Hostname: page-component-5c6d5d7d68-7tdvq Total loading time: 0 Render date: 2024-08-19T12:23:15.033Z Has data issue: false hasContentIssue false
  • English
  • Français

RELIABILITY COMPARISON OF TWO UNIT REDUNDANCY SYSTEMS UNDER THE LOAD REQUIREMENT

Published online by Cambridge University Press:  04 May 2020

Kyungmee O. Kim Open the ORCID record for Kyungmee O. Kim [Opens in a new window]
Kyungmee O. Kim*
Affiliation:
Department of Industrial Engineering, Konkuk University, Seoul 143-701, Korea E-mail: kyungmee@konkuk.ac.kr
Get access Rights & Permissions [Opens in a new window]

Abstract

This paper compares the reliability functions of the cold standby, hot standby, and load-sharing redundancy configurations, each of which is composed of two identical components for meeting a given system requirement. Thus far, no research has been done into the conditions that make one configuration more reliable than another because their reliability functions have no closed forms even when the component follows a Weibull lifetime distribution. In this paper, two analytical results are obtained given that the reliability of each configuration is expressed in terms of the design and operational loads of the component. First, higher reliability can be achieved in a cold standby configuration than in a load-sharing configuration if the increase in the component reliability obtained from the reduction in the operational load is not significant. Second, a cold standby configuration exhibits better reliability and carries a higher load than a hot standby configuration if the design load can be increased with a less decrease in the component reliability.

