Learn R Programming

smmR (version 1.0.3)

maintainability: Maintainability Function

Description

For a reparable system \(S_{ystem}\) for which the failure occurs at time \(k = 0\), its maintainability at time \(k \in N\) is the probability that the system is repaired up to time \(k\), given that it has failed at time \(k = 0\).

Usage

maintainability(x, k, upstates = x$states, level = 0.95, klim = 10000)

Arguments

x

An object of S3 class smmfit or smm.

k

A positive integer giving the period \([0, k]\) on which the maintainability should be computed.

upstates

Vector giving the subset of operational states \(U\).

level

Confidence level of the asymptotic confidence interval. Helpful for an object x of class smmfit.

klim

Optional. The time horizon used to approximate the series in the computation of the mean sojourn times vector \(m\) (cf. meanSojournTimes function) for the asymptotic variance.

Value

A matrix with \(k + 1\) rows, and with columns giving values of the maintainability, variances, lower and upper asymptotic confidence limits (if x is an object of class smmfit).

Details

Consider a system (or a component) \(S_{ystem}\) whose possible states during its evolution in time are \(E = \{1,\dots,s\}\). Denote by \(U = \{1,\dots,s_1\}\) the subset of operational states of the system (the up states) and by \(D = \{s_1 + 1,\dots, s\}\) the subset of failure states (the down states), with \(0 < s_1 < s\) (obviously, \(E = U \cup D\) and \(U \cap D = \emptyset\), \(U \neq \emptyset,\ D \neq \emptyset\)). One can think of the states of \(U\) as different operating modes or performance levels of the system, whereas the states of \(D\) can be seen as failures of the systems with different modes.

We are interested in investigating the maintainability of a discrete-time semi-Markov system \(S_{ystem}\). Consequently, we suppose that the evolution in time of the system is governed by an E-state space semi-Markov chain \((Z_k)_{k \in N}\). The system starts to fail at instant \(0\) and the state of the system is given at each instant \(k \in N\) by \(Z_k\): the event \(\{Z_k = i\}\), for a certain \(i \in U\), means that the system \(S_{ystem}\) is in operating mode \(i\) at time \(k\), whereas \(\{Z_k = j\}\), for a certain \(j \in D\), means that the system is not operational at time \(k\) due to the mode of failure \(j\) or that the system is under the repairing mode \(j\).

Thus, we take \((\alpha_{i} := P(Z_{0} = i))_{i \in U} = 0\) and we denote by \(T_U\) the first hitting time of subset \(U\), called the duration of repair or repair time, that is,

$$T_U := \textrm{inf}\{ n \in N;\ Z_n \in U\}\ \textrm{and}\ \textrm{inf}\ \emptyset := \infty.$$

The maintainability at time \(k \in N\) of a discrete-time semi-Markov system is

$$M(k) = P(T_U \leq k) = 1 - P(T_{U} > k) = 1 - P(Z_{n} \in D,\ n = 0,\dots,k).$$

References

V. S. Barbu, N. Limnios. (2008). Semi-Markov Chains and Hidden Semi-Markov Models Toward Applications - Their Use in Reliability and DNA Analysis. New York: Lecture Notes in Statistics, vol. 191, Springer.