Reliability Modelling through the Three-Parametric Weibull Model Based on Microsoft Excel Facilities

被引:1
|
作者
Titu, Aurel Mihail [1 ]
Boroiu, Andrei Alexandru [2 ]
Boroiu, Alexandru
Dragomir, Mihai [3 ]
Pop, Alina Bianca [4 ]
Titu, Stefan [5 ,6 ]
机构
[1] Lucian Blaga Univ Sibiu, Dept Ind Engn & Management, Fac Engn, 10 Victoriei St, Sibiu 550024, Romania
[2] Univ Pitesti, Fac Mecan & Technol, Dept Rd Vehicles & Transports, 1 Targul Din Vale St, Pitesti 110040, Romania
[3] Tech Univ Cluj Napoca, Fac Ind Engn Robot & Prod Management, Dept Design Engn & Robot, 103-105 Muncii Blvd, Cluj Napoca 400641, Romania
[4] Tech Univ Cluj Napoca, Northern Univ Ctr Baia Mare, Dept Engn & Technol Management, Fac Engn, 62A Victor Babes St, Baia Mare 430083, Romania
[5] Iuliu Hatieganu Univ Med & Pharm Cluj Napoca, Fac Med, 8 Victor Babes St, Cluj Napoca 400000, Romania
[6] Oncol Inst Prof Dr Ion Chiricuta Cluj Napoca, Dept Surg Oncol, 34-36 Republ St, Cluj Napoca 400015, Romania
关键词
Weibull model; estimator; BETA.INV function; location parameter; linear regression; probability; PARAMETERS;
D O I
10.3390/pr10081585
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
The paper aims to capitalize on the new features that are offered by the Microsoft Excel calculation program for reliability modeling, using the Median Ranks estimator that is calculated directly with the BETA.INV function, not estimated by various algebraic estimators, as is generally the case. Starting from this first step, a method of modeling reliability is elaborated through the three-parametric Weibull model that is based exclusively on this software, which is accessible to anyone and can be used even in the case of online learning, which is widespread in recent years due to the pandemic situation. The probability plotting method is applied, using the Median Ranks estimator that is calculated directly with the BETA.INV function for a probability equal to 0.5. A flowchart is made for the proposed method, which could be easily translated into a calculation program. By representing in logarithmic coordinates, we determined the Weibull models for different values that were initially adopted for the location parameter: using as a criterion the coefficient of determination that was obtained using the trendline function for the linear model, it was possible to identify, by successive tests, the optimal value of the location parameter-for which the three-parametric model has a good likelihood. By the proposed method, this value can be found following this iterative process. So, based on the current facilities of the Microsoft Excel program, a precise and easy-to-apply method has been achieved, through which an appropriate three-parametric Weibull model can be identified.
引用
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页数:13
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