Bivariate degradation modelling with marginal heterogeneous stochastic processes

被引:14
作者
Alberto Rodriguez-Picon, Luis [1 ]
Hugo Flores-Ochoa, Victor [2 ]
Carlos Mendez-Gonzalez, Luis [1 ]
Arnoldo Rodriguez-Medina, Manuel [2 ]
机构
[1] Autonomous Univ Ciudad Juarez, Inst Engn & Technol, Dept Ind Engn & Mfg, Ciudad Juarez, Mexico
[2] Technol Inst Ciudad Juarez, Ciudad Juarez, Mexico
关键词
Degradation process; bivariate modelling; heterogeneous processes; stochastic process; copula function; 60Gxx; 62N05; 62Nxx; GEOMETRIC BROWNIAN-MOTION; INVERSE GAUSSIAN PROCESS; WIENER-PROCESSES; PRODUCTS;
D O I
10.1080/00949655.2017.1324858
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In this paper, we consider that the degradation of two performance characteristics of a product can be modelled by stochastic processes and jointly by copula functions, but different stochastic processes govern the behaviour of each performance characteristic (PC) degradation. Different heterogeneous and homogeneous models are presented considering copula functions and different combinations of the most used stochastic processes in degradation analysis as marginal distributions. This is an important aspect to consider because the behaviour of the degradation of each PC may be different in its nature. As the joint distributions of the proposed models result in complex distributions, the estimation of the parameters of interest is performed via MCMC. A simulation study is performed to compare heterogeneous and homogeneous models. In addition, the proposed models are implemented to crack propagation data of two terminals of an electronic device, and some insights are provided about the product reliability under heterogeneous models.
引用
收藏
页码:2207 / 2226
页数:20
相关论文
共 50 条
  • [31] Stochastic Modeling and Analysis of Multiple Nonlinear Accelerated Degradation Processes through Information Fusion
    Sun, Fuqiang
    Liu, Le
    Li, Xiaoyang
    Liao, Haitao
    SENSORS, 2016, 16 (08)
  • [32] Remaining Useful Life Prediction for Hybrid Stochastic Degradation Processes with Finite Time Delay
    Xi, Xiaopeng
    Chen, Maoyin
    Zhou, Donghua
    2020 EUROPEAN CONTROL CONFERENCE (ECC 2020), 2020, : 818 - 824
  • [33] Stochastic degradation models with several accelerating variables
    Park, Chanseok
    Padgett, William J.
    IEEE TRANSACTIONS ON RELIABILITY, 2006, 55 (02) : 379 - 390
  • [34] Uncertainty quantification for monotone stochastic degradation models
    Chen, Piao
    Ye, Zhi-Sheng
    JOURNAL OF QUALITY TECHNOLOGY, 2018, 50 (02) : 207 - 219
  • [35] Modelling Temperature Using CARMA Processes with Stochastic Speed of Mean Reversion for Temperature Insurance Pricing
    Darus, M.
    Taib, C. M. I. C.
    MALAYSIAN JOURNAL OF MATHEMATICAL SCIENCES, 2022, 16 (02): : 273 - 288
  • [36] Insights into the degradation mechanisms and pathways of cephalexin during homogeneous and heterogeneous photo-Fenton processes
    Gou, Yejing
    Peng, Lai
    Xu, Haixing
    Li, Shengjun
    Liu, Chang
    Wu, Xiaoyong
    Song, Shaoxian
    Yang, Chenguang
    Song, Kang
    Xu, Yifeng
    CHEMOSPHERE, 2021, 285
  • [37] Wavelets and stochastic processes
    Antoniou, I
    Gustafson, K
    MATHEMATICS AND COMPUTERS IN SIMULATION, 1999, 49 (1-2) : 81 - 104
  • [38] Student-t Processes for Degradation Analysis
    Peng, Chien-Yu
    Cheng, Ya-Shan
    TECHNOMETRICS, 2020, 62 (02) : 223 - 235
  • [39] On multivariate copula modeling of dependent degradation processes
    Fang, Guanqi
    Pan, Rong
    COMPUTERS & INDUSTRIAL ENGINEERING, 2021, 159
  • [40] Exponential Dispersion accelerated degradation modelling and reliability assessment considering initial value and processes heterogeneity
    Tian, Runcao
    Zhang, Fan
    Du, Hongguang
    Wang, Peng
    EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY, 2024, 26 (04):