Google Digital Twins - Simulation

Digital Twins vs Simulations:

Digital twins are designed to be an exact replica of a physical object, system, or process. This replica is created using data collected from sensors that are attached to the physical object. 

In contrast, simulations are not necessarily meant to be an accurate representation of reality. Instead, they allow users to test different scenarios and explore different possibilities. Simulations are simplified models that are used to test hypotheses or predict outcomes.

Digital twins can be used for a variety of purposes, from monitoring and diagnostics to control and optimization. 

Simulations, on the other hand, are typically used for experimentation and analysis, training or risk assessment. 

What is a digital twin and how does it work?

A digital twin is a virtual representation of a real-world entity or process.
It is composed of the following three elements:

• a physical entity in real space;
• the digital twin in software form; and
• data that links the first two elements together.

Example of Digital Twins:

• A digital twin of an airplane can be used to monitor its performance and identify potential issues.
• A digital twin of a power plant can be used to monitor its performance and identify potential issues.
• A digital twin of a car can be used to monitor its performance and identify potential issues.
• A digital twin of a person can be used to monitor their health and identify potential issues.

Types of digital twins

Several ways of categorizing digital twins exist, but the following four categories, organized in a hierarchy, are by far the most common:

• Component twins (also referred to as part twins). The most basic level; it's not for simple parts like screws but for things like mechanical subassemblies.
• Asset twins (product). Two or more components whose interaction is represented in the digital twin.
• System twins (unit). Assets assembled into a complete, functioning unit.
• Process twins. Systems working together to serve a larger goal.

Data Analytics & Digital Twins

Digital twins are often used in conjunction with data analytics, as the data collected by digital twins can be used to improve the accuracy of predictions made by analytics software. The use of digital twins also allows companies to conduct “what if” analyses, which can help them to identify potential problems and solutions.

One of the most important benefits of digital twins is that they can be used to improve the accuracy of predictions made by analytics software. The data collected by digital twins can be used to train predictive models, which in turn can be used to make more accurate predictions about the behaviour of systems and processes.

How businesses are using digital twins

Digital twins are becoming an important part of Industry 4.0 and the Internet of Things (IoT). They allow companies to improve product quality, optimize operations and reduce costs. The following are some of the examples citing businesses which are leveraging digital twins:

• Airbus uses digital twins to monitor the health of its aircraft engines in real time. This helps them to identify potential problems early and take preventative action.
• General Electric is using digital twins to monitor the performance of its gas turbines. This helps them to identify potential issues and optimize operations.
• Ford Motor Company is using digital twins to model the behavior of its vehicles in order to improve product quality and safety.
• Siemens is using digital twins to model the behavior of its manufacturing processes in order to improve efficiency and reduce costs