Some detailed explanation will be helpful, especially for springboarding the rest of this course's resources. Get an overview that provides a substantive explaination of what a digital twin is and the role it plays in industry.
- Let's begin with a simple definition of a digital twin, and then we'll dive a little deeper to expand upon it. A digital twin is a virtual replica of a physical thing. This virtual twin exists only as software rendered by computing power. For the most part, this definition is reasonably adequate. But let's explore it further. Having a digital replica of a physical thing can significantly improve on one or more of the following processes, design, simulation, planning, building, operating, maintaining, optimizing, and disposal. For the design phase, it's possible to virtually create a solution and accurately render it operational before a single physical action is taken. Then we can simulate that solution under different types of real scenarios. For example, isn't it useful to first build a virtual skyscraper, then put it through a variety of earthquakes to accurately understand what might happen? Based on the data provided, the design can then be modified. In the build phase, a digital twin can be used to provide the construction specifications or what we call parametric estimates to different providers. In this way, a digital twin can be an asset in streamlining the procurement process. In addition, and importantly, during build, sensors are applied to the physical object in order to collect and transmit data back to its virtual replica. This is what enables the magic during the operational and maintenance phases. At this point, with enough sensors, the virtual twin is providing all relevant data about the state of the physical twin. For example, an operational machine can render accurately in its digital twin its temperature, vibration, speed, and so much more. All of this becomes possible because of increasingly better digital technologies that include faster computers, better telemetry, that is, the communication of measurements from a collection point to receiving equipment, smaller, more accurate sensors, data management, and artificial intelligence. During operations, an abundance of data is being collected and fed back to its digital twin over a digital thread. Think of this as a data pipeline that enables analytics of various states and stages. Backed by artificial intelligence, the digital twin can identify and even predict maintenance issues before they happen. It has become a data-informed model of a physical system. This compelling feature reduces cost, since it's typically cheaper to proactively conduct maintenance than to repair it after it's broken. Finally, this continuous real-time feed of data can help with optimization. That is, improve its performance by enabling the system to either automatically modify its own behavior or by prompting the manual intervention of a human. Digital twins have become particularly ubiquitous in the Internet of Things or IoT world. IoT devices are everywhere now, in our homes, across our cities, and in our factories, where we call them industrial IoT devices. These internet-connected electronics collect and produce data and services and interact and communicate with each other and central systems. The data collected from these devices creates detailed knowledge, enabling capabilities we will discuss in later videos. The use of digital twins in the context of IoT will likely be one of the defining qualities of the future of this topic. With billions of new IoT devices being deployed and managed each year, it must be clear by now that digital twins have a remarkable future ahead.