DT-enabled Validation and Maintenance for Pharma Industrial Processes

The aim of this PhD project is to adopt Digital Twins in order to reduce the time gap between a product being complete, and being delivered to a customer, as well as to optimize maintenance efforts after the product has been delivered. These are crucial for the manufacturing industry, as they relate directly to the time-to-market, and customer satisfaction, thus impacting the revenue of manufacturing companies.

Digital Twins are a promising technology intended to provide a variety of services, however their adoption in industry has not reached a mature stage, and typically focuses on monitoring a few properties, and to some extent predictive maintenance. Through this project, we will contribute to the state-of-art by applying Digital Twins at the validation and certification phases, thus reducing the time gap through digital experiments. Furthermore, we will develop methods for cases where several monitors, if triggered at once, can lead to system inconsistencies.