Okay, the Gradys are also terrifying.)
Equally fascinating—and, fortunately, not nightmare inducing—are digital twins, virtual doppelgängers of a physical factory, product, or process. A digital twin is connected to its physical counterpart by real-time data that’s gathered through sensors and other sources. The result is a constantly updated simulation model, powered by artificial intelligence (AI) and machine learning, that can be used to monitor, maintain, and optimize the physical model. By offering real-time insights into equipment and other assets, digital-twin technology is a boon for manufacturing, helping to reduce maintenance issues and ensure optimal production output. Read about how digital twins work today—and the promise they hold for the future.
1. The Digital Twin in the Product Lifecycle
Where in the product lifecycle do digital twins have the greatest impact? Research facilities provider Catapult surveyed 150 engineers from an array of disciplines to find out. According to the engineers, the maintenance, repair, and operations stage reaps the most benefits from digital twins, followed closely by manufacturing. Digital-twin technology also provides value for the simulation and quality control stages, engineers said. Read the article.
2. How Quickly Is AI Being Adopted in Manufacturing?
A Global Market Insights report published this month estimates that the market size for AI in manufacturing surpassed $1 billion in 2018 and is anticipated to grow at a compound annual growth rate of more than 40% from 2019 to 2025. Other reports, though, see AI adoption at a slower rate, noting that successful applications of the technology are often realized in smaller or isolated projects, where ROI can be more easily realized. Additional factors that may slow mass adoption include confidence in the technology, as well as scaling and connectivity issues. However, thanks to the ubiquity of cloud-computing services, the AI technology in digital twins is accessible and affordable for both large and small companies. Read the article.
3. Smart Twins, Smart Factories
In smart factories, digital twins can simulate potential scenarios and predict outcomes, letting manufacturers test new production strategies—and identify flaws in those strategies—before implementing them in the physical plant. Digital-twin technology can also analyze machine performance and product quality throughout the production lifecycle, helping manufacturers optimize processes to create better products at lower costs. And because digital twins can track overall equipment effectiveness in near-real time, they can serve as an early-warning system: Users can get alerts about possible machine breakdowns and can use predictive maintenance to prevent issues from happening. Read the article.
4. From Improving Aircraft Construction to Preventing Oil Spills
In the UK, the VADIS project, a collaboration between the University of Nottingham and aerospace company Electroimpact, uses digital-twin technology to improve wing construction, which currently employs manual processes that can lead to errors and inefficiencies. For example, if the holes that are drilled in a wing skin are misaligned, workers must make last-minute adjustments on the assembly line. To address this, VADIS is creating a digital twin of the wing, complete with detailed data and measurements of all holes and surfaces, which will be used to precisely manufacture components off-site so employees can focus on assembly, not rework.
Meanwhile, the Swiss firm Akselos builds digital twins for the energy sector, including highly detailed digital replicas of infrastructure such as oil platforms. By creating models that can predict which parts of a platform are prone to failure, the Akselos digital twins allow energy companies to proactively dispatch maintenance crews—preventing an expensive repair or, worse, an environmental accident. Read the article.
5. Digital-Twin Technology in Manufacturing and Beyond
With their ability to enable predictive maintenance, digital twins are an ideal technology for high-risk industries. Chevron, for example, has embraced digital twins: It aims to connect sensors to most of its high-value equipment in its oil fields and refineries by 2024 and expects to save millions of dollars in maintenance costs.
But applications for digital twins extend far beyond the manufacturing industry. The technology offers great potential for health-care operations and patient care, for example. Surgeons can practice procedures on a digital twin of a human organ instead of on an actual patient (uh, thanks). Sensors the size of a Band-Aid can transmit patient vital signs into the cloud, where software can analyze it and alert medical professionals to any abnormalities. Long before there were digital twins, NASA used their precursor—pairing technology—to rescue the Apollo 13 mission. Today, it uses digital twins to explore next-generation vehicles and aircraft. Even cities can have digital twins: Singapore is an early adopter of the technology; its leaders leverage it to help the city-state analyze and improve its energy use, manage town planning, and more. Read the article.