Testing of Grouped Product for the Weibull Distribution Using Neutrosophic Statistics
Parts manufacturers use sudden death testing to reduce the testing time of experiments. The sudden death testing plan in the literature can only be applied when all observations of failure time/parameters are crisp. In practice however, it is noted that not all measurements of continuous variables a...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2018-09-01
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| Series: | Symmetry |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2073-8994/10/9/403 |
| _version_ | 1798039669444706304 |
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| author | Muhammad Aslam Osama H. Arif |
| author_facet | Muhammad Aslam Osama H. Arif |
| author_sort | Muhammad Aslam |
| collection | DOAJ |
| description | Parts manufacturers use sudden death testing to reduce the testing time of experiments. The sudden death testing plan in the literature can only be applied when all observations of failure time/parameters are crisp. In practice however, it is noted that not all measurements of continuous variables are precise. Therefore, the existing sudden death test plan can be applied if failure data/or parameters are imprecise, incomplete, and fuzzy. The classical statistics have the special case of neutrosophic statistics when there are no fuzzy observations/parameters. The neutrosophic fuzzy statistics can be applied for the testing of manufacturing parts when observations are imprecise, incomplete and fuzzy. In this paper, we will design an original neutrosophic fuzzy sudden death testing plan for the inspection/testing of the electronic product or parts manufacturing. We will assume that the lifetime of the product follows the neutrosophic fuzzy Weibull distribution. The neutrosophic fuzzy operating function will be given and used to determine the neutrosophic fuzzy plan parameters through a neutrosophic fuzzy optimization problem. The results of the proposed neutrosophic fuzzy death testing plan will be implemented with the aid of an example. |
| first_indexed | 2024-04-11T21:57:02Z |
| format | Article |
| id | doaj.art-b57be5a7dc6f495f93ad6ff96eeca78a |
| institution | Directory Open Access Journal |
| issn | 2073-8994 |
| language | English |
| last_indexed | 2024-04-11T21:57:02Z |
| publishDate | 2018-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Symmetry |
| spelling | doaj.art-b57be5a7dc6f495f93ad6ff96eeca78a2022-12-22T04:01:04ZengMDPI AGSymmetry2073-89942018-09-0110940310.3390/sym10090403sym10090403Testing of Grouped Product for the Weibull Distribution Using Neutrosophic StatisticsMuhammad Aslam0Osama H. Arif1Department of Statistics, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi ArabiaDepartment of Statistics, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi ArabiaParts manufacturers use sudden death testing to reduce the testing time of experiments. The sudden death testing plan in the literature can only be applied when all observations of failure time/parameters are crisp. In practice however, it is noted that not all measurements of continuous variables are precise. Therefore, the existing sudden death test plan can be applied if failure data/or parameters are imprecise, incomplete, and fuzzy. The classical statistics have the special case of neutrosophic statistics when there are no fuzzy observations/parameters. The neutrosophic fuzzy statistics can be applied for the testing of manufacturing parts when observations are imprecise, incomplete and fuzzy. In this paper, we will design an original neutrosophic fuzzy sudden death testing plan for the inspection/testing of the electronic product or parts manufacturing. We will assume that the lifetime of the product follows the neutrosophic fuzzy Weibull distribution. The neutrosophic fuzzy operating function will be given and used to determine the neutrosophic fuzzy plan parameters through a neutrosophic fuzzy optimization problem. The results of the proposed neutrosophic fuzzy death testing plan will be implemented with the aid of an example.http://www.mdpi.com/2073-8994/10/9/403neutrosophic fuzzy statisticsfuzzy approachneutrosophic fuzzy plan parametersfuzzy optimization problemrisks |
| spellingShingle | Muhammad Aslam Osama H. Arif Testing of Grouped Product for the Weibull Distribution Using Neutrosophic Statistics Symmetry neutrosophic fuzzy statistics fuzzy approach neutrosophic fuzzy plan parameters fuzzy optimization problem risks |
| title | Testing of Grouped Product for the Weibull Distribution Using Neutrosophic Statistics |
| title_full | Testing of Grouped Product for the Weibull Distribution Using Neutrosophic Statistics |
| title_fullStr | Testing of Grouped Product for the Weibull Distribution Using Neutrosophic Statistics |
| title_full_unstemmed | Testing of Grouped Product for the Weibull Distribution Using Neutrosophic Statistics |
| title_short | Testing of Grouped Product for the Weibull Distribution Using Neutrosophic Statistics |
| title_sort | testing of grouped product for the weibull distribution using neutrosophic statistics |
| topic | neutrosophic fuzzy statistics fuzzy approach neutrosophic fuzzy plan parameters fuzzy optimization problem risks |
| url | http://www.mdpi.com/2073-8994/10/9/403 |
| work_keys_str_mv | AT muhammadaslam testingofgroupedproductfortheweibulldistributionusingneutrosophicstatistics AT osamaharif testingofgroupedproductfortheweibulldistributionusingneutrosophicstatistics |