Browsing by Author "Bochio, Gustavo"

Now showing 1 - 2 of 2
  • No Thumbnail Available
    Item
    Improved objective Bayesian estimator for a PLP model hierarchically represented subject to competing risks under minimal repair regime
    (2021) Louzada, Francisco; Cuminato, Jose A.; Rodriguez, Oscar M. H.; Tomazella, Vera L. D.; Ferreira, Paulo H.; Ramos, Pedro L.; Milani, Eder A.; Bochio, Gustavo; Perissini, Ivan C.; Gonzatto Junior, Oilson A.; Mota, Alex L.; Alegria, Luis F. A.; Colombo, Danilo; Perondi, Eduardo A.; Wentz, Andre V.; Junior, Anselmo L. Silva; Barone, Dante A. C.; Santos, Hugo F. L.; Magalhaes, Marcus V. C.
    In this paper, we propose a hierarchical statistical model for a single repairable system subject to several failure modes (competing risks). The paper describes how complex engineered systems may be modelled hierarchically by use of Bayesian methods. It is also assumed that repairs are minimal and each failure mode has a power-law intensity. Our proposed model generalizes another one already presented in the literature and continues the study initiated by us in another published paper. Some properties of the new model are discussed. We conduct statistical inference under an objective Bayesian framework. A simulation study is carried out to investigate the efficiency of the proposed methods. Finally, our methodology is illustrated by two practical situations currently addressed in a project under development arising from a partnership between Petrobras and six research institutes.
  • No Thumbnail Available
    Item
    Reliability assessment of repairable systems with series-parallel structure subjected to hierarchical competing risks under minimal repair regime
    (2022) Louzada, Francisco; Tomazella, Vera L. D.; Gonzatto, Oilson A.; Bochio, Gustavo; Milani, Eder A.; Ferreira, Paulo H.; Ramos, Pedro L.
    In this paper, we seek to propose a model that allows us to evaluate the failure times of a single repairable system represented hierarchically, exposed to competing risks and under a minimal repair framework. Our study can be regarded as an extension of the research presented in Louzada et al. (2019), which comprises the representation of complex systems through a hierarchical structure in series and/or in parallel. For this, we deduce the general form of the model, as well as the likelihood function associated with it, to obtain reliable estimates for the parameters that index the model. In addition, we display the mechanism for generating random numbers based on the presented structure, which enables obtaining point and interval estimates (via parametric bootstrap) in a more convenient way for reliability curves at any level of the system hierarchy. We conduct an extensive Monte Carlo simulation study to evaluate the performance of the proposed maximum likelihood estimators and confidence intervals for the model parameters. Finally, we illustrate the applicability of our model and methods with applications that deal with the reliability modeling of a robotic unit still under development, resulting from a project carried out in partnership between Petrobras and other Brazilian research centers.