LAPSE:2023.1609
Published Article
LAPSE:2023.1609
Reliability Modelling through the Three-Parametric Weibull Model Based on Microsoft Excel Facilities
February 21, 2023
Abstract
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.
Keywords
BETA.INV function, estimator, linear regression, location parameter, probability, Weibull model
Suggested Citation
Titu AM, Boroiu AA, Boroiu A, Dragomir M, Pop AB, Titu S. Reliability Modelling through the Three-Parametric Weibull Model Based on Microsoft Excel Facilities. (2023). LAPSE:2023.1609
Author Affiliations
Titu AM: Department of Industrial Engineering and Management, Faculty of Engineering, “Lucian Blaga” University of Sibiu, 10 Victoriei Street, 550024 Sibiu, Romania [ORCID]
Boroiu AA: Department of Road Vehicles and Transports, Faculty of Mecanics and Technology, University of Pitesti, 1 Targul din Vale Street, 110040 Pitesti, Romania
Boroiu A: Department of Road Vehicles and Transports, Faculty of Mecanics and Technology, University of Pitesti, 1 Targul din Vale Street, 110040 Pitesti, Romania [ORCID]
Dragomir M: Department of Design Engineering and Robotics, Faculty of Industrial Engineering, Robotics and Production Management, Technical University of Cluj-Napoca, 103−105 Muncii Blvd., 400641 Cluj-Napoca, Romania [ORCID]
Pop AB: Department of Engineering and Technology Management, Faculty of Engineering, Technical University of Cluj-Napoca, Northern University Centre of Baia Mare, 62A Victor Babes Street, 430083 Baia Mare, Romania [ORCID]
Titu S: Faculty of Medicine, 8 Victor Babeș Street, “Iuliu Hatieganu” University of Medicine and Pharmacy Cluj Napoca, 400000 Cluj-Napoca, Romania; Department of Surgical Oncology, The Oncology Institute “Prof. Dr. Ion Chiricuta” Cluj Napoca, 34−36 Rep [ORCID]
Journal Name
Processes
Volume
10
Issue
8
First Page
1585
Year
2022
Publication Date
2022-08-12
ISSN
2227-9717
Version Comments
Original Submission
Other Meta
PII: pr10081585, Publication Type: Journal Article
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LAPSE:2023.1609
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https://doi.org/10.3390/pr10081585
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Feb 21, 2023
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