Statistical Fuzzy Reliability Assessment of a Blended System
Fuzzy sets have been proven to constitute an asset in the evolution of reliability theory in recent decades. Their contribution in addressing the possibility of errors, insufficiency of data, randomness, or fuzziness, either in the system or in the accumulation of any data for the respective system,...
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MDPI AG
2023-04-01
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| Series: | Axioms |
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| author | Aayushi Chachra Akshay Kumar Mangey Ram Ioannis S. Triantafyllou |
| author_facet | Aayushi Chachra Akshay Kumar Mangey Ram Ioannis S. Triantafyllou |
| author_sort | Aayushi Chachra |
| collection | DOAJ |
| description | Fuzzy sets have been proven to constitute an asset in the evolution of reliability theory in recent decades. Their contribution in addressing the possibility of errors, insufficiency of data, randomness, or fuzziness, either in the system or in the accumulation of any data for the respective system, which is overlooked in the traditional reliability assessment, seems to be quite crucial. The present work deals with the statistical fuzzy reliability evaluation of a blended system that comprises two subsystems. One system contains two components aligned in a parallel configuration, and the other is a 3-out-of-5 system. The reliability of this model is assessed using two approaches to intuitionistic fuzzy sets (IFS), namely, traditional IFS and interval-valued intuitionistic fuzzy sets (IVIFS). Three cases are considered in each approach, which are compared individually as well as with each other. It was established that the IVIFS yield better results than the IFS. The obtained results are displayed in both tabular and graphical forms for better assessment. |
| first_indexed | 2024-03-11T03:57:02Z |
| format | Article |
| id | doaj.art-bff243a018da422cbc0bb299aefbcd38 |
| institution | Directory Open Access Journal |
| issn | 2075-1680 |
| language | English |
| last_indexed | 2024-03-11T03:57:02Z |
| publishDate | 2023-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Axioms |
| spelling | doaj.art-bff243a018da422cbc0bb299aefbcd382023-11-18T00:27:00ZengMDPI AGAxioms2075-16802023-04-0112541910.3390/axioms12050419Statistical Fuzzy Reliability Assessment of a Blended SystemAayushi Chachra0Akshay Kumar1Mangey Ram2Ioannis S. Triantafyllou3Department of Mathematics, Graphic Era Deemed to be University, Dehradun 248002, IndiaDepartment of Mathematics, Graphic Era Hill University, Dehradun 248002, IndiaDepartment of Mathematics, Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun 248002, IndiaDepartment of Statistics & Insurance Science, University of Piraeus, 18534 Piraeus, GreeceFuzzy sets have been proven to constitute an asset in the evolution of reliability theory in recent decades. Their contribution in addressing the possibility of errors, insufficiency of data, randomness, or fuzziness, either in the system or in the accumulation of any data for the respective system, which is overlooked in the traditional reliability assessment, seems to be quite crucial. The present work deals with the statistical fuzzy reliability evaluation of a blended system that comprises two subsystems. One system contains two components aligned in a parallel configuration, and the other is a 3-out-of-5 system. The reliability of this model is assessed using two approaches to intuitionistic fuzzy sets (IFS), namely, traditional IFS and interval-valued intuitionistic fuzzy sets (IVIFS). Three cases are considered in each approach, which are compared individually as well as with each other. It was established that the IVIFS yield better results than the IFS. The obtained results are displayed in both tabular and graphical forms for better assessment.https://www.mdpi.com/2075-1680/12/5/419interval-valued intuitionistic fuzzy sets (IVIFS)intuitionistic fuzzy reliability (IFR)intuitionistic fuzzy sets (IFS)<i>k</i>-out-of-<i>n</i> systemstatistical fuzzy reliability |
| spellingShingle | Aayushi Chachra Akshay Kumar Mangey Ram Ioannis S. Triantafyllou Statistical Fuzzy Reliability Assessment of a Blended System Axioms interval-valued intuitionistic fuzzy sets (IVIFS) intuitionistic fuzzy reliability (IFR) intuitionistic fuzzy sets (IFS) <i>k</i>-out-of-<i>n</i> system statistical fuzzy reliability |
| title | Statistical Fuzzy Reliability Assessment of a Blended System |
| title_full | Statistical Fuzzy Reliability Assessment of a Blended System |
| title_fullStr | Statistical Fuzzy Reliability Assessment of a Blended System |
| title_full_unstemmed | Statistical Fuzzy Reliability Assessment of a Blended System |
| title_short | Statistical Fuzzy Reliability Assessment of a Blended System |
| title_sort | statistical fuzzy reliability assessment of a blended system |
| topic | interval-valued intuitionistic fuzzy sets (IVIFS) intuitionistic fuzzy reliability (IFR) intuitionistic fuzzy sets (IFS) <i>k</i>-out-of-<i>n</i> system statistical fuzzy reliability |
| url | https://www.mdpi.com/2075-1680/12/5/419 |
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