Parameter Estimation of the Weibull Distribution in Modeling the Reliability of Technical Objects

被引:0
|
作者
Frolov, M. [1 ]
Tanchenko, S. [1 ]
Ohluzdina, L. [1 ]
机构
[1] Natl Univ Zaporizhzhia Polytech, 64 Zhukovskogo St, UA-69063 Zaporizhzhia, Ukraine
来源
关键词
cutting tool life; least squared estimation; maximum likelihood estimation; confidence interval; variation coefficient; bias; empirical data;
D O I
10.21272/jes.2024.11(1).a1
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The article discusses one of the most widely used distribution laws for reliability analysis - Weibull distribution. It describes a wide range of processes for all stages of the life cycle of technical objects, including yield stress of steel distribution and failures in the reliability theory regarding the wide range of technical objects (e.g., metal cutting tools, bearings, compressors, and wheels). A significant number of works are devoted to evaluating distribution law parameters based on empirical data in search of the most precise one, ignoring the probabilistic character of the parameters themselves. Parameters may have a relatively wide confidence range, which can be considered the parameter estimation error compared to biases of parameters estimated by different methods. Moreover, many approaches should be used for certain selection volumes, including comprehensive calculating procedures. Instead, this paper suggested and statistically confirmed a universal simplified approach. It demands a minimal set of data and connects the shape and scale parameters of the Weibull distribution with the variation coefficient as one of the leading statistical characteristics. This approach does not demand variational sequence arrangement. Nevertheless, it is supposed to be quite efficient for the engineering practice of reliability analysis. The adequacy of the results was confirmed using generated selections analysis and experimental data on cutting tool reliability. Within the achieved results, it was also demonstrated that the variation coefficient reflects not only selection stability and variable volatility degree, which are its main aim, but the cause of failure as well.
引用
收藏
页码:A1 / A10
页数:10
相关论文
共 50 条
  • [1] A Parameter Estimation of Weibull Distribution for Reliability Assessment with Limited Failure Data
    Enkhmunkh, Nemekhbayar
    Kim, Gwang Won
    Hwang, Kab-Ju
    Hyun, Seung-Ho
    IFOST: 2007 INTERNATIONAL FORUM ON STRATEGIC TECHNOLOGY, 2007, : 39 - 42
  • [2] Reliability estimation and parameter estimation for inverse Weibull distribution under different loss functions
    Yilmaz, Asuman
    Kara, Mahmut
    KUWAIT JOURNAL OF SCIENCE, 2022, 49 (01)
  • [3] BAYES ESTIMATION OF THE PARAMETERS AND RELIABILITY FUNCTION OF THE 3-PARAMETER WEIBULL DISTRIBUTION
    SINHA, SK
    SLOAN, JA
    IEEE TRANSACTIONS ON RELIABILITY, 1988, 37 (04) : 364 - 369
  • [4] On best estimation for parameter weibull distribution
    Alkutubi, Hadeel Salim
    World Academy of Science, Engineering and Technology, 2011, 51 : 281 - 283
  • [5] A new approach for parameter estimation of finite Weibull mixture distributions for reliability modeling
    Elmahdy, Emad E.
    Aboutahoun, Abdallah W.
    APPLIED MATHEMATICAL MODELLING, 2013, 37 (04) : 1800 - 1810
  • [6] Reliability estimation for two-parameter Weibull distribution under block censoring
    Zhu, Tiefeng
    RELIABILITY ENGINEERING & SYSTEM SAFETY, 2020, 203 (203)
  • [7] Robust estimation of the three parameter Weibull distribution for addressing outliers in reliability analysis
    Safari, Muhammad Aslam Mohd
    Masseran, Nurulkamal
    Majid, Muhammad Hilmi Abdul
    Tajuddin, Razik Ridzuan Mohd
    SCIENTIFIC REPORTS, 2025, 15 (01):
  • [8] Parameter estimation of the Weibull probability distribution
    Pang, WK
    BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING, 2004, 735 : 549 - 554
  • [9] PARAMETER-ESTIMATION FOR WEIBULL DISTRIBUTION
    STONE, GC
    VANHEESWIJK, RG
    IEEE TRANSACTIONS ON ELECTRICAL INSULATION, 1977, 12 (04): : 253 - 261
  • [10] Estimation of the reliability parameter for three-parameter Weibull models
    Montoya, Jose A.
    Diaz-Frances, Eloisa
    Figueroa P, Gudelia
    APPLIED MATHEMATICAL MODELLING, 2019, 67 : 621 - 633