TwinCAT Machine Learning:
Scalable, open and in real time
News | TwinCAT
Machine learning for all areas of automation
Beckhoff now offers a machine learning (ML) solution that is
seamlessly integrated into TwinCAT 3. Building on established standards,
it brings to ML applications the advantages of system openness familiar
from PC-based control. In addition, the TwinCAT solution supports
machine learning in real time, allowing it to handle demanding tasks
like complex motion control. Its capabilities provide machine builders
with an optimum foundation for enhancing machine performance.
The fundamental idea with machine learning is to no longer follow
the classic engineering route of designing solutions for specific tasks
and then turning these solutions into algorithms, but to enable the
desired algorithms to be learned from model process data instead.
For data collection, various proven TwinCAT products are available
such as e.g. TC3 Database Server TF6420 or TC3 Scope Server TF3300.
Training is performed in established frameworks such as MATLAB ® ,
TensorFlow, PyTorch, SciKit-learn, a.o. A trained model can be easily
imported into the TwinCAT runtime in a standardised format (ONNX).
In automation technology, this opens up new possibilities as well
as optimisation potential in such areas as predictive maintenance and
process control, anomaly detection, collaborative robotics, automated
quality control, and machine optimisation.
www.beckhoff.com/machine-learning
14 Product announcement For availability status of the new products see Beckhoff website at: www.beckhoff.com