Machine Reliability Optimization by Genetic Algorithm Approach

1
Ngnassi Djami Aslain Brisco
Ngnassi Djami Aslain Brisco Dr
2
Nzie Wolfgang
Nzie Wolfgang
3
Doka Yamigno Serge
Doka Yamigno Serge
1 University of Ngaoundere

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The objective of our study was to evaluate, in a population of Togolese People Living With HIV(PLWHIV), the agreement between three scores derived from the general population namely the Framingham score, the Systematic Coronary Risk Evaluation (SCORE), the evaluation of the cardiovascular risk (CVR) according to the World Health Organization.
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To define the reliability network of a system (machine), we start with a set of components arranged in an appropriate topology (series, parallel, or parallel-series), choose the best terms of the ratio performance / cost, and gather by links with the aim to combine them. This process requires a long time and effort, given the very large number of possible combinations, which becomes tedious for the analyst. For this reason, it is essential to use an appropriate optimization approach when designing any product. However, before trying to optimize, it is necessary to have a reliability assessment method. The objective of this paper is to display a meta-heuristic method, which is sustained on the genetic algorithm (GA) to improve the machines reliability. To achieve this objective, a methodology that consists of presenting the functionalities of genetic algorithms is developed. The result achieved is the proposal of a reliability network for the optimal solution.

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10 Cites in Articles

References

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

Ngnassi Djami Aslain Brisco. 2020. \u201cMachine Reliability Optimization by Genetic Algorithm Approach\u201d. Global Journal of Research in Engineering - A : Mechanical & Mechanics GJRE-A Volume 20 (GJRE Volume 20 Issue A2): .

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Journal Specifications

Crossref Journal DOI 10.17406/gjre

Print ISSN 0975-5861

e-ISSN 2249-4596

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GJRE-A Classification: FOR Code: 091399
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v1.2

Issue date

September 24, 2020

Language

English

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Machine Reliability Optimization by Genetic Algorithm Approach

Ngnassi Djami Aslain Brisco
Ngnassi Djami Aslain Brisco University of Ngaoundere
Nzie Wolfgang
Nzie Wolfgang
Doka Yamigno Serge
Doka Yamigno Serge

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