mttr {smmR} | R Documentation |
Mean Time To Repair (MTTR) Function
Description
Consider a system that has just failed at time
. The mean time to repair (MTTR) is defined as the mean of the
repair duration.
Usage
mttr(x, upstates = x$states, level = 0.95, klim = 10000)
Arguments
x |
An object of S3 class |
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 |
Details
Consider a system (or a component) whose possible
states during its evolution in time are
.
Denote by
the subset of operational states of
the system (the up states) and by
the
subset of failure states (the down states), with
(obviously,
and
,
). One can think of the states
of
as different operating modes or performance levels of the
system, whereas the states of
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 . Consequently, we suppose
that the evolution in time of the system is governed by an E-state space
semi-Markov chain
. The system has just failed at
instant 0 and the state of the system is given at each instant
by
: the event
, for a certain
, means that the system
is in operating mode
at time
, whereas
, for a certain
, means that the system is not operational at time
due to the mode of failure
or that the system is under the
repairing mode
.
Let denote the first passage time in subset
, called the
duration of repair or repair time, i.e.,
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 ,
Value
A matrix with rows, and with columns
giving values of the mean time to repair for each state
,
variances, lower and upper asymptotic confidence limits (if
x
is an
object of class smmfit
).
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.
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