Enterprise resource planning systems and maintenance management systems are commonly used by organisations for handling of maintenance records, through a graphical user interface. A maintenance record consists of a number of data fields, such as drop-down lists, list boxes, check boxes and text entry fields. In contrast to the other data fields, the operator has the freedom to type in any text in the text entry fields, to complement and make the maintenance record as complete as possible. Accordingly, the text entry fields of maintenance records can contain any words, in any number.Data quality is crucial in statistical analysis of maintenance records, and therefore manual analysis of maintenance records’ text entry fields is often necessary before any decision making. However, this may be a very tedious and resource consuming process.In this article, natural language processing is applied to text entry fields of maintenance records in a case study, to show how it can bring further value in the assessment of technical assets’ performance.Keywords: Maintenance records, Natural language processing, Structured and unstructured data, Data quality, Rail infrastructure.