Digital Twins: virtual images of real machines

What is a digital twin?

A digital twin is the virtual representation of an actual machine. By simulating and emulating real components, control programs (PLC processes) can be tested, and the behavior of the machine can be realistically mapped in various scenarios. Based on CAD data, 3D models are created that visualize mechanical movements. This makes the functionality of a system tangible.
 

Digital twins in action

A digital twin offers numerous advantages when considering a machine’s life cycle. The three main use cases include:

• Simulation: 
  This provides advantages through visualization of the mechanics. The movements of mechanical components can be precisely traced, specifically to optimize movement sequences. Newly developed mathematical models for calculating kinematics can be integrated and tested virtually. Simulation also makes it possible to digitally map the object transport and check it for correct behavior.
   
• Testing: 
  During testing, the focus is on verifying the proper functioning of the control code and the defined process sequences. Changes such as new formats, programs, or software updates can be tested virtually before they are implemented on the actual machine - reducing downtime and improving planning reliability. Virtually tested code changes can be seamlessly transferred to the live system.
   
• Training: 
  Operating personnel train and practice virtually for processes including changing formats or cleaning a system before they work on a live machine. This sharpens their understanding of the processes in advance, reduces the risk of errors, minimizes downtimes, and increases operational safety.
   

What does the future of the digital twin look like?

Digital twins have not yet reached their full potential.  In the future, there will be an increasing focus on networking digital models across system boundaries to create a holistic, digital image of complex systems. Strategic partnerships play an important role in pooling expertise and implementing new approaches in practice.

At the same time, we are driving internal process optimization. A standardized project structure ensures greater efficiency, clear processes, and better scalability. We are also working with partners on new functions and expanded simulation options.

Particular attention is being paid to further the development of the models themselves. The goal is to depict the behavior of machines even more realistically - for example through more detailed behavioral models or the integration of simplified flow simulations.

In this way, the digital twin is gradually becoming an indispensable tool - from the initial concept to ongoing operation.