Availability Evaluation and Design Optimization of Multi-State k-out-of-n: G Systems With Random Performance Requirements
As an important aspect of reliability theory, availability has now been considered a very meaningful design criterion of repairable system. This paper investigates the availability evaluation and design optimization of the multi-state k-out-of-n: G systems considering random weight threshold. The sy...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10295493/ |
| _version_ | 1797640370426740736 |
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| author | Jing Li Li Xue Guodong Wang Haofei Zhou |
| author_facet | Jing Li Li Xue Guodong Wang Haofei Zhou |
| author_sort | Jing Li |
| collection | DOAJ |
| description | As an important aspect of reliability theory, availability has now been considered a very meaningful design criterion of repairable system. This paper investigates the availability evaluation and design optimization of the multi-state k-out-of-n: G systems considering random weight threshold. The system availability is evaluated by extending the recursive algorithm (RA) and universal generating function (UGF) technique. Based on the traditional recursive algorithm, the total probability theorem is used to solve the discrete random weight threshold. Another better UGF method combines a new stochastic joint operator, which is suitable for both continuous and discrete random weight thresholds. Furthermore, we constructed two system design optimization models under availability or cost constraint respectively, and genetic algorithm (GA) programming can be applied to obtain the optimal state probability distribution and weight distribution of multi-state components of the suggested system. Finally, through numerical examples, the flexibility and effectiveness of the proposed methods for design optimization are demonstrated. In addition, two evaluation methods are compared to show that the customized UGF method features higher generality than RA in the case of continuous stochastic weight threshold, and higher operational efficiency in the case of increasing component quantity and state. The results can be helpful for engineers to optimize the design of complex systems. |
| first_indexed | 2024-03-11T13:30:52Z |
| format | Article |
| id | doaj.art-c8ab2a9a64664c989ad3e4c26ac49e16 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-11T13:30:52Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-c8ab2a9a64664c989ad3e4c26ac49e162023-11-02T23:01:37ZengIEEEIEEE Access2169-35362023-01-011111910611911710.1109/ACCESS.2023.332743110295493Availability Evaluation and Design Optimization of Multi-State k-out-of-n: G Systems With Random Performance RequirementsJing Li0https://orcid.org/0000-0002-4242-4181Li Xue1https://orcid.org/0000-0002-6963-7064Guodong Wang2Haofei Zhou3School of Management Engineering, Zhengzhou University of Aeronautics, Zhengzhou, ChinaSchool of Management Engineering, Zhengzhou University of Aeronautics, Zhengzhou, ChinaSchool of Management Engineering, Zhengzhou University of Aeronautics, Zhengzhou, ChinaSchool of Management Engineering, Zhengzhou University of Aeronautics, Zhengzhou, ChinaAs an important aspect of reliability theory, availability has now been considered a very meaningful design criterion of repairable system. This paper investigates the availability evaluation and design optimization of the multi-state k-out-of-n: G systems considering random weight threshold. The system availability is evaluated by extending the recursive algorithm (RA) and universal generating function (UGF) technique. Based on the traditional recursive algorithm, the total probability theorem is used to solve the discrete random weight threshold. Another better UGF method combines a new stochastic joint operator, which is suitable for both continuous and discrete random weight thresholds. Furthermore, we constructed two system design optimization models under availability or cost constraint respectively, and genetic algorithm (GA) programming can be applied to obtain the optimal state probability distribution and weight distribution of multi-state components of the suggested system. Finally, through numerical examples, the flexibility and effectiveness of the proposed methods for design optimization are demonstrated. In addition, two evaluation methods are compared to show that the customized UGF method features higher generality than RA in the case of continuous stochastic weight threshold, and higher operational efficiency in the case of increasing component quantity and state. The results can be helpful for engineers to optimize the design of complex systems.https://ieeexplore.ieee.org/document/10295493/Multi-state k-out-of-n: G systemavailabilitydesign optimizationuniversal generating functionrecursive algorithm |
| spellingShingle | Jing Li Li Xue Guodong Wang Haofei Zhou Availability Evaluation and Design Optimization of Multi-State k-out-of-n: G Systems With Random Performance Requirements IEEE Access Multi-state k-out-of-n: G system availability design optimization universal generating function recursive algorithm |
| title | Availability Evaluation and Design Optimization of Multi-State k-out-of-n: G Systems With Random Performance Requirements |
| title_full | Availability Evaluation and Design Optimization of Multi-State k-out-of-n: G Systems With Random Performance Requirements |
| title_fullStr | Availability Evaluation and Design Optimization of Multi-State k-out-of-n: G Systems With Random Performance Requirements |
| title_full_unstemmed | Availability Evaluation and Design Optimization of Multi-State k-out-of-n: G Systems With Random Performance Requirements |
| title_short | Availability Evaluation and Design Optimization of Multi-State k-out-of-n: G Systems With Random Performance Requirements |
| title_sort | availability evaluation and design optimization of multi state k out of n g systems with random performance requirements |
| topic | Multi-state k-out-of-n: G system availability design optimization universal generating function recursive algorithm |
| url | https://ieeexplore.ieee.org/document/10295493/ |
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