Optimizing Parallel-Series Configurations for Reliability: Enhancing Integrated Redundancy.

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Bibliographic Details
Title:	Optimizing Parallel-Series Configurations for Reliability: Enhancing Integrated Redundancy.
Authors:	Akiri, Sridhar¹ sakiri@gitam.edu, Kapu, Bhavani² bkapu@gitam.in, Bushan Rao, Peddi Phani³ ppeddi@gitam.edu, Saripalli, Arun Kumar⁴ asaripal@gitam.in, Chesneau, Christophe⁵ christophe.chesneau@gmail.com
Source:	IAENG International Journal of Applied Mathematics. Oct2025, Vol. 55 Issue 10, p3104-3111. 8p.
Subjects:	Engineering reliability theory, Redundancy in engineering, Engineering systems, Newton-Raphson method, Constraint programming, Lagrange multiplier, Mathematical optimization
Abstract:	In reliability theory, technical systems are often modeled using Series-Parallel configurations, which provide a structured framework to analyze the relationship between the lifetimes of individual components and the overall system reliability. These configurations build upon the foundational concept of Parallel-Series systems and are widely used in system design and optimization. Traditionally, system optimization focuses on constraints such as cost. However, additional factors like weight, volume, size, and space also play critical roles, particularly in applications such as AC motor control units. This paper investigates the impact of multiple constraints on optimizing system reliability. We explore an Integrated Redundant Reliability Parallel-Series configuration system, specifically designed to address these multidimensional constraints. The model is developed and solved using the Lagrangean multiplier method (LMM), providing real-valued solutions for critical parameters, including the number of components, component reliability, stage reliability, and overall system reliability. To ensure practical applicability, integer solutions are derived by employing the Newton- Raphson method during the analytical process. This comprehensive approach facilitates a deeper understanding of how multiple constraints influence system reliability and offers valuable insights for optimizing complex technical systems. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
Abstract:	In reliability theory, technical systems are often modeled using Series-Parallel configurations, which provide a structured framework to analyze the relationship between the lifetimes of individual components and the overall system reliability. These configurations build upon the foundational concept of Parallel-Series systems and are widely used in system design and optimization. Traditionally, system optimization focuses on constraints such as cost. However, additional factors like weight, volume, size, and space also play critical roles, particularly in applications such as AC motor control units. This paper investigates the impact of multiple constraints on optimizing system reliability. We explore an Integrated Redundant Reliability Parallel-Series configuration system, specifically designed to address these multidimensional constraints. The model is developed and solved using the Lagrangean multiplier method (LMM), providing real-valued solutions for critical parameters, including the number of components, component reliability, stage reliability, and overall system reliability. To ensure practical applicability, integer solutions are derived by employing the Newton- Raphson method during the analytical process. This comprehensive approach facilitates a deeper understanding of how multiple constraints influence system reliability and offers valuable insights for optimizing complex technical systems. [ABSTRACT FROM AUTHOR]
ISSN:	19929978