What Is a Digital Twin and how is it related to edge computing?

What Is a Digital Twin and how is it related to edge computing?

A digital twin is a virtual representation of real-world entities and processes designed to help businesses optimize operations and improve decision-making. Using real-time and historical data, digital twins can be used to simulate different scenarios. In turn, the digital twins can provide insights into potential outcomes and allow businesses to make more informed decisions.

Digital twins are used in various industrial applications, from predictive maintenance to smart cities, and they rely on integrating information from IT and OT systems. With its focus on outcomes and tailored use cases, the digital twin concept is rapidly gaining popularity as companies look for novel ways to optimize operations.

One of the key efforts to promote digital twin interoperability is the Digital Twin Consortium, founded in 2020 by leading industry players such as Autodesk, Ansys, Bentley Systems, General Electric, Dell and Microsoft. Through this partnership, companies work together to promote the use of digital twin technology. They developed open standards for digital twin models, allowing them to be interoperable across different platforms and applications. This ultimately helps businesses better leverage the power of digital twins to improve their operations and drive innovation.

How digital twin concepts are related to edge computing

At its core, edge computing brings computing power and data storage closer to where they are needed most. This has important implications for digital twins, as real-time data processing and decision-making often means systems must be near the modeled physical entities.

With edge computing, more companies can access digital twins. Companies can avoid the extra cost and time delays often associated with large cloud computing by using smaller, more localized technology resources to gather and manage real-time data. When combined with a digital twin strategy, edge computing can save time and money.

As more companies seek to leverage the power of digital twins for their operations, edge computing will be increasingly important for ensuring data integrity, real-time decision-making capabilities, and overall efficiency.

How are digital twins used in industrial applications?

Digital twins are commonly used in industrial applications to monitor and predict the performance of physical assets. For example, companies in the manufacturing industry may use digital twin models to optimize production processes or improve predictive maintenance practices. For production purposes, the digital twin helps track a machine’s operation and can adjust it in real-time.

Engineers also use digital twins to monitor end products for defects or poor performance. Companies in fields such as supply chain management and logistics can use data from the past to streamline their operations and avoid potential errors. Digital twins also help logistics companies by allowing them to see how different packaging can affect product delivery.

How are digital twins used in other applications, such as Smart Cities?

Digital twins help test city plans before actually putting them into action. Examples of architectural aspects that digital twins can test include housing, wireless network antennas, solar panels and public transport.

Some cities have started deploying sensor networks that collect data on everything from energy use to traffic patterns. This information can be used to create accurate models of city systems and make informed decisions about improving a city’s overall operations.

How groups such as the Digital Twin consortium effort promote interoperability

The Digital Twin Consortium developed a framework for interoperability that allows complex systems to work together seamlessly. This framework considers a range of critical concepts, including system-centric design, model-based approach, holistic information flow, state-based interactions, federated repositories, actionable information, and scalable mechanisms. This framework seeks to facilitate collaboration across disciplines, making it easier for systems of all sizes and types to work together effectively. Additionally, it supports the growing ecosystem of high-value services offered by different vendors, allowing them to plug into a multi-dimensional digital twin system.

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