The rise of digitalization has had a profound impact on virtually all domains of society, as is best illustrated by the ubiquitous access to the internet and the various services that run on top. Clearly, digitalization is one of the mega-trends that is affecting work and life in a multitude of ways. In some cases, the ramifications are obvious and clear, in other they are quite subtle. For instance, the development coined Internet of Things (IoT) changes how devices connect and interact, but its relevance for plant infrastructure remains to be seen in full due to rather long investment cycles. The relative ease of data acquisition, storage and access today as well as the availability of powerful computing hardware like GPU’s and simple coding tools like Python to deploy Machine Learning (ML)/ Artificial Intelligence (AI) methods or even packaged commercial tools is broadening the scope for application. Similarly, Digital Twins live and operate on top of these new computing capabilities as well as on existing mechanistic and data-driven modeling and simulation methodologies. They promise efficiency gains through better asset utilization while enabling highly flexible operations.