Weibull and lognormal Taguchi analysis using multiple linear regression

被引:20
|
作者
Pina-Monarrez, Manuel R. [1 ]
Ortiz-Yanez, Jesus F. [1 ]
机构
[1] Univ Autonoma Ciudad Juarez, Ind & Mfg Dept, Engn & Technol Inst, Cd Juarez 32310, Chih, Mexico
关键词
Taguchi method; Weibull analysis; Accelerated life testing analysis; Multiple linear regression; RELIABILITY;
D O I
10.1016/j.ress.2015.08.004
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The paper provides to reliability practitioners with a method (I) to estimate the robust Weibull family when the Taguchi method (TM) is applied, (2) to estimate the normal operational Weibull family in an accelerated life testing (ALT) analysis to give confidence to the extrapolation and (3) to perform the ANOVA analysis to both the robust and the normal operational Weibull family. On the other hand, because the Weibull distribution neither has the normal additive property nor has a direct relationship with the normal parameters (mu, sigma), in this paper, the issues of estimating a Weibull family by using a design of experiment (DOE) are first addressed by using an L-9 (3(4)) orthogonal array (OA) in both the TM and in the Weibull proportional hazard model approach (WPHM). Then, by using the Weibull/Gumbel and the lognormal/normal relationships and multiple linear regression, the direct relationships between the Weibull and the lifetime parameters are derived and used to formulate the proposed method. Moreover, since the derived direct relationships always hold, the method is generalized to the lognormal and ALT analysis. Finally, the method's efficiency is shown through its application to the used OA and to a set of ALT data. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:244 / 253
页数:10
相关论文
共 50 条
  • [31] Error analysis of dimensionless scaling experiments with multiple points using linear regression
    Guercan, Oe. D.
    Vermare, L.
    Hennequin, P.
    Bourdelle, C.
    NUCLEAR FUSION, 2010, 50 (02)
  • [32] Estimating harmonic impact of individual loads using multiple linear regression analysis
    Wang, Yang
    Mazin, Hooman E.
    Xu, Wilsun
    Huang, Biao
    INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS, 2016, 26 (04): : 809 - 824
  • [33] Analysis of thefts in Colombia during 2017 using multiple linear regression models and geographically weighted regression
    Lopez Herrera, Nelson Ricardo
    Aceros Bueno, Marlon Augusto
    Luzardo Briceno, Marianela
    REVISTA CRIMINALIDAD, 2019, 61 (03) : 141 - 163
  • [34] On estimating percentiles of the Weibull distribution by the linear regression method
    David Hudak
    Murat Tiryakioğlu
    Journal of Materials Science, 2009, 44 : 1959 - 1964
  • [35] On estimating percentiles of the Weibull distribution by the linear regression method
    Hudak, David
    Tiryakioglu, Murat
    JOURNAL OF MATERIALS SCIENCE, 2009, 44 (08) : 1959 - 1964
  • [36] Improved estimation of Weibull parameters with the linear regression method
    Wu, DF
    Lu, GZ
    Jiang, H
    Li, YD
    JOURNAL OF THE AMERICAN CERAMIC SOCIETY, 2004, 87 (09) : 1799 - 1802
  • [37] Unbiased estimates of the Weibull parameters by the linear regression method
    Murat Tiryakioğlu
    David Hudak
    Journal of Materials Science, 2008, 43 : 1914 - 1919
  • [38] Improved linear regression method for estimating Weibull parameters
    Saghafi, A.
    Mirhabibi, A. R.
    Yari, G. H.
    THEORETICAL AND APPLIED FRACTURE MECHANICS, 2009, 52 (03) : 180 - 182
  • [39] Diagnostic tools in generalized Weibull linear regression models
    Hernando Vanegas, Luis
    Marina Rondon, Luz
    Cordeiro, Gauss M.
    JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 2013, 83 (12) : 2315 - 2338
  • [40] Unbiased estimates of the Weibull parameters by the linear regression method
    Tiryakioglu, Murat
    Hudak, David
    JOURNAL OF MATERIALS SCIENCE, 2008, 43 (06) : 1914 - 1919