Keywords

cold standbyhot standbyload-sharingstep-stress model
Type
Research Article
Information
Probability in the Engineering and Informational Sciences , Volume 35 , Issue 3 , July 2021 , pp. 766 - 780
Copyright
© Cambridge University Press 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Amari, S.V. & Bergman, R. (2008). Reliability analysis of k out of n load sharing systems. In Proceedings Annual Reliability and Maintainability Symposium. Las Vegas: IEEE, pp. 440–445.CrossRefGoogle Scholar
2.Amari, S.V., Misra, K.B., & Pham, H. (2007). Tampered failure rate load-sharing systems: status and perspectives. In Misra, K.B. (ed.), Handbook on performability engineering. New York, NY: Springer, pp. 291–308.Google Scholar
3.Ardakan, M.A. & Hamadani, A.Z. (2018). Multi-objective optimization of reliability-redundancy allocation problem with cold standby strategy using NSGA-II. Reliability Engineering and System Safety 172: 225–238.CrossRefGoogle Scholar
4.Barlow, R.E. & Proschan, F. (1975). Statistical theory of reliability and life testing. New York: Holt, Rinehart and Winston.Google Scholar
5.Bauer, E. & Adams, R. (2012). Reliability and availability of cloud computing. Piscataway: IEEE Press/NJ: John Wiley and Sons.CrossRefGoogle Scholar
6.Bazovsky, I. (2004). Reliability theory and practice. New York: Dover Publications, Inc.Google Scholar
7.Bednarek, K. (2014). Reliability level versus load-carrying capacity of the uninterruptible power systems. Computer Applications in Electrical Engineering 12: 364–375.Google Scholar
8.Bhattacharrya, G.K. & Soejoeti, Z.A. (1989). Tampered failure rate model for step-stress accelerated life test. Communications in Statistics – Theory and Methods 18: 1627–1643.CrossRefGoogle Scholar
9.Curtis, P.M. (2007). Maintaining mission critical systems in a 24/7 environment. Hoboken, NJ: Wiley Interscience, John Wiley and Sons, Inc.CrossRefGoogle Scholar
10.Finkelstein, M. & Hazra, N.K. (2017). On stochastic comparisons for load sharing series and parallel systems. Probability in the Engineering and Informational Sciences 31: 311–329.CrossRefGoogle Scholar
11.Hassett, T.F., Dietrich, D.L., & Szidarovszky, F. (1995). Time varying failure rates in the availability and reliability analysis of repairable systems. IEEE Transactions on Reliability 44: 155–160.CrossRefGoogle Scholar
12.Kenyon, T. (2002). Data networks: routing, security, and performance optimization. Wobun, MA: Elsevier Science.Google Scholar
13.Kim, K.O. (2018). Optimal number of components in a load-sharing system for maximizing reliability. Journal of the Korean Statistical Society 47: 32–40.CrossRefGoogle Scholar
14.Kim, H. & Kim, P. (2017). Reliability-redundancy allocation problem considering optimal redundancy strategy using parallel genetic algorithm. Reliability Engineering and System Safety 159: 153–160.CrossRefGoogle Scholar
15.Kim, K.O., Roh, T., Lee, J.-W., & Zuo, M. (2016). Derating design for optimizing reliability and cost with an application to liquid rocket engines. Reliability Engineering and System Safety 146: 13–20.CrossRefGoogle Scholar
16.Kuo, W., Prasad, V.R., Tillman, F.A., & Hwang, C.-L. (2001). Optimal reliability design. UK: Cambridge University Press.Google Scholar
17.Lee, D., Kim, S., & Chung, T. (2016). Dependability analysis of digital library cloud services with load sharing. In Park, J.J., Loia, V., Yi, G., & Sung, Y. (eds), Advances in computer science and ubiquitous computing. Singapore: Springer, pp. 861–866.Google Scholar
18.Li, J. (2016). Reliability comparative evaluation of active vs standby redundancy. International Journal of Mathematical Engineering and Management Sciences 1: 122–129.CrossRefGoogle Scholar
19.Liang, Y.-C. & Chen, Y.-C. (2004). An ant colony optimization algorithm for the redundancy allocation problem (RAP). IEEE Transactions on Reliability 53: 417–423.CrossRefGoogle Scholar
20.Liang, Y.-C. & Chen, Y.-C. (2007). Redundancy allocation of series parallel system using a variable neighborhood search algorithm. Reliability Engineering and System Safety 92: 323–331.CrossRefGoogle Scholar
21.Liu, H. (1998). Reliability of a load sharing k out of n: G system: non-IID components with arbitrary distributions. IEEE Transactions on Reliability 47: 279–284.Google Scholar
22.Liu, B., Xie, M., & Kuo, W. (2016). Reliability modeling and preventive maintenance of load sharing systems with degrading components. IIE Transactions 48: 699–709.CrossRefGoogle Scholar
23.Mettas, A. & Vassiliou, P. (2004). Application of quantitative accelerated life models on load sharing redundancy. In Proceedings Annual Reliability and Maintainability Symposium. Los Angeles: IEEE, pp.551–555.CrossRefGoogle Scholar
24.Mohammad, R., Kalam, K., & Amari, S.V. (2013). Reliability of load sharing system subject to proportional hazards model. In Proceedings Annual Reliability and Maintainability Symposium, Orlando, FL: IEEE, pp. 1–5.CrossRefGoogle Scholar
25NASA (2005). Exploration systems architecture study. Final Report.Google Scholar
26.Nelson, W.B. (1980). Accelerated life testing — Step stress models and data analysis. IEEE Transactions on Reliability 29: 103–108.CrossRefGoogle Scholar
27.Nelson, W.B. (2004). Applied life data analysis. Hoboken, NJ: John Wiley.Google Scholar
28.Scheuer, E.M. (1988). Reliability of an m out of n system when component failure induces higher failure rates in survivors. IEEE Transactions on Reliability 37: 73–74.CrossRefGoogle Scholar
29.Shao, J. & Lamberson, L.R. (1991). Modeling a shared load k out of n: G system. IEEE Transactions on Reliability 40: 205–209.CrossRefGoogle Scholar
30.Shekar, C., Kumar, A., & Varshney, S. (2020). Load sharing redundant repairable systems with switching and reboot delay. Reliability Engineering and System Safety, 193, 106656, to appear.CrossRefGoogle Scholar
31.Wang, R. & Fei, H. (2004). Conditions for the coincidence of the TFR, TRV and CE models. Statistical Papers 45: 393–412.CrossRefGoogle Scholar
32.Wang, W., Xiong, J., & Xie, M. (2015). Cold-standby redundancy allocation problem with degrading components. International Journal of General Systems 44: 876–888.CrossRefGoogle Scholar
33.Yang, C., Zeng, S., & Guo, J. (2015). Reliability analysis of load-sharing k out of n system considering component degradation. Mathematical Problems in Engineering 2015: 1–10.Google Scholar
34.Ye, Z., Review, M., & Walls, L. (2014). A load sharing system reliability model with managed component degradation. IEEE Transactions on Reliability 63: 721–730.CrossRefGoogle Scholar
35.Yeh, W.C. (2019). Solving cold standby reliability redundancy problem using a new swarm intelligence algorithm. Applied Soft Computing, 83, 105582, to appear.CrossRefGoogle Scholar
36.Yinghui, T. & Jing, Z. (2008). New model for load-sharing k-out-of-n: G system with different components. Journal of Systems Engineering and Electronics 19: 748–751.CrossRefGoogle Scholar
37.Yun, W.Y. & Nakagawa, T. (2017). Comparison between parallel and standby redundant systems. In Reliability modeling with computer and maintenance applications, Chapter 10. Singapore: World Scientific Publishing Co.Google Scholar
38.Zhang, Y. & Zhao, P. (2019). Optimal allocation of minimal repairs in parallel and series systems. Naval Research Logistics 66: 517–526.CrossRefGoogle Scholar
39.Zhang, J., Zhao, Y., & Ma, X. (2020). Reliability modeling methods for load-sharing k out of n system subject to discrete external load. Reliability Engineering and System Safety, 193, 106603, to appear.CrossRefGoogle Scholar
40.Zhao, P., Zhang, Y., & Chen, J. (2017). Optimal allocation policy of one redundancy in a n-component series system. European Journal of Operational Research 257: 656–668.CrossRefGoogle Scholar
41.Zhao, X., Liu, B., & Liu, Y. (2018). Reliability modeling and analysis of load sharing systems with continuously degrading components. IEEE Transactions on Reliability 67: 1096–1110.CrossRefGoogle Scholar