Working on presentation while ill (have not eaten for 54+ hours)

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Robin Clark 2011-10-27 17:14:15 +01:00
parent 640f27125a
commit 4059c7f79c
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DIAPNG= component.png fmmd_env_op_uml.png fmmd_exm_h.png master_uml.png mvampcircuit.png mvamp.png n_inv_dc.png pd.png pd_euler2.png pd_euler.png
DIAPNG= three_tree.png component.png fmmd_env_op_uml.png fmmd_exm_h.png master_uml.png mvampcircuit.png mvamp.png n_inv_dc.png pd.png pd_euler2.png pd_euler.png
%.png:%.dia
dia -t png $<

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@ -22,7 +22,9 @@
\frametitle{FMEA}
%\tableofcontents[currentsection]
\end{frame}
This talk introduces Failure Mode Effects Analysis, and the different ways it is applied.
These techniques are discussed, and then
a refinement is proposed, which is essentially a modularisation of the FMEA process.
\begin{frame}
\frametitle{FMEA}
\begin{itemize}
@ -129,13 +131,13 @@ We need to look at a large number of failure scenarios
to do this completely (all failure modes against all components).
This is represented in the equation below. %~\ref{eqn:fmea_state_exp},
where $N$ is the total number of components in the system, and
$cfm$ is the number of failure modes per component.
$f$ is the number of failure modes per component.
\begin{equation}
\label{eqn:fmea_single}
N.(N-1).cfm % \\
%(N^2 - N).cfm
N.(N-1).f % \\
%(N^2 - N).f
\end{equation}
\end{frame}
@ -159,11 +161,14 @@ $N^3$.
\begin{equation}
\label{eqn:fmea_double}
N.(N-1).(N-2).cfm % \\
%(N^2 - N).cfm
N.(N-1).(N-2).f % \\
%(N^2 - N).f
\end{equation}
$100*99*98*3=2,910,600$.
\pause
.\\
The European Gas burner standard (EN298:2003), demands the checking of
double failure scenarios (for burner lock-out scenarios).
@ -438,6 +443,7 @@ against all safe and dangerous failure probabilities.
Again this is usually expressed as a percentage.
$$ SFF = \big( \Sigma\lambda_S + \Sigma\lambda_{DD} \big) / \big( \Sigma\lambda_S + \Sigma\lambda_D \big) $$
\pause
SFF determines how proportionately fail-safe a system is, not how reliable it is ! \pause
Weakness in this philosophy; \pause adding extra safe failures (even unused ones) improves the SFF.
@ -577,12 +583,12 @@ judged to be in critical sections of the product.
% to do this completely (all failure modes against all components).
% This is represented in equation~\ref{eqn:fmea_state_exp},
% where $N$ is the total number of components in the system, and
% $cfm$ is the number of failure modes per component.
% $f$ is the number of failure modes per component.
%
% \begin{equation}
% \label{eqn:fmea_state_exp}
% N.(N-1).cfm % \\
% %(N^2 - N).cfm
% N.(N-1).f % \\
% %(N^2 - N).f
% \end{equation}
@ -606,6 +612,8 @@ This creates an analysis hierarchy.
\pause \item Collect Symptoms.
\pause \item Create a '{\dc}', where its failure modes are the symptoms of the {\fg} from which it was derived.
\pause \item The {\dc} is now available to be used in higher level {\fgs}.
\pause \item We can represent this process as a function which converts a {\fg} into a {\dc} and use the symbol $ \bowtie $ to represet it.
\pause \item i.e. $ \bowtie ( FunctionalGroup ) \rightarrow {DerivedComponent} $
\end{itemize}
\end{frame}
@ -623,7 +631,7 @@ This creates an analysis hierarchy.
We can return to the milli-volt amplifier as an example to analyse.
\pause
We can begin by looking for functional groups.\pause
The resistors would together to perform a fairly common function in electronics, that of the potential divider.
The resistors perform a fairly common function in electronics, that of the potential divider.
So our first functional group is $\{ R1, R2 \}$.\pause
We can now take the failure modes for the resistors (OPEN and SHORT EN298) and see what effect each of these failures will have on the {\fg} (the potential divider).
@ -652,6 +660,7 @@ Resistor and its failure modes represented as a directed graph.
\begin{table}
\begin{tabular}{|| l | l | c | c | l ||} \hline
\textbf{Failure Scenario} & & \textbf{Pot Div Effect} & & \textbf{Symptom} \\
\textbf{ / test case } & & \textbf{ } & & \textbf{ } \\
\hline
FS1: R1 SHORT & & $LOW$ & & $PDLow$ \\ \hline
FS2: R1 OPEN & & $HIGH$ & & $PDHigh$ \\ \hline
@ -782,36 +791,50 @@ how the levels work and converge to a top or system level.
\caption{Functional Group Tree example}
\label{fig:three_tree}
\end{figure}
\end{frame}
\begin{frame}
\frametitle{FMMD - Failure Mode Modular De-Composition}
\begin{frame}
\frametitle{FMMD - Failure Mode Modular De-Composition}
The fact FMMD analyses small groups of components at a time, and organises them
into a hierarchy
addresses the state explosion problem. \pause
Where $O$ is order
of complexity $O(N^2)$ in the equation below.
For FMEA where we check every component failure mode rigorously
against all the other components (we could call this \textbf{RFMEA})
Where $N$ is the number of components, we can determine the order
of complexity $ O(N^2) $ thus.
