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Robin Clark 2013-04-16 14:15:41 +01:00
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15
mybib.bib
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@ -271,10 +271,12 @@ ISSN={Doi:10.1145/2330667.2330683},}
@ARTICLE{fftoriginal,
title={An Algorithm for the Mechine Calculation of Complex Fourier Series},
title={An Algorithm for the Machine Calculation of Complex Fourier Series},
author={James W. Cooley and John W. Tukey},
journal={Mathematics of Computation},
year={1965},
volume={19},
pages={297-301},
publisher={American Mathematical Society}
@ -483,6 +485,13 @@ Database
YEAR = "1991"
}
@ARTICLE{fmeca,
AUTHOR = "United States DOD",
TITLE = "MIL-STD-1629A: Procedure for performing a failure mode, effects and criticality analysis",
JOURNAL = "United States Department of Defence",
YEAR = "1980"
}
% $Id: mybib.bib,v 1.3 2009/11/28 20:05:52 robin Exp $
@article{Clark200519,
title = "Failure Mode Modular De-Composition Using Spider Diagrams",
@ -790,8 +799,8 @@ strength of materials, the causes of boiler explosions",
@BOOK{mil1991,
AUTHOR = "United~States~DOD",
TITLE = "Reliability Prediction of Electronic Equipment",
PUBLISHER = "DOD",
TITLE = "MIL-1991: Reliability Prediction of Electronic Equipment",
PUBLISHER = "United States Department of Defence",
YEAR = "1991"
}

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related_papers_books/FMECA_Mil-Std-1629A.pdf Normal file
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17
submission_thesis/CH7_Evaluation/copy.tex
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@ -1154,20 +1154,26 @@ $ \Omega(C) = fm(C) \cup \{OK\} $).
The $OK$ statistical case is the (usually) largest in probability, and is therefore
of interest when analysing systems from a statistical perspective.
%
For these examples, the OK state is not represented area proportionately, but is included
in the diagrams.
%
This type of diagram is germane to the application of conditional probability calculations
such as Bayes theorem~\cite{probstat}.
The current failure modelling methodologies (FMEA, FMECA, FTA, FMEDA) all use Bayesian
statistics to justify their methodologies~\cite{nucfta}\cite{nasafta}.
%
The current failure modelling methodologies
(FMECA~\cite{fmeca}, FTA~\cite{nucfta}\cite{nasafta}, FMEDA~\cite{en61508})
use Bayesian
statistics to justify their methodologies.
%
That is to say, a base component or a sub-system failure
has a probability of causing given system level failures\footnote{FMECA has a $\beta$ value that directly corresponds
to the probability that a given part failure mode will cause a given system level failure/event.}.
%
Another way to view this is to consider the failure modes of a
component, with the $OK$ state, as a universal set $\Omega$, where
all sets within $\Omega$ are partitioned.
%
Figure \ref{fig:combco} shows a partitioned set representing
component failure modes $\{ B_1 ... B_3, OK \}$: partitioned sets
where the OK or empty set condition is included, obey unitary state conditions.
@ -1193,7 +1199,8 @@ This would make it seemingly impossible to model as `unitary state'.
There are two ways in which we can deal with this.
We could consider the component a composite
of two simpler components, and model their interaction to
create a derived component (i.e. use FMMD on the simpler components).
create a derived component (i.e. use FMMD).
%
The second way to do this would be to consider the combnations of non-mutually
exclusive {\fms} as new {\fms}: this approach is discussed below.