Dynamic risk assessment for CBM-based adaptation of maintenance planning

This paper proposes a practical method for dynamic maintenance planning based on Dynamic Risk Assessment (DRA). This is founded on the interpretation, in terms of risk levels evolution, the available information of monitoring events and maintenance activities integrated in and that conform the condi...

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Detalles Bibliográficos
Autores: Martínez-Galán Fernández, Pablo, Guillén López, Antonio Jesús, Crespo Márquez, Adolfo, Gómez Fernández, Juan Fco., Marcos Alberca, Jose Antonio
Tipo de recurso: artículo
Fecha de publicación:2022
País:España
Institución:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/116191
Acceso en línea:https://hdl.handle.net/20.500.14352/116191
Access Level:acceso abierto
Palabra clave:DRA
CBM
Maintenance decision making
Maintenance planning
Risk-based maintenance
Risk levels
Ciencias Sociales
5311 Organización y Dirección de Empresas
Descripción
Sumario:This paper proposes a practical method for dynamic maintenance planning based on Dynamic Risk Assessment (DRA). This is founded on the interpretation, in terms of risk levels evolution, the available information of monitoring events and maintenance activities integrated in and that conform the condition-based maintenance (CBM) processes. DRA proposal is supported by ISO 31000 risk management framework in order to better understanding and results integration within other risk management approaches. Proposed method analyzes CBM results (monitoring events and maintenance activities) regarding their impact on failure risk level, and how to program and manage maintenance decision making (maintenance planning) regarding with dynamic risk evolution. This strategy not only helps maintenance management optimization but also facilitates the link of intelligent maintenance with global risk management within the organization, which is lined with modern Asset Management principles. To illustrate the method, an example of a real use case is presented where it is applied to the dynamic maintenance planning of a critical component in a high-speed train, and which integrates monitoring, predictive analytics and inspection data