A method for estimating the probability distribution of the lifetime for new technical equipment based on expert judgement

被引:15
作者
Andrzejczak, Karol [1 ]
Bukowski, Lech [2 ]
机构
[1] Poznan Univ Tech, Fac Control Robot & Elect Engn, Inst Math, Ul Piotrowo 3A, PL-60965 Poznan, Poland
[2] WSB Univ, Ul Zygmunta Cieplaka 1c, PL-41300 Dabrowa Gomicza, Poland
来源
EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY | 2021年 / 23卷 / 04期
关键词
uncertainty; expert elicitation of lifetime; quantile function; Weibull distribution; RELIABILITY; INTERVAL; FAILURE;
D O I
10.17531/ein.2021.4.18
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Managing the exploitation of technical equipment under conditions of uncertainty requires the use of probabilistic prediction models in the form of probability distributions of the lifetime of these objects. The parameters of these distributions are estimated with the use of statistical methods based on historical data about actual realizations of the lifetime of examined objects. However, when completely new solutions are introduced into service, such data are not available and the only possible method for the initial assessment of the expected lifetime of technical objects is expert methods. The aim of the study is to present a method for estimating the probability distribution of the lifetime for new technical facilities based on expert assessments of three parameters characterizing the expected lifetime of these objects. The method is based on a subjective Bayesian approach to the problem of randomness and integrated with models of classical probability theory. Due to its wide application in the field of maintenance of machinery and technical equipment, a Weibull model is proposed, and its possible practical applications are shown. A new method of expert elicitation of probabilities for any continuous random variable is developed. A general procedure for the application of this method is proposed and the individual steps of its implementation are discussed, as well as the mathematical models necessary for the estimation of the parameters of the probability distribution are presented. A practical example of the application of the developed method on specific numerical values is also presented.
引用
收藏
页码:757 / 769
页数:13
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