Performance Evaluation of a Parallel System with Asymmetric Units and Dynamic Repair Prioritization
DOI:
https://doi.org/10.13052/jrss0974-8024.1912Keywords:
Non-identical units, parallel system, dual priority conditions, regenerative point techniqueAbstract
In this paper, a parallel system consisting of two non-identical units has been studied. These dissimilar units of system are assumed to have different characteristics and different types of failure modes. All types of failures are treated by a single repairman who is made available to the system within no time. Some constraints for repair priorities are introduced for the system, which will vary as per unit undergoing failure. Failure rates of both units are assumed to follow exponential distribution, while repair rates are supposed to have any arbitrary distribution. To evaluate the system’s reliability measures, Regenerative Point Technique has been used. Also, graphical and numerical representations are provided to illustrate the variations in these measures with respect to all parameters involved within system.
Downloads
References
Feizabadi, M., and Jahromi, A. E. (2017). A new model for reliability optimization of series-parallel systems with non-homogeneous components. Reliability Engineering and System Safety, 157, 101–112.
Ghnimi, S., Gasmi, S., and Nasr, A. (2017). Reliability parameters estimation for parallel systems under imperfect repair. Metrika, 80, 273–288.
Chauhan, S. K., and Malik, S. C. (2017). Evaluation of reliability and MTSF of a parallel system with Weibull failure laws. Journal of Reliability and Statistical Studies, 10(1), 137–148.
Ding, Y., Lin, Y., Peng, R., and Zuo, M. J. (2019). Approximate reliability evaluation of large-scale multistate series-parallel systems. IEEE Transactions on Reliability, 68(2), 539–553.
Kumar, A., Pawar, D., and Malik, S. C. (2020). Reliability analysis of a redundant system with FCFS repair policy subject to weather conditions. International Journal of Advanced Science and Technology, 29(3), 7568–7578.
Shekhar, C., Kumar, A., Varshney, S., and Ammar, S. I. (2020). Fault-tolerant redundant repairable system with different failures and delays. Engineering Computations, 37(3), 1043–1071.
Shekhar, C., Kumar, A., and Varshney, S. (2020). Load sharing redundant repairable systems with switching and reboot delay. Reliability Engineering and System Safety, 193, 106656.
Kumar, A., and Kumar, P. (2020). Application of Markov process/mathematical modelling in analysing communication system reliability. International Journal of Quality and Reliability Management, 37(2), 354–371.
Khalil, N., and Yusuf, I. (2021). Reliability models of a series-parallel system with replacement at failure. International Journal of Operational Research, 40(4), 524–543.
Kumar, K., Kumar, B., and Ravi, V. (2021). Study of reliability measures of a two unit system with inspection and on-line/off-line repairs using the regenerative point technique. International Journal of Operations Research, 18(3), 57–66.
Goyal, N., Ram, M., Amoli, S., and Suyal, A. (2017). Sensitivity analysis of a three-unit series system under k-out-of-n redundancy. International Journal of Quality and Reliability Management, 34(6), 770–784.
Monika, Chopra, G., and Sheetal. (2024). Sensitivity and performance analysis of a three-unit soft biscuit manufacturing system with two types of repairers. International Journal of System Assurance Engineering and Management, 1–14.
Yadav, A. D., Nandal, N., Malik, S., and Malik, S. C. (2023). Markov approach for reliability-availability-maintainability analysis of a three unit repairable system. Opsearch, 60(4), 1731–1756.
Shekhar, C., Kumar, N., Gupta, A., Kumar, A., and Varshney, S. (2020). Warm-spare provisioning computing network with switching failure, common cause failure, vacation interruption, and synchronized reneging. Reliability Engineering and System Safety, 199:106910.
Shekhar, C., Kumar, A., and Varshney, S. (2020). Parametric nonlinear programming for fuzzified queuing systems with catastrophe. International Journal of Process Management and Benchmarking, 10(1), 69–98.
Kumar, P., and Kumar, A. (2023). Time dependent performance analysis of a Smart Trash bin using state-based Markov model and Reliability approach. Cleaner Logistics and Supply Chain, 9, 100122.
Kumar, P., and Kumar, A. (2023). Quantifying reliability indices of garbage data collection IOT-based sensor systems using Markov birth-death process. International Journal of Mathematical, Engineering and Management Sciences, 8(6), 1255.
Kumar, A., and Ram, M. (2023). 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.
Bhat, K. S., and Simon, M. K. (2024). Stochastic analysis of a complex repairable system with a constrain on the number of repairs. Reliability: Theory and Applications, 19(2(78)), 178–187.
Sonker, P., and Bhardwaj, R. K. (2024). Enhancing redundant system performance: A stochastic model for optimized inspection strategies post-failure. Reliability: Theory and Applications, 19(4(80)), 448–460.
Baloda, P., Kumar, A., and Garg, V. (2024). Reliability estimation of parallel systems with diverse failure modes: Semi-Markov model approach. Journal of Reliability and Statistical Studies, 17(2), 351–366.
Kumar, A. (2025). Parametric optimization of repairable systems in IoT: addressing detection delays, imperfect coverage, and fuzzy parameters. Life Cycle Reliability & Safety Engineering, 14, 329–-340.
