Hostname: page-component-76fb5796d-skm99 Total loading time: 0 Render date: 2024-04-25T16:44:03.763Z Has data issue: false hasContentIssue false

ON THE COMPARISON OF PERFORMANCE-PER-COST FOR COHERENT AND MIXED SYSTEMS

Published online by Cambridge University Press:  19 May 2020

Bo H. Lindqvist
Affiliation:
Department of Mathematical Sciences, Norwegian University of Science and Technology, Trondheim, Norway E-mail: bo.lindqvist@ntnu.no
Francisco J. Samaniego
Affiliation:
Department of Statistics, University of California, Davis, CA, USA
Nana Wang
Affiliation:
Department of Statistics, University of California, Davis, CA, USA

Abstract

The present paper is concerned with reliability economics, considering a certain performance-per-cost criterion for coherent and mixed systems, as introduced in [Dugas, M.R. & Samaniego, F.J. (2007). On optimal system designs in reliability-economics frameworks. Naval Research Logistics 54, 568–582]. We first present a new comparison result for performance-per-cost of systems with independent and identically distributed component lifetimes under certain stochastic orderings. We then consider optimization of the performance-per-cost criterion, first reconsidering and refining results from the above cited paper, and then considering mixtures of given subsets of coherent systems.

Type
Research Article
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

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.Aslett, L.J., Coolen, F.P., & Wilson, S.P. (2015). Bayesian inference for reliability of systems and networks using the survival signature. Risk Analysis 35(9): 16401651.CrossRefGoogle ScholarPubMed
2.Barlow, R.E. & Proschan, F. (1981). Statistical theory of reliability and life testing. Silver Spring, MD: To Begin With.Google Scholar
3.Billinton, R. & Allan, R.N. (2013). Reliability evaluation of power systems, 2nd ed. New York: Springer Science & Business Media.Google Scholar
4.Calabrese, G. (1947). Generating reserve capacity determined by the probability method. Transactions of the American Institute of Electrical Engineers 66(1): 14391450.CrossRefGoogle Scholar
5.Coolen, F.P. & Coolen-Maturi, T. (2012). Generalizing the signature to systems with multiple types of components. In Zamojsk, W., Mazurkiewicz, J., Sugier, J., Walkowiak, T., & Kacprzyk, J. (eds), Complex Systems and Dependability. Advances in Intelligent and Soft Computing, vol. 170. Berlin, Heidelberg: Springer, pp. 115130.Google Scholar
6.Da, G., Chan, P.S., & Xu, M. (2018). On the signature of complex system: A decomposed approach. European Journal of Operational Research 265(3): 11151123.CrossRefGoogle Scholar
7.Dugas, M.R. & Samaniego, F.J. (2007). On optimal system designs in reliability-economics frameworks. Naval Research Logistics (NRL) 54(5): 568582.CrossRefGoogle Scholar
8.Dupuits, E., Schweckendiek, T., & Kok, M. (2017). Economic optimization of coastal flood defense systems. Reliability Engineering & System Safety 159: 143152.CrossRefGoogle Scholar
9.Georgilakis, P.S. & Katsigiannis, Y.A. (2009). Reliability and economic evaluation of small autonomous power systems containing only renewable energy sources. Renewable Energy 34(1): 6570.CrossRefGoogle Scholar
10.Huang, X., Aslett, L.J., & Coolen, F.P. (2019). Reliability analysis of general phased mission systems with a new survival signature. Reliability Engineering & System Safety 189: 416422.CrossRefGoogle Scholar
11.Lindqvist, B.H., Samaniego, F.J., & Huseby, A.B. (2016). On the equivalence of systems of different sizes, with applications to system comparisons. Advances in Applied Probability 48(2): 332348.CrossRefGoogle Scholar
12.Navarro, J., Águila, Y., Sordo, M.A., & Suárez-Llorens, A. (2014). Preservation of reliability classes under the formation of coherent systems. Applied Stochastic Models in Business and Industry 30(4): 444454.CrossRefGoogle Scholar
13.Samaniego, F.J. (1985). On closure of the IFR class under formation of coherent systems. IEEE Transactions on Reliability 34(1): 6972.CrossRefGoogle Scholar
14.Samaniego, F.J. (2007). System signatures and their applications in engineering reliability, vol. 110. New York: Springer Science & Business Media.CrossRefGoogle Scholar
15.Samaniego, F.J. & Navarro, J. (2016). On comparing coherent systems with heterogeneous components. Advances in Applied Probability 48(1): 88111.CrossRefGoogle Scholar
16.Shaked, M. & Shanthikumar, G. (2007). Stochastic orders. New York: Springer Science & Business Media.CrossRefGoogle Scholar
17.Tazi, N., Châtelet, E., Meziane, R., & Bouzidi, Y. (2016). Reliability optimization of wind farms considering constraints and regulations. In 2016 IEEE International Conference on Renewable Energy Research and Applications (ICRERA). IEEE, pp. 130–136.CrossRefGoogle Scholar
18.Watchorn, C. (1950). The determination and allocation of the capacity benefits resulting from interconnecting two or more generating systems. Transactions of the American Institute of Electrical Engineers 69(2): 11801186.CrossRefGoogle Scholar
19.Zhou, P., Jin, R., & Fan, L. (2016). Reliability and economic evaluation of power system with renewables: A review. Renewable and Sustainable Energy Reviews 58: 537547.CrossRefGoogle Scholar