Perfection becomes a virtual reality with Digital Twin 2022

Perfection becomes a virtual reality in the age of the digital twin

Imagine being able to accurately predict system performance over its entire lifespan and deal with problems even before they occur! That would put you ahead of the digital disruption, right? Welcome to Digital Twins – computer systems that predict asset performance using inputs from real-world data. Only large and complex VR assets are justified by their use due to time and expense.

non-stop benefit

The lives of three astronauts were in grave danger when an oxygen tank aboard the Apollo 13 spacecraft exploded on April 13, 1970. Although there was no room for error, NASA mission controllers rigged 15 training simulators and quickly developed foolproof procedures that successfully returned all three men. on the earth. Even if the phrase “digital twin” was not in use at the time, this would likely have been its first use. That’s roughly how useful even basic digital twins were fifty years ago. Simulators are not digital twins per se, hence the term “primitive”. They were approaching digital twins as they experimented to mimic conditions in space.

Turning to the present, Deloitte has used digital twins to reduce the time between changeovers for its industrial clients by 20%. Boeing used digital twins to increase the quality of its first parts by 40%. A single wind turbine could generate an additional $100 million during its life thanks to General Electric’s digital wind farm, which is expected to increase energy production by up to 20%.

Digital twins initially gained popularity in 2017 when Gartner, Inc. listed them. , a technology consulting and research organization, as one of the top ten major technology trends. In 2018, the company released a similar score. That is why by 2026, the global market for digital twins is expected to increase from $3.1 billion to $48.2 billion.

How do digital twins work?

Digital Twin Studios (@digitwinstudios) / twitter

A virtual or digital model, representation or replica of a real object is known as the “digital twin”. It is represented by the physical twin of the origin throughout its entire existence.

  • Input real-time data from the actual origin.
  • Analyzes data and improves asset performance using machine learning, simulation, and inference.

A product, system, or process are all examples of assets. A manufacturing process, a vehicle, an aircraft, a cargo ship, a turbine, an engine, a city, a bridge, a building, an offshore oil platform, a person or another object, for example, may be considered an asset.

Digital twins are essentially computer algorithms that predict asset performance using real-world data inputs. This data is collected by Internet of Things (IoT) sensors, which are also used to predict failures and other issues.

The physical prototype of the asset may also serve as the basis for the digital twin, which will be used to improve its performance before it is produced. Alternately, the prototype may be the same twin. Digital twins scan many processes and get real-time data, unlike simulations. This enables them to run countless simulations to examine different problems from different angles. Instead of real-time data, predictive twins use archived data from other physical assets.

Other than component and partial twins, others manage the data of different entities cooperating. The level represented by digital twins determines how they are classified:

  • The individual components are replicated across Component Twins. Partial twins are the somewhat less important parts.
  • Asset Twins stand for many interconnected elements.
  • System/Unit twins simulate different asset transfers.
  • Digital replicas of two or more systems are known as processing twins.

Applications, disadvantages and pluses

Sophisticated systems are essential to creating, using, and managing assets as they become increasingly complex. It makes sense to be aware of the ever-changing expectations of your customers.

Benefits are related to the information they collect and evaluate:

  • By forecasting asset performance and providing information on how customers use assets after purchase, manufacturers can be on the cutting edge of digital disruption. The latter helps in understanding changing consumer expectations.
  • Enhance the effectiveness of existing product-making processes.
  • Eliminate unused features, goods, or parts by analyzing data on how customers use assets after they have purchased them. Money and time are saved.
  • Before starting manufacturing, research and develop potential performance scenarios to enable better product design.
  • Optimizing processes and redefining erroneous assumptions in product development.
  • Make it easy to determine which method to use as items reach the end of their useful life. Manufacturers may also decide what materials manufacturers may profitably extract from these items.
  • By allowing professionals to test a potential cure on an asset before applying it, maintenance can be made simpler.
  • Increase traceability by creating a digital link across multiple platforms.
  • Repair the device from a distance.

The following are already using digital twins:

The digital twin: creating competencies in the virtual world |  pharmaceutical engineering

  • Energy production Maintenance of turbines, jet engines and locomotive engines can be better planned by instrument operators.
  • Manufacturing processes provide better goods because the process is simplified from design to manufacture. Keep in mind that digital twins depict the entire life of a system or product.
  • Being a systematic, complex configuration of many interconnected systems, cars are an ideal application of digital twins. Vehicle performance and efficiency of production methods are improved through virtual prototyping.
  • Large structures must strictly comply with engineering regulations, such as skyscrapers, bridges, offshore drilling platforms and the like.
  • Health services use digital twins to actually model people to collect and analyze data on health variables.
  • Both augmented reality and real-time, 3D or even 4D spatial information are used in city planning. This makes it possible to better predict the effects of the proposed modifications. The fourth dimension is very mysterious. It is understood to refer to time or something perpendicular to the cube.

Digital twins should not be used in all assets. It can sometimes be technical overkill, Gartner warns. They also raise cost, privacy, security, and integration issues.

It is only economically viable for large and complex systems, processes, and products, such as the following:

  • systems engineering
  • Manufacturing processes
  • power generation and distribution equipment
  • Aircraft and automobile production
  • Railcar design
  • big constructions

Asset-intensive industries, in particular, but all industries, depend on the health and capacity of their assets as well as the performance standards of their operations. As more resources are devoted to enhancing the cognitive abilities of the digital twins, their analytical capacity will grow, thus enhancing their value in production.

Edited by Prakriti Arora

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