DocumentCode :
3761855
Title :
Prediction of the criticality of a heavy duty mining equipment
Author :
Millaray Curilem;Cristian Huanquilef;Gonzalo Acuna;Francisco Cubillos;Beatriz Araya;Guisselle Segovia;Carlos P?rez
Author_Institution :
Departamento de Ingenier?a El?ctrica, Universidad de La Frontera (UFRO) Temuco, Chile
fYear :
2015
Firstpage :
1
Lastpage :
5
Abstract :
In this paper, we are concerned by the improvement of the maintenance procedures in heavy mining equipment. Criticality is an important concept in the maintenance task because it points out which piece of equipment has a higher probability to fail, and how this failure may impact the general productive process. The paper proposes a definition of criticality of equipment, based on an expert´s experience and on historical data of seven asset management variables of a mining process. We propose a criticality semaphore and a method to classify the criticality of the next month and the subsequent month, based on the present values of the asset management variables. This is a preliminary work, however the results show a good prediction performance of criticality.
Keywords :
"Maintenance engineering","Support vector machines","Databases","Asset management","Mathematical model","Mining equipment","Data mining"
Publisher :
ieee
Conference_Titel :
Computational Intelligence (LA-CCI), 2015 Latin America Congress on
Type :
conf
DOI :
10.1109/LA-CCI.2015.7435946
Filename :
7435946
Link To Document :
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