A bivariate fatigue-life regression model and its application to fracture of metallic tools

Helton Saulo, Jeremias Leão, VICTOR ELISEO LEIVA SANCHEZ, Roberto Vila, Vera Tomazella

Research output: Contribution to journalArticlepeer-review

Abstract

The Birnbaum-Saunders distribution has been widely used to model reliability and fatigue data. In this paper, we propose a regression of generalized linear models type based on a new bivariate Birnbaum-Saunders distribution. This is parameterized in terms of its means and allows data to be described in their original scale. We estimate the model parameters and carry out inference with the maximum likelihood method. A case study with realworld reliability data is conducted for motivating our investigation, illustrating the potential applications of the proposed results. We obtain a predictive model which can be a useful addition to the tool-kit of diverse practitioners, reliability engineers, applied statisticians, and data scientists.

Original languageEnglish
Pages (from-to)119-137
Number of pages19
JournalBrazilian Journal of Probability and Statistics
Volume35
Issue number1
DOIs
StatePublished - 2021
Externally publishedYes

Keywords

  • Bivariate birnbaum-saunders distribution
  • Fatigue data
  • Maximum likelihood method
  • Predictive models
  • R software

Fingerprint

Dive into the research topics of 'A bivariate fatigue-life regression model and its application to fracture of metallic tools'. Together they form a unique fingerprint.

Cite this