% %
\begin{equation}
\label{eqn:fmea_single2}
N.(N-1).cfm % \\
%(N^2 - N).cfm
N.(N-1).f
\end{equation}
%
% %\end{frame}
\end{frame}
\begin{frame}
\frametitle{FMMD - comparing number of checks RFMEA $\ldots$ FMMD}
%\end{frame}
If we consider $c$ to be the number of components in a {\fg}, $f$ is the number of failure modes per component, and
$L$ to be the number of levels in the hierarchy of FMMD analysis.
%\begin{frame}
We can represent the number of failure scenarios to check in an FMMD hierarchy
with equation~\ref{eqn:anscen}.
\pause
\begin{equation}
\label{eqn:anscen}
\sum_{n=0}^{L} {fgn}^{n}.fgn.cfm.(fgn-1)
\sum_{n=0}^{L} {c}^{n}.c.f.(c-1)
\end{equation}
Where $fgn$ is the number of components in each functional group,
and $cfm$ is the number of failure modes per component
and L is the number of levels, the number of
analysis scenarios to consider.
% Where $c$ is the number of components in each functional group,
% and $f$ is the number of failure modes per component
% and L is the number of levels, the number of
% analysis scenarios to consider.
~\ref{eqn:fmea_state_exp}.
%%~\ref{eqn:fmea_state_exp}.
\end{frame}
@ -833,18 +856,18 @@ analysis scenarios to consider.
% In other words, we have three components in our functional group,
% and nine failure modes to consider.
% So taking each failure mode and looking at how that could affect the functional group,
% we must compare each failure mode against the two other components (the `$fgn-1$' term).
% we must compare each failure mode against the two other components (the `$c-1$' term).
%
% For the one `zero' level FMMD case we are doing the same thing as FMEA type analysis
% (but on a very simple small sub-system).
% We are looking at how each failure~mode can effect the system/top level.
% We can use equation~\ref{eqn:fmea_state_exp44} to represent
% the number of checks to rigorously perform FMEA, where $N$ is the total
% number of components in the system, and $cfm$ is the number of failures per component.
% number of components in the system, and $f$ is the number of failures per component.
%
% Where $N=3$ and $cfm=3$ we can see that the number of checks for this simple functional
% Where $N=3$ and $f=3$ we can see that the number of checks for this simple functional
% group is the same for equation~\ref{eqn:fmea_state_exp22}
% and equation~\ref{eqn:anscen}.
% \clearpage
@ -855,7 +878,7 @@ analysis scenarios to consider.
To see the effects of reducing `state~explosion' we can use an example.
% with fixed numbers
%for components in a functional group, and failure modes per component.
Let us take a system with 4 levels (with a top/system 0 level),
Let us take a system with 3 levels of FMMD analysis,
with three components per functional group and three failure modes per component,
and apply these formulae.
Having 4 levels (in addition to the top zeroth level)
@ -865,14 +888,14 @@ $$
%\begin{equation}
\label{eqn:fmea_state_exp22}
81.(81-1).3 = 19440 % \\
%(N^2 - N).cfm
%(N^2 - N).f
%\end{equation}
$$
$$
%\begin{equation}
% \label{eqn:anscen}
\sum_{n=0}^{4} {3}^{n}.3.3.(2) = 2178
\sum_{n=0}^{3} {3}^{n}.3.3.(2) = 720
%\end{equation}
$$
\end{frame}
@ -884,10 +907,10 @@ $$
\begin{itemize}
\pause \item Thus for FMMD we needed to examine 2178 failure~modes against functionally adjacent components, and for traditional FMEA
\pause \item Thus for FMMD we needed to examine 720 failure~modes against functionally adjacent components, and for traditional FMEA
type analysis methods, the number rises to 19440.
\pause \item 19440 `checks' is not practical
\pause \item 2178 checks is alot, but...
\pause \item 720 checks is quite alot, but...
\pause \item Modules in FMMD can be re-used...
\end{itemize}
% In practical example followed through, no more than 9 components have ever been required for a functional
@ -907,22 +930,31 @@ To determine all possible double simultaneous failures for rigorous FMEA
\begin{equation}
\label{eqn:fmea_state_exp2}
N.(N-1).(N-2).cfm % \\
%(N^2 - N).cfm
N.(N-1).(N-2).f % \\
%(N^2 - N).f
\end{equation}
Or express in terms of the level
\begin{equation}
\label{eqn:fmea_state_exp2}
c^{L+1}.(c^{L+1}-1).(c^{L+1}-2).f % \\
%(N^2 - N).f
\end{equation}
\pause
The FMMD case (equation~\ref{eqn:anscen2}), is cubic within the functional groups only,
not all the components in the system.
\begin{equation}
\label{eqn:anscen2}
\sum_{n=0}^{L} {fgn}^{n}.fgn.cfm.(fgn-1).(fgn-2)
\sum_{n=0}^{L} {c}^{n}.c.f.(c-1).(c-2)
\end{equation}
\end{frame}
\begin{frame}
\frametitle{FMMD - Failure Mode Modular De-Composition}
\textbf{Traceability}
Because each reasoning stage contains associations ($FailureMode \mapsto Symptom$)
Because each reasoning stage contains associations ($FailureMode \rightarrow Symptom$)
we can trace the `reasoning' from base level component failure mode to top level/system
failure, by traversing the tree/hierarchy. This is in effect providing a `framework' of the reasoning.

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