maintainability | R Documentation |
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
.
maintainability(x, k, upstates = x$states, level = 0.95, klim = 10000)
x |
An object of S3 class |
k |
A positive integer giving the period |
upstates |
Vector giving the subset of operational states |
level |
Confidence level of the asymptotic confidence interval. Helpful
for an object |
klim |
Optional. The time horizon used to approximate the series in the
computation of the mean sojourn times vector |
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).
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
).
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.
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