Even if usually filled in the form of unstructured text, maintenance service reports can be an important source of information for manufacturing companies providing field and remote maintenance services to their customers. By analyzing their content, companies can discover hidden knowledge that can be used for improvement purposes. By exploiting Natural Language Processing (NLP) techniques, this paper wants to show how an Italian company producing machinery can extract new knowledge from its maintenance database. The company under analysis started a servitization journey and need to understand how to improve the maintenance service delivery. By using the information extracted, the company can define improvement plans linked to both the maintenance service delivery and the asset design.
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