Consider a system \(S_{ystem}\) that has just failed at time \(k = 0\). The mean time to repair (MTTR) is defined as the mean of the repair duration.
mttr(x, upstates = x$states, level = 0.95, klim = 10000)An object of S3 class smmfit or smm.
Vector giving the subset of operational states \(U\).
Confidence level of the asymptotic confidence interval. Helpful
for an object x of class smmfit.
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.
A matrix with \(\textrm{card}(U) = s_{1}\) rows, and with columns
giving values of the mean time to repair for each state \(i \in U\),
variances, lower and upper asymptotic confidence limits (if x is an
object of class smmfit).
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 mean time to repair 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 has just failed 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 \(j\).
Let \(T_U\) denote the first passage time in subset \(U\), called the duration of repair or repair time, i.e.,
$$T_U := \textrm{inf}\{ n \in N;\ Z_n \in U\}\ \textrm{and}\ \textrm{inf}\ \emptyset := \infty.$$
The mean time to repair (MTTR) is defined as the mean of the repair duration, i.e., the expectation of the hitting time to up set \(U\),
$$MTTR = E[T_{U}]$$
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.
I. Votsi & A. Brouste (2019) Confidence interval for the mean time to failure in semi-Markov models: an application to wind energy production, Journal of Applied Statistics, 46:10, 1756-1773