Capacity loss and residual capacity in weighted k-out-of-n: G systems

A binary weighted-k-out-of-n:G system is a system that consists of n binary components, and functions if and only if the total weight of working components is at least k. The performance of such a system is characterized by its total weight/capacity. Therefore, the evaluation of the capacity of the system is of special importance for understanding the behavior of the system over time. This paper is concerned with capacity loss and residual capacity in binary weighted-k-out-of-n:G systems. These measures are potentially useful for the purposes of preventive action. In particular, recursive and non-recursive equations are obtained for the mean capacity loss and mean residual capacity of the binary weighted-k -out-of-n:G system while it is working at a specific time. The mean residual capacity after the failure of the system is also studied.

[1]  Minge Xie,et al.  Modeling the reliability of threshold weighted voting systems , 2005, Reliab. Eng. Syst. Saf..

[2]  Serkan Eryilmaz,et al.  An algorithmic approach for the dynamic reliability analysis of non-repairable multi-state weighted k-out-of-n: G system , 2014, Reliab. Eng. Syst. Saf..

[3]  Rong-Jaye Chen,et al.  An algorithm for computing the reliability of weighted-k-out-of-n systems , 1994 .

[4]  S. Eryilmaz,et al.  Modeling and analysis of weighted-k-out-of-n: G system consisting of two different types of components , 2014 .

[5]  Ali M. Rushdi,et al.  Threshold systems and their reliability , 1990 .

[6]  Yong Chen,et al.  Reliability of two-stage weighted-k-out-of-n systems with components in common , 2005, IEEE Trans. Reliab..

[7]  Yong Wang,et al.  Reliability and covariance estimation of weighted k-out-of-n multi-state systems , 2012, Eur. J. Oper. Res..

[8]  Frank P. A. Coolen,et al.  Nonparametric predictive reliability of series of voting systems , 2013, Eur. J. Oper. Res..

[9]  J. Scott Provan,et al.  Threshold reliability of networks with small failure sets , 1995, Networks.

[10]  Gregory Levitin Multi-State Vector-k-Out-of-n Systems , 2013, IEEE Transactions on Reliability.

[11]  Kirtee K. Kamalja,et al.  RELIABILITY AND IMPORTANCE MEASURES OF WEIGHTED-k-OUT-OF-n SYSTEM , 2014 .

[12]  Wei Li,et al.  A Framework for Reliability Approximation of Multi-State Weighted $k$-out-of-$n$ Systems , 2010, IEEE Transactions on Reliability.

[13]  Min Xie,et al.  Dynamic availability assessment and optimal component design of multi-state weighted k-out-of-n systems , 2014, Reliab. Eng. Syst. Saf..

[14]  Kirtee K. Kamalja,et al.  Computational Methods for Reliability and Importance Measures of Weighted-Consecutive-System , 2014, IEEE Transactions on Reliability.

[15]  Wei Li,et al.  Optimal design of multi-state weighted k-out-of-n systems based on component design , 2008, Reliab. Eng. Syst. Saf..

[16]  Serkan Eryilmaz,et al.  Mean instantaneous performance of a system with weighted components that have arbitrarily distributed lifetimes , 2013, Reliab. Eng. Syst. Saf..

[17]  Wei Li,et al.  Reliability evaluation of multi-state weighted k-out-of-n systems , 2008, Reliab. Eng. Syst. Saf..

[18]  Serkan Eryilmaz Mean Time to Failure of Weighted k-out-of-n: G Systems , 2015, Commun. Stat. Simul. Comput..

[19]  Moshe Shaked,et al.  Systems with weighted components , 2008 .

[20]  Serkan Eryilmaz,et al.  Computing marginal and joint Birnbaum, and Barlow-Proschan importances in weighted-k-out-of-n: G systems , 2014, Comput. Ind. Eng..