In the past two decades, the use of ontologies has been proven to be an effective tool for enriching existing information systems in the digital data modelling domain and exploiting those assets for semantic interoperability. With the rise of Industry 4.0, the data produced on assembly lines within factories is becoming particularly interesting to leverage precious information. However, adding semantics to data that already exists remains a challenging process. Most manufacturing assembly lines predate the outbreak of graph data, or have adopted other data format standards, and the data they produce is therefore difficult to automatically map to RDF. This has been a topic of research an ongoing technical issue for almost a decade, and if certain mapping approaches and mapping languages have been developed, they are difficult to use for an automatic, large-scale data conversion and are not standardized. In this research, a technical approach for converting existing data to semantics has been developed. This paper presents an overview of this approach, as well as two concrete tools that we have built based on it. The results of these tools are discussed as well as recommendations for future research.