In a Nutshell

A digital twin is a virtual image of a physical object
There are four basic types of such virtual twin systems
Digital twins are particularly suitable for large-scale projects
Digital images are often superior to simple simulations
The quality of virtual images depends on the quality of the data

What is a Digital Twin?

A digital twin is a virtual replication of a physical machine, process or system. This virtual copy uses real-time data to reproduce the actual life cycle of the physical original as accurately as possible. With the help of this digital copy, processes can be simulated and tests carried out to optimize the performance and efficiency of real assets.

How does a Digital Twin Work?

A digital twin uses real-time data collected in physical systems / facilities to map the real use of an asset as accurately as possible. For example, IoT sensors are used to continuously collect data from real physical systems (temperature / power consumption / throughput), which - depending on the asset - is suitable for processing.

Before the data can be used for this purpose, it must be checked and standardized accordingly. At this point, AI can also help to ensure the necessary data quality for use and guarantee the relevance of the data for the respective application.

In the next step, this relevant real-time data is fed into the virtual copy of the system, machine or plant or used to create this image (data integration). Once the modeling is complete, this copy is subjected to exactly the same “loads” as the physical original.

The digital twin can now be used to simulate a wide variety of processes or changes using regularly provided, authentic real-time data. These range from small adjustments to the system to complex “what-if” analyses. This allows potential errors, faults or inefficiencies in the digital image to be identified and, ideally, rectified without affecting the physical system.

Twin Systems vs. Simulations - What are the Differences?

At first glance, working with a digital twin system looks like a simulation. In fact, such a digital image in its own virtual environment is much more interesting for industry than pure simulations.

Instead of individual, isolated simulations, a digital twin can be used to run through complex test scenarios - as often as required and in the finest variations. With minimal effort, a wide range of variables can be adapted in the process and taken into account in the twin system in order to test them.

So while simulations are well suited to depicting strictly defined individual scenarios, digital twins can also depict very complex scenarios thanks to constant updating with real-time data. Appropriately set up twin systems are therefore much more granular and can replicate multifactorial influences on assets such as plants and systems much more precisely and predict their possible effects.

Types of Digital Twins

In practice, various types of digital twin systems are used. The most suitable variant depends on exactly what kind of digital image is to be created.

Component Twin

Component twins are the most basic version of a digital image. These are often used in manufacturing and mechanical engineering to create virtual copies of parts or components of an overall system.

In this way, critical components such as motors or mechanical parts can be continuously checked in order to make precise predictions about their suitability in the process, possible signs of wear and correct maintenance intervals on the basis of the virtual copy.

Asset Twin

Virtual images of complete assets are created here, which typically include entire machines or simply several interacting components. The sensor data of the physical assets can be used to determine their status and performance.

The real-time data from these assets is then used to detect any inefficiencies in their interaction or to plan predictive maintenance.

System Twin

Digital system twins are used for the virtual replication of entire (manufacturing) systems or (production) plants. They offer the possibility of mapping an entire system instead of individual sub-areas. This can also include a bundle of individual assets.

Such a digital twin can be used to precisely determine the overall performance of a system in order to uncover and realize optimization potential - for example, by eliminating redundant processes or identifying bottlenecks.

Process Twin

Process twins are used for the detailed reproduction of business processes as a whole. At this top level, we look at how several systems work together in practice and whether they are optimally coordinated.

A digital twin of your own business processes provides virtual information about where subordinate systems work together seamlessly or less efficiently. This data can then be used to balance synergies and interdependencies between these systems in the best possible way.

In practice, it is quite common that several types of digital twins are (or can be) used in a single company. At GFOS, we are happy to support you in professionally integrating the right system solutions for your requirements into your processes - for example with the help of our powerful MES software solution. Please do not hesitate to contact us.

