Digital Twin Explained
The term digital twin basically refers to the digital representation of physical assets such as production facilities, products or supply chain networks throughout their life cycles. From product development to process management to supply chain optimization, digital twins enable companies to digitally test new concepts or simulate optimizations on existing physical entities.
In this way, they are able to perfect the digital representation of an asset before a physical prototype is even built. Digital twins can also be used to evaluate the impact of changes to existing systems and processes without disrupting their real-world operations.
Composition and architecture of digital twins
A digital twin is typically composed of three elements:
- A physical object in real space
- The digital twin as a software entity
- Data that connects the first two elements
The generation of a digital twin requires various components. Usually, these is a real object to be mapped, a virtual representation space, and data on the environmental conditions. The twins are generated by collecting real-time data of the physical object and descriptive algorithms and then mapped into a digital representation space. Often a modular concept is used, where the Digital Twin is composed of many individual Digital Twins. For example, a Digital Twin of a car might consist of the individual twins of the chassis, the body, the engine, the tires, etc. The engine, in turn, is composed of Digital Twins of individual engine components. Digital twins of a complete production line can be divided into three basic individual twins. These are:
- the digital twin of a product in the form of a CAD or 3D model
- the digital manufacturing twin in the form of machines, tools, and programs
- the digital performance twin in the form of delivery times, production times, and production or quality metrics.
What are the various advantages of having a digital twin?
The use of a digital twin offers a variety of advantages. The efficacy of certain concepts can be tested in virtual environment before investing into actual hardware. The risk of malfunctions or errors in actual physical processes is reduced. Quality and efficiency improvements in production are the results. In addition, development and launch times for products or processes are reduced, and overall flexibility increases.
Suppose you have a power bank that you can use to charge your smartphone and other devices via a USB cable. If this power bank features a digital twin, you could virtually test how many times you can charge your specific device and how long your power bank will last in its current use. Additionally, the digital twin may also be able to detect malfunctions and bugs in the use of the device that would sooner or later significantly shorten the life span.
- Easier and faster coordination with suppliers by checking the product properties of a workpiece with the help of its digital twin
- Meaningful, insightful forecasts of product and plant characteristics performance and operational behavior.
- Holistic view of products and plants in real time, and easier and faster
- Deep understanding of operations and processes through an in-depth study of the behavior of digital twins
- Error-free, optimized operating processes right from the beginning
- Saving time in the development and production processes
- Ability to conduct optimization of the manufacturing plant and process design while still in the early planning phase
- Smooth commissioning through prior simulations and tests
- Efficient modifications of products and processes through testing and simulation of effects in digital environments
Different stages of digital twinning
The digital twin is able to assist the company in every stage during the lifecycle of an object. In the initial research and design stage, a digital twin can be used to illustrate the different effects of different decisions. This is particularly interesting for Formula 1 or aerospace engineering, for example, where even small changes to the outer shell can have a major impact on the aerodynamics and thus on the speed and fuel consumption of a device. After research, there is the production process: Digital twins are able to assist companies to conduct their operation with more efficiency, and higher quality standards.
In the final phase, an issue that virtually every company has to deal with right now, in terms of corporate reputation and external impact, arises: The recyclability of products. Digital twins can help you identify and implement reuse and upcycling potential. Furthermore, the digital twin can help reveal specific weak points in your products that can be eliminated, and your object can be used over a longer period of time.
Digital twins FAQ
How do digital twins benefit Industrial IoT?
The term ”Digital Twin” is usually used for the digital mapping of an object from the ”Internet of Things”. This means that any industrial product can be dynamically digitally mapped. With the mapping of the entire company organization by the ”Digital Twin of an Organization” (DTO), the optimal and comprehensive planning of all processes in the company becomes possible. The software solutions available today and obtainable from the cloud provide important building blocks for the realization of this vision.
Digital Twins ensure up to 30 percent shorter throughput times and, for example, improve the efficiency of machine deployment in Industry 4.0 by around 20 percent through ongoing real-time data analysis from production.
What types of digital twins exist?
The different varieties of digital twins can be grouped into 4 main categories:
1. Asset Twins
Asset twins describe how individual elements work together as a whole. Asset Twins are able to receive data from Component Twins. Component Twins tend to be rather focused with the durability and stability of individual components. Asset Twins on the other hand, let you validate a whole system. They can be used to check the compatibility between individual components.
2. System Twins
System twins, also called unit twins, operate at a higher level. They combine various individual asset twins and provide you with the ability to review how these individual twins work together.
3. Process Twins
A process twin can be used to simulate the whole operation. Only at this level does the full complexity of monitoring via digital twins become evident. After all, a process only becomes functional and effective when all units, assets, and components fulfill their purpose.
4. Component Twins
This is the most basic and common form of a digital twin. A twin of a single component in the entire system.
How do I find the ideal digital twin solution?
As already mentioned: A solution should be individually conceived, designed and implemented. The decisive factors are the market strategy pursued, the processes and workflows already set up, the possible continued use of legacy devices and systems, and subsequently also the innovation goals and perspectives that must be incorporated into the search for a solution.
And, of course, plant safety and data protection are also of great concern. With the exact mapping of the company organization or a production process, the necessary performance requirements also emerge. It is imperative that technology is never an end in itself, but is aligned with existing operational processes and communication requirements.