Reliability Advancement and Availability Improvement 
of Industrial Systems using RPGT and              
Metaheuristic Algorithms

Savita Garg; Rachna Aggarwal; Shilpa Rani; Neetu Rani; Diksha Mangla

doi:https://doi.org/10.14445/22315373/IJMTT-V71I11P101

International Journal of Mathematics Trends and Technology

Research Article | Open Access | Download PDF

Volume 71 | Issue 11 | Year 2025 | Article Id. IJMTT-V71I11P101 | DOI : https://doi.org/10.14445/22315373/IJMTT-V71I11P101

Reliability Advancement and Availability Improvement of Industrial Systems using RPGT and Metaheuristic Algorithms

Savita Garg, Rachna Aggarwal, Shilpa Rani, Neetu Rani, Diksha Mangla

Received	Revised	Accepted	Published
04 Sep 2025	18 Oct 2025	03 Nov 2025	17 Nov 2025

Citation :

Savita Garg, Rachna Aggarwal, Shilpa Rani, Neetu Rani, Diksha Mangla, "Reliability Advancement and Availability Improvement of Industrial Systems using RPGT and Metaheuristic Algorithms," International Journal of Mathematics Trends and Technology (IJMTT), vol. 71, no. 11, pp. 1-6, 2025. Crossref, https://doi.org/10.14445/22315373/IJMTT-V71I11P101

Abstract

This paper investigates the optimization of reliability and availability using the Regenerative Point Graphical Technique (RPGT). The study mainly focuses on system performance by systematically analyzing failure and repair rates through nature-inspired algorithms using Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Cuckoo Search Algorithm (CSA). A Markovian state model is developed to represent transitions between operational and failed states to compute reliability metrics such as Mean Time to System Failure (MTSF) and the system’s availability. Mean sojourn times and transition probabilities are derived to solve state distributions. The methodology set a dataset comprising parameters such as workload, failure rate, and repair rate. Sensor index, which collectively determines maintenance priority, enables predictive maintenance strategies. The optimization framework employing GA, PSO, and CSA can effectively optimize failure and repair parameters, improving system reliability and operational continuity. Comparative analysis highlights the efficiency and behavior of each algorithm, as well as the trade-offs between exploration and exploitation in the optimization process.

Keywords

Availability Analysis, Cuckoo Search Algorithm, Genetic Algorithm, Particle Swarm Optimization, System performance optimization.

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