In the last few years, digital twins — virtual replicas of physical products — have become increasingly popular. A digital twin is a virtual replica of a physical object that can be used to optimize manufacturing and product design. The concept is also being applied to other use cases, such as monitoring and simulating the performance of buildings and infrastructure.
Digital twin technology is evolving beyond just product manufacturing and beginning to impact the real world — for example, by optimizing operations for smart buildings or improving predictive maintenance for critical infrastructure.
In this article, we’ll take a deeper look at what exactly digital twins are and how they’re being used in industry today. We’ll also explore some of the ways this technology has the potential to revolutionize our world by increasing efficiency, maximizing productivity and reducing waste across a wide range of industries.
Digital twin technology is a relatively new concept that has the potential to revolutionize how we understand and interact with the world. A digital twin of something is a virtual representation of that “something.” It could be a person, an airplane engine, or even an entire city.
In its most basic form, the digital twin is a metaphor for the relationship between two things: the physical and the digital. The digital twin concept is based on combining simulations and models with real-time data to create an accurate replica of a product, process, or service.
Digital Twin Technology Is All Around You
The Digital Twin concept was originally developed in 2002 by Dr. Michael Grieves at the Florida Institute of Technology to describe a virtual representation of a physical object.
It’s one of those “Why didn’t I think of that?” ideas. It’s so simple and intuitive that it seems obvious. But like all seemingly obvious ideas, the digital twin is an invention that has to happen at exactly the right moment in history for two reasons: sensor technology and data processing power.
Think about what a digital twin is: It’s a virtual copy of an actual thing or system connected by sensors to a data processing engine that gathers information from the real-world counterpart, analyzes it, and then brings it back to its digital self. The idea is that you can use the digital twin to predict how your thing or system will work before you even build it.
Now digital twins are being applied to industries as diverse as transportation and logistics, manufacturing, aerospace engineering, healthcare and smart cities. And they are being used in more functional ways too – not only to design things better but also to operate them more efficiently and effectively once they’ve been built
Digital Twin Technology has been a buzzword for quite a while now. And it’s not hard to see why. The term was coined by Gartner analyst Dr. Michael J. Gourlay in 2003 as a way to describe the “digital representation of a real-world entity or system.” As the name suggests, digital twins are virtual models of physical products or processes that can be used for various purposes such as monitoring, simulating, and improving efficiency.
The concept of the digital twin is not only exciting but also revolutionary. In fact, it’s been rated one of the most disruptive technologies to have emerged in recent years. And we’re not exaggerating here. According to Gartner, by 2021, “40% of industrial manufacturers will use digital twins, resulting in those organizations achieving a 10% reduction in product development costs and a 15% reduction in product/service recall costs.”
Some of the most exciting innovations that are going to disrupt manufacturing and other industries in the coming years are related to digital twins.
Digital twin is a digital replica of a living or non-living physical entity. Digital twin uses sensor data to inform itself about its “physical twin” and changes its behavior accordingly. It can be used for monitoring, analyzing and predicting what is going to happen with the physical entity that it represents.
Digital twins have been around for a long time. NASA started using them back in the 1960s during Apollo Moon landing missions. They have been using digital twins ever since to simulate their space missions. Digital twins are also used in aircraft industry, where they are called virtual prototypes. However, cost has always been a limiting factor for wider adoption of this technology until now.
With the emergence of affordable sensors, big data and IoT connectivity, digital twins will become a reality for many industries in the near future. The manufacturing industry is expected to benefit the most from this advance due to its complexity and high value of its products. Predictive maintenance is one of the most common applications of digital twins, but we will see them being used in all areas of manufacturing including supply chain management, equipment design and optimization of production processes. With widespread use of this
A digital twin is a digital replica of a living or non-living physical entity. Digital twin refers to a digital replica of potential and actual physical assets (physical twin), processes, people, places, systems and devices that can be used for various purposes. The digital representation provides both the elements and the dynamics of how an Internet of Things (IoT) device operates and lives throughout its life cycle. Because a digital twin is constantly updated with data from its associated physical product, it can be used for monitoring, troubleshooting and predictive maintenance.
The concept was first used by Dr. Michael Grieves at the University of Michigan in 2002 to help optimize design and improve operational efficiency for physical assets such as buildings, manufacturing equipment and aircraft engines. By 2005, NASA had adopted the concept and began using it to increase safety for space missions.
What is a Digital Twin?
The key components of any digital twin are:
A unique identity that represents an individual thing or system
A reference architecture that defines the functional model of the thing or system
A visual representation that enables interaction with the models
An analytics engine that optimizes the interaction between people and models in terms of decisions made or actions taken
A digital twin is a replica of a physical asset, system or process. It is a virtual model that can be used for various purposes including monitoring, simulating, analyzing and optimizing real-world applications in manufacturing, supply chain management and outcome prediction.
The concept of digital twin was originally introduced by Dr. Michael Grieves from the Florida Institute of Technology. The idea has been around since 2002 but it has only recently gained popularity after the Internet of Things (IoT) technology became more powerful and affordable.
The first use case for digital twins goes back to all the way in 2003 when NASA’s Mars Rover Curiosity was created using virtual modeling before the physical prototype was built. The interest in digital twin technology has increased rapidly over the last five years especially among large companies. ~~