|Neural networks which
"learn" your process can predict product
quality for those properties where there are no on-line
sensors. The neural network models can then be used to optimize your
process. This new technology has matured and packages are now
available for industrial processes.
Being able to continuously predict quality delivers the following benefits:
Neural networks can recognize and match process conditions to QA lab results. The relationships that are identified are updated over time as more process information and QA results are gathered. Thus, processes with variability of raw materials or other process characteristics can learn and adapt.
The accuracy of the predictions is such that the loop can be closed to give real-time process control of the predicted quality parameters.
In fact, any calculated variable can also be used to allow optimization of costs, for example.
Procex has successfully created neural network models to predict:
The Models can be used to:
If you are interested in pursuing this application of modern technology, then Contact Procex!