Stochastic Analysis of Redundant RF Amplifiers with Priority Repair and Data-Driven Parameters
DOI:
https://doi.org/10.13052/jrss0974-8024.19213Keywords:
Parallel systems, RF power amplifier module, RF backup amplifier module, reliability analysis, regenerative point technique, semi-Markov processAbstract
RF amplifier modules provide fundamental and indispensable functionality across diverse domains such as aerospace, defence, medical imaging, industrial automation, and scientific research by ensuring reliable operation and robust signal transmission. Their criticality is amplified in high-end applications for example cellular base stations, radar, and real-time networks dependent. The current work develops a stochastic model for the reliability analysis of a parallel redundant system comprising a primary and a backup RF Power Amplifier Module. Utilizing the semi-Markov Regenerative Point Technique (SMRPT), we compute key metrics like Mean Time to System Failure (MTSF), availability and system’s profit. The system is initially fully operational and fails only when both units fail. A dedicated server performs immediate, flawless repairs upon failure, prioritizing the primary module. The study assumes constant failure rates and exponentially distributed repair times. To estimate the failure and repair rates from empirical data, a linear regression technique which is one of the fundamental supervised learning methods in AI and machine learning, is utilized. The observed repair and failure times are considered as dependent variables and the rates are approximated as the inverse of the mean observed times.
Downloads
References
A. Al-Ammouri, V. Kharuta, A. Klochan, O. Shkurko, and H. Al-Ammori, Enhancing the Reliability of Information in Positioning Systems On Road Transport By Using Parallel Information Redundancy. Eastern-European Journal of Enterprise Technologies, 2024. DOI: 10.15587/1729-4061.2024.304129.
A. K. Lado, and V. V. Singh. Cost assessment of complex repairable system consisting two subsystems in series configuration. International Journal of Quality and Reliability Management, 36(10): 1683–1699, 2019. DOI: 10.1108/IJQRM-12-2018-0322.
A. Kumar. Parametric Optimization of Repairable Systems in IoT: Addressing Detection Delays, Imperfect Coverage, and Fuzzy Parameters, Life Cycle Reliability and Safety Engineering, 14: 329–340, DOI: 10.1007/s41872-025-00298-6.
A. Kumar and M. Ram. Process modeling for decomposition unit of a UFP for reliability indices subject to fail-back mode and degradation, Journal of Quality in Maintenance Engineering, 29(3): 606–621, 2023, DOI: 10.1108/JQME-01-2022-0008.
A. Kumar, D. Goyal, D. Sinwar, M. Saini. Stochastic modeling and performance optimization of sludge digestion processing system using genetic algorithm, International Journal of Information Technology, 14: 3391–3400, 2022. DOI: 10.1007/s41870-022-00908-x.
A. Munjal, and S. B. Singh. Reliability analysis of a complex repairable system composed of a 2-out-of-3: G subsystem and a series subsystem connected in parallel. Journal of Reliability and Statistical Studies, 7: 19–39, 2014. DOI: 10.1007/s41872-019-00103-1.
A. R. Kommula, and A. K. Mishra. Stochastic Reliability Modelling of Three-Component Systems under Simultaneous Failure Shocks. East Journal of Applied Science, 1–10, 2025. DOI: 10.63496/ejas.Vol1.Iss2.86.
B. Singh, V. Saxena, R. Gupta, and S. Rathi. A Bayesian analysis of a geometric distribution model of two identical unit warm standby system with regular and expert repair facility. Reliability Assessment and Optimization of Complex Systems, 309–341, 2025. DOI: 10.1016/B978-0-443-29112-8.00018-9.
C. Shekhar, S. Varshney, and A. Kumar. Standbys provisioning machine repair problem with unreliable service and vacation interruption, The Handbook of Reliability, Maintenance, and System Safety through Mathematical Modeling, A. Kumar and M. Ram, Eds. Elsevier, 101–137, 2021, DOI: 10.1016/B978-0-12-819582-6.00006-X.
C. Wang, S. Luo, G. Chen, Z. Wu, W. Rong, and Q. Guan. Phase combination for reliability analysis of dynamic k-out-of-n Phase-AND mission systems. Reliability Engineering & System Safety, 257, 2025. DOI: 10.1016/j.ress.2025.110817.
D. Kumar, D. Jana, S. Gupta, and P. Yadav. Bayesian Network Approach for Dragline Reliability Analysis: a Case Study. Mining Metallurgy & Exploration, 40(4), 2023. DOI: 10.1007/s42461-023-00729-x.
D. Kumar, S. Gupta, and P. Yadav. Reliability, Availability, Maintainability of a Dragline, Journals of Mines, Metals and Fuels, 2020. DOI: 10.18311/jmmf/2020/26922.
D. Mitra, S. B. Hamidi, P. Roy, C. Biswas, A. Biswas, and D. Dawn. Radio frequency reliability studies of CMOS RF integrated circuits for ultra-thin flexible packages, Electronic Letters, 56: 264–312, 2020. DOI: 10.1049/el.2019.3420.
Gitanjali. Consistency of 2-out of -3 Redundant Systems with Priority of Repairing the Original Unit, International Journal of Agricultural and Statistical Sciences, 17(1): 2291–2299, 2021. DocID: https://connectjournals.com/03899.2021.17.2291.
Gitanjali and S. C. Malik. Stochastic behaviour of the parallel system with expert repair and maintenance. Life Cycle Reliability and Safety Engineering, 8(1): 55–64, 2018. DOI: 10.1007/s41872-018-0064-6.
