Digital Twin Tutorial

The development of Internet of Things (IoT) has paved the way for a lot of new technologies, among which Digital Twin is a notable one. The concept of Digital Twin is mainly used in different industries like logistics, healthcare, automation, manufacturing, asset management, etc.

What is a Digital Twin?

A Digital Twin can be defined as a virtual representation of a physical object or a process that simulated the performance of its counterparts in the real world.

Digital Twin technology is used to predict and analyze the performance of physical assets. It is classified into different types and they perform different functionalities. We will cover all these points in detail in the subsequent chapters of this tutorial.

Who Should Learn Digital Twin Technology?

Digital Twin technology was initially originated by NASA when they wanted to simulate the physical model performance of an aircraft. Later on, this innovative technology created a huge impact on manufacturing and other industries as well.

Equipment manufacturers started deploying Digital Twin technology in their operations for sustainable growth. This technology is also paired with AI and ML to generate predictive models and produce accurate results.

Digital Twin technology will be helpful for all professionals who are aspiring to make a career in the field of digital transformation, digital replica, predictive data analysis, big data analytics, asset management, and R&D domains.

Prerequisites to Learn Digital Twin

Digital Twins are used for modeling and design purposes. The virtual models are used to represent the physical performance and design solutions are used to improve the physical counterparts.

You must have a good understanding of IoT concepts such as devices and data. It will be an added advantage if you have a working knowledge of Python, Azure, Java, SQL queries, CAD drawing, etc.

FAQs on Digital Twin

There are some very Frequently Asked Questions (FAQs) on Digital Twin, this section tries to answer them briefly.

1. What are the technologies used in Digital Twins?

Digital Twin can be integrated with a variety of new technologies. It supports the following technologies −

• Artificial Intelligence
• Internet of Things (IoT)
• Big data analytics
• Data Management
• Cloud Computing
• Cybersecurity
• Project Management
• Software Development
• 3D Representation Models
• Augmented Reality Systems

2. What are the characteristics of Digital Twins?

Digital Twin technology provides accurate models and simulations of physical systems. Some of its notable characteristics are listed below −

• Digital Twins have the ability to predict complex data sets using mathematical functions.
• Digital Twins enable the connectivity between physical object and its counterpart.
• Digital Twins can get real-time data with the help of sensors and they can simulate what happens in reality.
• Digital Twins can be used to perform predictive analysis. They provide modularity to track the performance of data.
• Digital Twins provide digital traces that are useful in diagnosing problems and provide fast computation of data.

3. What are the benefits of using Digital Twins?

Digital Twin technology has the potential to offer a lot of benefits to its users. We have listed here some of the major benefits that Digital Twins can offer −

• Predictive maintenance and development
• Performance monitoring
• Process optimization
• Ensure quality and integrity
• Protecting data privacy
• Accurate models
• Improve operational and engineering efficiency
• Improve the customer experience

4. What are the different levels of Digital Twins?

Digital Twins are classified into different levels based on their complexity, scope and different industries applications. Let us briefly understand each level, one by one −

• Virtual Twin − First level. It is a replica of physical asset.
• Connected Twin − Second level. It incorporates data and integrate asset performance.
• Predictive Twin − Third level. It identifies potential issues and forecasts the outcome.
• Prescriptive Twin − Fourth level. It combines advanced modeling techniques.
• Autonomous Twin − Last level. Learn data from multiple feeds and make decisions quickly.

5. What are the subtypes of Digital Twins?

Digital Twins are divided into the following subtypes −

• Digital Twin Prototype (DTP) − It is used for the design and analysis of physical asset.
• Digital Twin Instance (DTI) − It is linked with physical counterparts.
• Digital Twin Aggregate (DTA) − It is the aggregation of DTI, used in order to get information about physical products.

6. What are the different modeling methods in Digital Twin technology?

Digital Twin models helps to make better decisions and perform extensive data analysis. Let us understand different models one by one in brief now,

• Data Driven Model − It is used to optimize the scheduling techniques.
• Similarity Model − It takes records from similar machines based on the previous history.
• Survivor Model − It takes data from failure.
• Degradation Model − If there is no failure data then take the data from safety threshold.

7. What are the use cases of Digital Twin technology?

Digital Twin is a set of adaptive models. It replicates physical system and predict the performance of real time actions. It supports wide range of use cases that highlight the performance of current digital environment.

The sensors designed and installed on physical asset that generate extensive data. Digital Twin technology may range from simple to complex depending upon the use cases.

Some of the use cases are listed below −

• Aerospace and Defense sector
• Streamlined and Supply chain process
• Advanced diagnostics
• Renewable energy optimization
• Oil and Gas sector
• Sustainable operations
• Disaster management
• Cargo management
• Agricultural industries

8. What are the popular tools used in Digital Twin technology?

Digital Twin supports several different tools, some of which are listed below −

• Ansys Twin Builder
• Autodesk Tandem
• Azure Digital Twins
• Bentley Systems
• AVEVA
• ANSYS
• COMSOL Multiphysics

9. What are the main pillars of Digital Twin technology?

Digital Twin services help business to optimize the operations and achieve their goal easily. The latest tools provide accurate representation of physical assets or systems and generate valuable performance and behavior.

The important pillars of Digital Twin technology are −

• Combine data
• Connectivity
• Processing

The above three pillars help to create software design patterns that represent physical objects. We can easily achieve fast production and reduce maintenance and equipment downtime. Also, we can check the performance anywhere.