Data taxonomy to manage information and data in Maintenance Management

Nowadays Maintenance Management (MM) is covering a primary role for competitiveness in manufacturing. The advent of Asset Management (AM), in which MM is a core function, enlarges the scope MM was used to. Besides, digitalization has brought a vast amount of information and data sources that MM may exploit to improve its processes and asset-related decision-making. This evolution of MM has brought a lot of opportunities but also various criticalities about information and data management. Data models are envisioned to provide significant support to this end. However, a common reference data taxonomy is needed for the correct development of data models. This work aims at exploring how the data taxonomy could help in addressing the current criticalities by synthesizing most information and data classes that support MM. The data taxonomy, along with other elements, like data models, effectively support companies in improving the management of their information and data. The usefulness of a data taxonomy is proved thanks to action research in a company within the automotive sector aiming at improving the MM process.