Algoritmo para la asignación de actividades de mantenimiento utilizando la gestión de conocimiento
[EN] The present study focuses on generating a methodological proposal for the allocation of human resources in the execution of maintenance tasks. This considers the implementation of an algorithm that assumes a set of maintenance activities (tasks or resources), a set of maintenance personnel (age...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | español |
| OAI Identifier: | oai:riunet.upv.es:10251/200421 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/200421 |
| Access Level: | acceso abierto |
| Palabra clave: | Factor humano Asignación de recursos Mantenimiento industrial Human factor Resource allocation Industrial maintenance CONSTRUCCIONES ARQUITECTONICAS |
| Sumario: | [EN] The present study focuses on generating a methodological proposal for the allocation of human resources in the execution of maintenance tasks. This considers the implementation of an algorithm that assumes a set of maintenance activities (tasks or resources), a set of maintenance personnel (agents), a plausibility relationship over resources, a hierarchical relationship over agents and the preference that Agents have about resources. These assumptions lead to a hierarchy of personnel and identification of critical tasks. These hierarchy of personnel takes the management of knowledge as a fundamental part since; the maintenance function requires very specific technical knowledge, normally tacitly stored among the personnel operating in these areas. The methodology is complemented by a new hierarchy of tasks using the methodology of analysis of failure modes, effects and criticality (AMFE). The results applied to a fleet of vehicles show that other assumptions are needed to obtain reasonable and fair criteria in the allocation of maintenance tasks, which are considered as weightings in a knowledge management function that include: Professional experience criteria, experience in the company, talent and self-training. |
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