The Reliability of $K$ Out of $N$ Systems

Abstract

A system with $n$ independent components which functions if and only if at least $k$ of the components function is a $k$ out of $n$ system. Parallel systems are 1 out of $n$ systems and series systems are $n$ out of $n$ systems. If $\mathbf{p} = (p_1, \cdots, p_n)$ is the vector of component reliabilities for the $n$ components, then $h_k(\mathbf{p})$ is the reliability function of the system. It is shown that $h_k(\mathbf{p})$ is Schur-convex in $\lbrack(k - 1)/(n - 1), 1\rbrack^n$ and Schur-concave in $\lbrack 0, (k - 1)/(n - 1)\rbrack^n$. More particularly if $\prod$ is an $n \times n$ doubly stochastic matrix, then $h_k(\mathbf{p}) \geq (\leq)h_k(\mathbf{p}\prod)$ whenever $\mathbf{p} \in \lbrack(k - 1)/(n - 1), 1\rbrack^n(\lbrack 0, (k - 1)/(n - 1)\rbrack^n)$. This Theorem is compared with a result on Schur-convexity and -concavity by Gleser [2] which in turn extends work of Hoeffding [4].