Digital Engineering: A New Term In Engineering Field

Digital Engineering: What is it and why should you know it?

Over the centuries, engineers have designed and built physical assets such as dams, tunnels, bridges, and buildings. They are now increasingly producing digital and physical assets: digital twins that provide interactive, real-time models of other parts of a building or infrastructure.

Digital Engineering: What is it and why should you know it?

Digital engineering involves building and informing the data that make up the digital twin. Just as software engineers produce software, digital engineers develop what’s called a building information model, or BIM, which is a digital representation of a physical asset, including data about its design, construction, and future functionality. From the start of an engineering project, their goal is to generate and capture this data in an organized and rational manner, and to collaborate with other stakeholders to ensure high-quality results.

Digital engineering involves building and informing the data that make up the digital twin.

BIM is a very useful technology because it allows architects and engineers to test the performance of a design before it is built, and improve the performance of an asset throughout its life cycle.

But digital engineering also includes drone imagery, augmented and virtual reality, IoT sensors, advanced building materials, and even artificial intelligence and machine learning. Combined with BIM, these techniques can be used to inform the digital twin and ensure that it accurately represents the real-time properties of its physical counterpart.

Digital Engineering: What is it and why should you know it?
Digital Engineering: What is it and why should you know it?

As these digital technologies and capabilities increase and improve, engineers will need new skills to make the most of them. In other words, digital engineers will have traditional engineering skills and knowledge of software engineering, including knowledge of 3D modeling and data science techniques, and how to apply them to engineering projects.

Team building

Given how difficult it is to become a skilled civil, structural or mechanical engineer, it takes a lot of talent and determination to acquire all these additional skills. As a result, individuals rarely have a full grasp of digital engineering. A team with different skills may come together to provide digital engineering.

These teams will need to work effectively with hundreds of consultants, designers, subcontractors and other stakeholders to produce the asset and its digital twin. The entire process generates a large amount of data that needs to be captured and stored; data can come from a wide range of traditional and non-traditional sources, including paper documents and various technological systems.

To successfully capture, structure, and understand all of this information, you need an open platform that can integrate any data source. Building such a platform is Astor’s top priority. In fact, it translates all the different language engineering teams into one common language or one common language so that everyone can easily exchange information and communicate normally. This will ensure that data flows smoothly throughout the asset’s lifecycle, not just the design and build phases.

Performance Management

Over the life of an asset such as an office building, its owners will hire a variety of businesses and individuals to maintain and operate it, from cleaners keeping spaces clean to maintenance teams keeping lights on. All of these fall under the umbrella of facility management. Digital twins will revolutionize the way industries operate by providing dynamic, real-time models of asset operations and environmental performance.

Digital Engineering: What is it and why should you know it?
Digital Engineering: What is it and why should you know it?

Why is digital engineering important?

Well, imagine if one of the devices hidden behind the wall suddenly stopped working. The only way the maintenance team will be able to spot the problem is to break this wall and look behind it. But with a digital twin, they can accurately see the problem and evaluate the best way to solve it without destroying the structure of the building, saving a lot of time and money.

This ability to see exactly what’s going on inside a physical asset is based on something called a semantic data model, which simply captures the “meaning” of data elements and the relationships between them. In other words, if you approach the development of the digital twin in a thoughtful way during the design and build process, rather than just dumping data into it, the facility management team will have a useful digital model to refer to that they have already made asset management decisions.

The process of capturing and storing this data begins when an asset is still just an idea. It is the beginning of a golden thread of information throughout the life of the project, a thread that grows and collects more threads until it develops the weight and weight of the digital character

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