The Advantages of Digital Twins - Benefits in Practice

The professional implementation of digital twins is usually a major project in itself. However, companies can look forward to a range of benefits afterwards. Here is a selection of the strengths of virtual twin systems:

Maintenance & Servicing

With the help of real-time data from operation, the digital image of a machine can be used to simulate when signs of wear will occur or failures are to be expected. This information can be used to plan maintenance measures in advance in order to avoid costly breakdowns and reduce maintenance costs.

Optimization of Processes

A digital twin enables virtual test runs to be carried out under various conditions in order to check whether systems/machines are and remain fully efficient throughout their entire life cycle. The simulation of these scenarios provides important clues to uncover bottlenecks in the provision of materials or other complications in the processes.

Virtual Product Development

The use of product prototypes can also be simulated using a digital twin. This allows valuable data to be obtained on the performance to be expected in certain areas of application and where any weak points in the structure/design can be found. These can be addressed directly on the basis of these tests.

Sustainable Increase in Efficiency

A virtual copy of complete systems and processes gives those responsible a holistic view of workflows and interrelationships. From this perspective, a wide range of scenarios, adjustments and changes to processes can be simulated in order to evaluate their impact on the systems and processes. In this way, the overall efficiency of a company can be increased step by step and based on data.

Industries at a Glance - Where a Digital Twin is Used

The possible areas of application for digital twins are diverse and cover several industries. We have listed three fields of application here as examples.

Manufacturing Industry

The manufacturing industry uses digital copies of production systems or even individual machines to analyze and optimize their performance data. The virtual images of production processes can be used to reproduce workflows and easily simulate even extensive adjustments in production facilities.

Automotive Industry

In the automotive industry, digital twins are suitable for the development and simulation of new vehicle models, among other things. Based on virtual copies of cars or prototypes, various design options can be tested and the driving behavior and fuel consumption of the vehicles can be optimized.

Logistics / Supply Chain Management

In supply chain management, virtual copies of supply chains provide valuable insights into processes, the utilization of delivery routes and possible dependencies. This data is then used for the sustainable optimization of fleet management.

As impressive as the strengths and potential applications of this technology are, it does not make sense for every company to rely on digital twins. The larger the company and the more comprehensive its own project plans, the more profitable it typically is to create virtual images (of parts) of its own production.

Challenges When Using Digital Twins

The use of digital twin systems can be a lucrative investment, especially for large companies - as long as the most important challenges are known and taken into account during implementation.

Complex Implementation / Setup

The less a company has dealt with the possibilities of Industry 4.0 to date, the more costly and complex the introduction of digital twin systems will be. The intensive use of (IoT) sensors, for example, is indispensable and requires expert integration in order to aggregate the necessary data from the processes in the first place. This requires the use of specialized software and hardware as well as professional support during setup - if these skills are not available internally.

Ensuring Data Quality

Inaccurate, incomplete or outdated data can lead to incorrect analyses and decisions. The integration of valuable, relevant data is crucial to the added value that digital twin systems create. In order to use the digital twin effectively, it is crucial that this data is continuously collected and processed. However, the availability of such real-time data can be problematic, especially for older systems.

Data Protection Requirements

Virtual twin systems are entirely data-driven, meaning that high-quality data must be provided on an ongoing basis for accurate mapping. Depending on the industry (medicine, etc.), this data can be very sensitive. Companies are therefore required in several respects to ensure that the IT infrastructure used is protected against possible data loss, cyber attacks or other incidents.

Economic Efficiency Issues

Depending on the specific type of digital twin, the creation and ongoing maintenance of such a virtual replica can represent a significant investment. Companies should determine in advance whether a virtual replica of components, assets, systems or processes actually delivers sufficient added value in practice to justify these costs.

Using Digital Twins - With the Support of GFOS

How can a digital twin be used in the best possible way? What needs to be considered with regard to the quality of the data and its preparation? And does such an investment pay off for your company? Rely on the expertise of GFOS and let us advise you professionally on high-performance virtual solutions. We look forward to hearing from you.