Reliability-centered maintenance: analyzing failure in harvest sugarcane machine using some generalizations of the Weibull distribution

TL;DR

This paper evaluates five generalized Weibull distributions to model failure times of sugarcane harvester components, aiming to optimize maintenance scheduling and reduce costly machine downtimes.

Contribution

It introduces the application of generalized Weibull models for component lifetime analysis and proposes a predictive maintenance schedule for harvesters.

Findings

Best-fit distribution identified for each component

Enhanced maintenance scheduling reduces downtime

Improved reliability predictions for harvesters

Abstract

In this study we considered five generalizations of the standard Weibull distribution to describe the lifetime of two important components of harvest sugarcane machines. The harvesters considered in the analysis does the harvest of an average of 20 tons of sugarcane per hour and their malfunction may lead to major losses, therefore, an effective maintenance approach is of main interesting for cost savings. For the considered distributions, the mathematical background is presented. Maximum likelihood is used for parameter estimation. Further, different discrimination procedures were used to obtain the best fit for each component. At the end, we propose a maintenance scheduling for the components of the harvesters using predictive analysis.