Predictive Models Applied to Heavy Duty Equipment Management

Acuna, G.; Curilem, M.; Araya, B; Cubillos, F; Miranda, R.; Garrido, F

Keywords: availability, asset management, svm, NARX, Predictive models, Mining Equipment, Mean Time between Failures, Mean Time to Repair

Abstract

In this work we present the development of nonlinear autoregressive with exogenous inputs models to predict some relevant variables for asset management of heavy mining equipment, like Mean Time between Failures (MTBF), Mean Time to Repair (MTTR) and Availability is presented. The models were developed using support vector machine with historical data obtained on a daily basis during 2013 from one heavy mining equipment of an important copper mine site in Chile. One-step-ahead predictions of the predicted variables confirmed good performance of the dynamic models.

Más información

Título según WOS: Predictive Models Applied to Heavy Duty Equipment Management
Título según SCOPUS: Predictive models applied to heavy duty equipment management
Título de la Revista: EDUCATING FOR A NEW FUTURE: MAKING SENSE OF TECHNOLOGY-ENHANCED LEARNING ADOPTION, EC-TEL 2022
Volumen: 8857
Editorial: SPRINGER INTERNATIONAL PUBLISHING AG
Fecha de publicación: 2014
Página de inicio: 198
Página final: 205
Idioma: English
Notas: ISI, SCOPUS