In the light of recent challenges in the manufacturing industry, operational data is becoming an increasingly valuable resource. Enabled by developments in digitalization, communication and processing, information describing the current state of assets in production and logistics can be used to assess performance, aid in the decision-making process and serve as a basis for further optimization of production systems. Assembly line resources in the TU Wien Industry 4.0 Pilot Factory are equipped with sensors delivering operational data, which holds a great potential for a better understanding and further development of value creating processes in the facility. Information condensed into Key Performance Indicators (KPI) is of special interest in this aspect, and has to be made available for operational employees of the Pilot Factory in the form of a dashboard visualization. A Digital Twin model based upon a material flow simulation tool has to be used as the central source of information, to consolidate data and to create a continuous information flow from shop floor assets towards the dashboard application, as well as back to the model, where past data can be used for the prediction and optimization of future states. Following a literature research focusing on enabling technologies and metrics relevant for a performance assessment of the assembly process, an analysis of existing information flows was executed. Taking into account the relevance of performance indicators and the availability of raw data, a selection process led to a set of KPIs to be visualized for individual stakeholder roles. These metrics were made available to shop floor workers and operational managers of the Pilot Factory with the development of a personalized, real-time dashboard application, improving their decision-making ability. Additionally, the developed application enables a parametrization of the Digital Twin with collected past data, expecting more realistic simulation results, and finally optimized assembly processes.