System Reliability-Redundancy optimization with High-Level of subsystems

Mohamed Arezki Mellal; Sameer Al-Dahidi; Rajkumar Bhimgonda Patil; Basavraj S. Kothavale; Rajendra S. Powar

doi:10.1016/j.matpr.2022.11.088

System Reliability-Redundancy optimization with High-Level of subsystems

Mohamed Arezki Mellal
, Sameer Al-Dahidi
, Rajkumar Bhimgonda Patil^*
, Basavraj S. Kothavale
, Rajendra S. Powar

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

High systems’ reliability is crucial in competitive industrial plants. System Reliability-Redundancy Allocation (RRA) is an essential design consideration for maximizing the overall systems’ reliability under various systems’ constraints. This paper addresses the system RRAP problem by investigating two effective nature-inspired optimization techniques, namely Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO), implemented with penalty functions. Their capability in solving the RRA problem is evaluated regarding a system consisting of fifteen subsystems connected in series. Results show that the PSO is a better approach to solving this problem than the GWO.

Original language	English
Pages (from-to)	627-630
Number of pages	4
Journal	Materials Today: Proceedings
Volume	77
DOIs	https://doi.org/10.1016/j.matpr.2022.11.088
State	Published - Jan 2023
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2022

Keywords

Allocation
Grey wolf optimizer
Optimization
Particle swarm optimization
Redundancy allocation
Reliability

ASJC Scopus subject areas

General Materials Science

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10.1016/j.matpr.2022.11.088

Cite this

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title = "System Reliability-Redundancy optimization with High-Level of subsystems",

abstract = "High systems{\textquoteright} reliability is crucial in competitive industrial plants. System Reliability-Redundancy Allocation (RRA) is an essential design consideration for maximizing the overall systems{\textquoteright} reliability under various systems{\textquoteright} constraints. This paper addresses the system RRAP problem by investigating two effective nature-inspired optimization techniques, namely Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO), implemented with penalty functions. Their capability in solving the RRA problem is evaluated regarding a system consisting of fifteen subsystems connected in series. Results show that the PSO is a better approach to solving this problem than the GWO.",

keywords = "Allocation, Grey wolf optimizer, Optimization, Particle swarm optimization, Redundancy allocation, Reliability",

author = "Mellal, \{Mohamed Arezki\} and Sameer Al-Dahidi and \{Bhimgonda Patil\}, Rajkumar and Kothavale, \{Basavraj S.\} and Powar, \{Rajendra S.\}",

note = "Publisher Copyright: {\textcopyright} 2022",

year = "2023",

month = jan,

doi = "10.1016/j.matpr.2022.11.088",

language = "English",

volume = "77",

pages = "627--630",

journal = "Materials Today: Proceedings",

issn = "2214-7853",

publisher = "Elsevier Ltd.",

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AU - Mellal, Mohamed Arezki

AU - Al-Dahidi, Sameer

AU - Bhimgonda Patil, Rajkumar

AU - Kothavale, Basavraj S.

AU - Powar, Rajendra S.

PY - 2023/1

Y1 - 2023/1

N2 - High systems’ reliability is crucial in competitive industrial plants. System Reliability-Redundancy Allocation (RRA) is an essential design consideration for maximizing the overall systems’ reliability under various systems’ constraints. This paper addresses the system RRAP problem by investigating two effective nature-inspired optimization techniques, namely Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO), implemented with penalty functions. Their capability in solving the RRA problem is evaluated regarding a system consisting of fifteen subsystems connected in series. Results show that the PSO is a better approach to solving this problem than the GWO.

AB - High systems’ reliability is crucial in competitive industrial plants. System Reliability-Redundancy Allocation (RRA) is an essential design consideration for maximizing the overall systems’ reliability under various systems’ constraints. This paper addresses the system RRAP problem by investigating two effective nature-inspired optimization techniques, namely Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO), implemented with penalty functions. Their capability in solving the RRA problem is evaluated regarding a system consisting of fifteen subsystems connected in series. Results show that the PSO is a better approach to solving this problem than the GWO.

KW - Allocation

KW - Grey wolf optimizer

KW - Optimization

KW - Particle swarm optimization

KW - Redundancy allocation

KW - Reliability

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DO - 10.1016/j.matpr.2022.11.088

M3 - Article

AN - SCOPUS:85142680400

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VL - 77

SP - 627

EP - 630

JO - Materials Today: Proceedings

JF - Materials Today: Proceedings

ER -

System Reliability-Redundancy optimization with High-Level of subsystems

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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