Eventos Anais de eventos
COBEM 2019
25th International Congress of Mechanical Engineering
FEASEBILITY AND COSTS OF PREDICTIVE MAINTENANCE VIA OIL ANALYSIS IN AGRICULTURAL EQUIPMENT
Submission Author:
Leonardo Rosa Ribeiro da Silva , MG
Co-Authors:
Leonardo Rosa Ribeiro da Silva , Felipe Chagas Rodrigues de Souza, Felipe dos Anjos Rodrigues Campos, Pedro Henrique Pires França, Luiz Eduardo Rodrigues Vieira , Gustavo Henrique Nazareno Fernandes, Wisley Sales
Presenter: Leonardo Rosa Ribeiro da Silva
doi://10.26678/ABCM.COBEM2019.COB2019-1249
Abstract
Agricultural activities depend largely on mechanical equipment and so availability of machines is a key component to guarantee on-schedule operations. In association with a local service provider of this segment, feasibility of predictive maintenance through oil analysis was assessed. Wear particles and contaminants were measured via spectrometry analysis which is one of most important tools for lubricant assessment. Water content and viscosity were also evaluated. Samples were analyzed by a tribology laboratory and results for viscosity, Fe content and contaminant levels were compared to acceptable limits. Results provided information about condition of engine, final reduction gearbox and differential gearbox, which are critical component for tractors. Problems like excessive wear particles and water content revealed root causes like dust contamination, defective seals and leakage in oil intercooler. Costs of repair and inspection due to predictive maintenance were compared to costs that would result from corrective maintenance. Oil analysis permitted considerable maintenance economy compared to parts and services necessary when tractor breaks down. Since unavailability of equipment may also cause loss of profit, product and clients, this predictive method can be considered effective and advantageous for agriculturists. Additionally it also benefits local service provider by selling assistance plans and increasing customer loyalty.
Keywords
Predictive maintenance, lubricant analysis, contaminant level, agricultural equipment