J. R., Neyman, and E. L. Scott. Statistical Aspects of Queues, Operation Research, 6(1): 93–103, 1958.
K. Ramesh and R. Gupta. Reliability of a Mechanical System with k-out-of-n subsystems. International Journal of Mechanical and Production Engineering Research and Development, 10(3): 7179–7188, 2020. DOI: 10.24247/IJMPERDJUN2020679.
M. Todinov. Enhancing the Reliability of Series-Parallel Systems With Multiple Redundancies by Using System-Reliability Inequalities. Journal of Risk and Uncertainty in Engineering Systems, 9, 2024. DOI: 10.1115/1.4062892.
Md. A. Lawan, U.A. Ali, A. L. Ismal, Md. S. Isa, A. S. Maihulla, and I. Yusuf. Reliability and Performance Analysis of Two Unit Active Parallel System Attended by Two Repairable Machines. International Journal of Operations Research, 19(2): 27–40, 2022. DOI: 10.6886/IJOR.202201_19(2).0001.
M. Saini, D. Sinwar, A. M. Swarith, and A. Kumar. Reliability and maintainability optimization of load haul dump machines using genetic algorithm and particle swarm optimization. Journal of Quality in Maintenance Engineering, 29(2): 356–376, 2023. DOI: 10.1108/JQME-11-2021-0088.
N. Jaiswal, S. Negi, and S. B. Singh. Reliability analysis of non-repairable weighted k-out-of-n system using belief universal generating function. International Journal of Industrial and Systems Engineering, 28: 300, 2018. DOI: 10.1504/IJISE.2018.089741.
P. Baloda, A. Kumar, and V. Garg. Reliability Estimation of Parallel Systems with Diverse Failure Modes: Semi-Markov Model Approach. Journal of Reliability and Statistical Studies, 17, 2024. DOI: 10.13052/jrss0974-8024.1725.
P. Kumar and A. Kumar. Time dependent performance analysis of a Smart Trash bin using state-based Markov model and Reliability approach, Cleaner Logistics and Supply Chain, 9, 2023, DOI: 10.1016/j.clscn.2023.100122.
P. Lévy, Proceesus semi-markoviens, Proceedings of the International Congress of Mathematics, 3:416–426, 1954.
P. M. Ferreira, J. Ou, C. Gaquière, and P. Benabes. Automated System-Level Design for Reliability: RF Front-End Application. Computational Intelligence in Analog and Mixed-Signal (AMS) and Radio-Frequency (RF) Circuit Design, 2015. DOI: 10.1007/978-3-319-19872-9_13.
P. Sur, semi-Markov Processes, Theory of Probability & Its Applications, 6(1):21–38, 1961. DOI: 10.1137/1106003.
R. Krishnan. Survey of Reliability Analysis of Weighted K-out-of-N System, Science Journal of Applied Mathematics and Statistics, 13: 15–21, 2025, DOI: 10.11648/j.sjams.20251301.12.
R. Surapati, S. Akiri, S. R. Velampudi, and B. V. Nagarjuna. Enhancing Reliability of Series-Parallel Systems: A Novel Mathematical Model for Redundancy Allocation. European Journal of Pure and Applied Mathematic, 18(1):5672, 2025. DOI: 10.29020/nybg.ejpam.v18i1.5672.
S. C. Malik and Gitanjali. A Parallel System with the Arrival time of Expert Server Subject to Maximum Repair and Inspection Times of Ordinary Server. Journal of Reliability and Statistical Studies, 7(1): 103–112, 2014.
S. Jadhav, and A. Kumar. Stochastic modeling and availability optimization of wireless sensor network through particle swarm optimization. Reliability Engineering & System Safety, 265(B), 2026, DOI: 10.1016/j.ress.2025.111538.
S. Kadyan, and S. C. Malik. Stochastic analysis of a three-unit non-identical repairable system with priority to main unit for operation and repair. International Journal of Quality & Reliability Management, 40(1), 2022, DOI: 10.1108/IJQRM-11-2020-0361.
S. K. Kaul, and S. Dey. Reliability Analysis of RF MEMS Devices. Micromachined Circuits and Devices, 859: 225–245, 2022. DOI: 10.1007/978-981-16-9443-1_8.
S. Kundu, A. Kumar and S. Varshney. Bayesian modeling of repairable systems with imperfect coverage and delayed detection dynamics. Quality and Reliability Engineering International, 41(4): 1630–1641, 2025, DOI: 10.1002/qre.3742.
W. Feller. On the Integro-Differential Equations of Purely Discontinuous Markov Processes. Transactions of the American Mathematical Society, 48(3): 488–515, 1940.
Y. Rani, I. Kumar, and Gitanjali. Reliability Modeling of Parallel Tubular and Plate Heat Exchangers using Regenerative Point Technique. International Journal of Information Technology, (2025). DOI: 10.1007/s41870-025-02636-4.
Y. Rani, I. Kumar, and Gitanjali. Enhancing Sustainability through Reliability Optimization of Interconnected Pump and Water Supply Systems Using - a semi Markov Model. Scientific Reports, (2026). DOI: 10.1038/s41598-026-49337-x.
Z. Li, H. Fu, and J. Guo, Reliability Assessment of a Series System with Weibull- Distributed Components Based on Zero-Failure Data. Applied Sciences, 15(5): 2869, 2025, DOI: 10.3390/app15052869.
