Artificial intelligence applied to condition-based maintenance

• Autores: Jesús Ferrero, Juan Francisco Gómez Fernández, Fernando Agustín Olivencia Polo, Pablo Martínez Galán, Adolfo Crespo Márquez
• Localización: Industria química, ISSN 2340-2113, Nº. 57, 2018 (Ejemplar dedicado a: ACHEMA 2018), págs. 44-48
• Idioma: inglés
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• Resumen

  • The recent and remarkable use of Artificial Intelligence (AI) techniques, and particularly, of data mining, allows the improvement of industrial processes through pattern analysis. These tools become very useful when considering condition-based maintenance (CBM) processes, where it is necessary to detect the inflection point in normal operation conditions. In this paper, a novel methodology for CBM is proposed, consisting of 3 data mining techniques: Artificial Neural Networks (ANN), Support Vector Machines (SVM) and Random Forests (RF). Initial analysis of the experiment outcomes suggests that it is recommended to continue the researching efforts in this field because of the improvement obtained in predictive maintenance.