Industrial manufacturing is facing new and growing challenges. The shortage of well-trained specialists is omnipresent. At the same time, the lifecycle of many products is becoming shorter and shorter, while the number of variants and batch sizes is increasing. In addition, the dynamics of the markets and the changing supply chains require ever higher utilization of CNC machines, more transparency in the processes and the ability of the employees to carry out their tasks in a targeted manner. In this complex environment, the concept of the Digital Twin is a great source of hope. It makes it possible to virtually simulate physical objects, machines and systems and to use real-time data from sensors to improve decision-making, among other things. But what exactly is a Digital Twin and how can it help to optimize processes in modern manufacturing?
From a technical point of view, the concept of a Digital Twin is inadequate. Although the goal is to transfer the reality of a physical object with all its details and properties into digital space, such a digital image alone would have no further function and would therefore be worthless.
Digital Twin: Digital model of the real object
The Digital Twin becomes truly useful only through the digital model of the real object and its digital shadow. The digital model is a dynamic 3D representation of a real object that can be used for simulations and analysis. The associated digital shadow of the corresponding real component represents the data collected or to be simulated from this model. Only through the combination of model and shadow is the Digital Twin able to improve products and processes and avoid errors in a continuous cycle of simulation, analysis and optimization based on the information generated.
Industry applications
In industry, Digital Twins can be used at various stages in the lifecycle of a product or individual components. Possible applications in the machine tool and manufacturing industry include
- Virtual evaluation and verification
- Iterative optimization
- Real-time monitoring
- Machine and system management
- Production and manufacturing control
- Condition monitoring
- Predictive maintenance
- Fault detection and diagnosis
- Machine and system performance prediction
Customer benefits when using the DMG MORI DIGITAL TWIN
The advantages of using a Digital Twin are numerous. Using the DMG MORI DIGITAL TWIN as an example, the customer benefits can be divided into three areas:
Increase productive spindle hours
- Shift unproductive activities such as running-in and programming to the virtual world
- Eliminate machine downtime due to collisions
Reduce component costs
- Reduce cycle times through process optimization and visibility of cost drivers
- Eliminate rejects through pre-simulation and simplified troubleshooting
Employee empowerment
- Reduce error rates through early and, if necessary, ongoing training
- Make complex tasks easier to understand through greater transparency
Virtual space machine development
With the DMG MORI DIGITAL TWIN, a new machine can be developed entirely in the virtual world. Its functions and capabilities are simulated, analyzed and optimized using virtual controls, tools, fixtures and workpieces until the result meets all expectations of the innovation. Every step – from pressing a button on the control and changing tools to different clamping situations, axis movements and spindle loads – can be digitally examined and adjusted with and on a Digital Twin. All of this is done before the "real" machine is ever put into production.
Realistic test machining of components
Customers can use the Digital Twin to perform realistic test machining of their components while their CNC machine is still being built. They can perfect CNC programs for the new machine and train their operators long before the machine is installed in their own facility. Once the machine is installed, it continuously transmits information about its status and current jobs to its Digital Twin. This data, in turn, helps to continuously improve processes and make informed decisions.
Digital Twins are not loners. They communicate and work together based on a common language and structure. This applies not only to individual machines, but also to robotic manufacturing cells or automated production systems with multiple machines, pallets and tools, as well as autonomous transport systems and their routes within a facility.
The only requirement is that each element of a system and each characteristic of a service or process must be linked to the associated data as a Digital Twin. The more and better past information is available and the more comprehensive the current data, the "smarter" the algorithms become. This makes analysis more precise and answers more accurate. This is especially important when it comes to predicting events before they happen in the real world.
Definitions for the Digital Twin: Voices from the scientific community
After all these explanations, you may still be wondering how to clearly and concisely define the concept of the Digital Twin. Even academia has yet to come up with a single, unambiguous definition, and there are different approaches to explaining the term. Here are some of the definitions we would like to share with you: