The article shows a way of collecting data to prepare the Overall Equipment Effectiveness (OEE) using the asset administration shell (AAS) in a case study. A systematic approach and the use of established methods are essential for this. The established KPI metric for evaluating equipment effectiveness has proven itself and is used across all industries for quantitative productivity measurement. The digitalization of systems generates a large amount of data from the production environment, which forms the basis for modern analysis methods. These enable, among other things, the detection of anomalies in the plant environment and an increase in machine effectiveness. With the increasing establishment of the AAS, there is a need for pragmatic integration of data that supports the process of asset evaluation and optimization. In this context, the use of the “Time Series Data” submodel offers an effective solution. It defines a uniform standard for the integration and semantic description of time series data. The effective integration of time series data into the AAS environment, which enables the comprehensive use of generated process data, is explained using an example.