Lecture
Digital Transformation and Digital Twins: Prerequisites and Potentials
- at -
- ICM Saal 3
- Type: Lecture
Lecture description
Data is the new gold. Also in the biotech domain, we have to enrol into using the data, else our business will not survive. But how? What are the steps to take in order to cope with the vast variety of data sources? Which steps do we need to do to preprocess and contextualize the data, so that we can convert data into information and knowledge?
However, we shall not do all this without having clear use cases in mind. Therefore this contribution also focuses on the potentials of using well contextualized data to develop digital twins and demonstrated the potential to deploy the digital twins along the product life cycle.
Therefore we show how Physics Informed AI enables the deployment of digital twins in real time use cases, as well as how digital twins can be concatenated to build end-toend digital twins. The latter one allows in addition robust prediction of product qualit at the end of the process chain as well as compenstory and optimizing actions to avoid batch failure and increase business economy.
So the potentials of the show approach are: Being quicker in process development and chracterization, being more predictive in tech transfer and validation, as well as allow for process robustness and optimization in manufacturing using digital twin based control as well as real time release using end to end solutions.
However, we shall not do all this without having clear use cases in mind. Therefore this contribution also focuses on the potentials of using well contextualized data to develop digital twins and demonstrated the potential to deploy the digital twins along the product life cycle.
Therefore we show how Physics Informed AI enables the deployment of digital twins in real time use cases, as well as how digital twins can be concatenated to build end-toend digital twins. The latter one allows in addition robust prediction of product qualit at the end of the process chain as well as compenstory and optimizing actions to avoid batch failure and increase business economy.
So the potentials of the show approach are: Being quicker in process development and chracterization, being more predictive in tech transfer and validation, as well as allow for process robustness and optimization in manufacturing using digital twin based control as well as real time release using end to end solutions.
