Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceTechnology has accelerated the growth of the Facility Management industry and its roles are
broadening to encompass more responsibilities and skill sets. FM budgets and teams are becoming
larger and more impactful as new technological trends are incorporated into data-driven strategies.
This new scenario has motivated institutions such as the European Central Bank to initiate projects
aimed at optimising the use of data to improve the monitoring, control and preservation of the assets
that enable the continuity of the Bank's activities. Such projects make it possible to reduce costs, plan,
manage and allocate resources, reinforce the control, and efficiency of safety and operational systems.
To support the long-term maintenance strategy being developed by the Technical Facility
Management section of the ECB, this thesis proposes a model to calculate the Left wear margin of the
equipment. This is accomplished through the development of an algorithm based on a fuzzy logic
system that uses Python language and presents the system's structure, its reliability, feasibility,
potential, and limitations. For Facility Management, this project constitutes a cornerstone of the
ongoing digital transformation program
