Diseño de soluciones avanzadas de CBM/PHM en sistemas inteligentes de gestión de activos

Laburpena

The use of analytical and predictive techniques is one of the functional pillars of the process of digital transformation. It contributes to the emergence of two basic capabilities of digital systems or, at a higher stage of development, CPS (Ciber Physical System), focused on the practical use of available data: predictive capacity and knowledge management. Many of these techniques and their industrial applications are being developed within the PHM (Prognostics and Health Management), understood today as a discipline of engineering, and linked to its use as maintenance tool. The results in this field are giving rise to a condition-based maintenance (CBM) of high performance: CBM / PHM. The fundamental challenge now lies in the massive transfer of these advances to practical applications in industry and other productive sectors. Parallel to this process asset management (AM, Asset Management) is being consolidated as a model of reference for organizations. A model that is being proven adequate as a strategic support for the development of digital organization models or Industry 4.0. This thesis addresses, from maintenance engineering, a study of CBM / PHM solutions. The conception of these as a fundamental part of the digital transformation raises the need for a twofold approach: (i) the design and management of these solutions starting from the point of view of the maintenance manager and (ii) integration as a fundamental part of a Intelligent Asset Management System (IAMS) where these tools are connected to the design of key processes for the organization's objectives. As results of the thesis are developed: a methodology for the analysis, design and management of CBM / PHM solutions, with a clear focus to facilitate the capture of expert knowledge of maintenance technicians and to orientate itself to the adequate formulation of the processes of making maintenance decision; and a conceptual model for the definition of an IAMS. In these systems the CBM / PHM process, as it treats and gives access to the formulation "information-knowledge-risk" and subsequent decision-making "risk-value" on analytical and / or quantitative models, is one as one of the key processes of the system and main reference for its definition.