and put the formal defininitions into the appendix, along with the algorithm descriptions. Needs red penning. Alot probably. Going to dump a full back up on ubuntu one just in case I forgot to `git add' any graphics file. find out at work on tuesday.
305 lines
12 KiB
TeX
305 lines
12 KiB
TeX
\section*{Metrics}
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\section{Defining the concept of `comparison~complexity' in FMEA}
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%
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% DOMAIN == INPUTS
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% RANGE == OUTPUTS
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%
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When performing FMEA, we have a system under investigation, which will be
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comprised of a collection of components which have associated failure modes.
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The object of FMEA is to determine cause and effect:
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from the failure modes (the causes, {\fms} of {\bcs}) to the effects (or symptoms of failure) at the top level.
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%
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To perform FMEA rigorously
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we could stipulate that every failure mode must be checked for effects
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against all the components in the system.
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We could term this `rigorous~FMEA'~(RFMEA).
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The number of checks we have to make to achieve this, gives an indication of the complexity of the task.
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%
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We could term this `comparison~complexity', as the number of
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paths between failure modes and components necessary to achieve RFMEA for a given system/functional~group.
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% (except its self of course, that component is already considered to be in a failed state!).
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%
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Obviously, for a small number of components and failure modes, we have a smaller number
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of checks to make than for a complicated larger system.
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%
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We can consider the system as a large {\fg} of components.
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We represent the number of components in the {\fg} $G$, by
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$ | G | $,
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(an indexing and sub-scripting notation to identify particular {\fgs}
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within an FMMD hierarchy is given in section~\ref{sec:indexsub}).
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The function $fm$ has a component as its domain and the components failure modes as its range (see equation~\ref{eqn:fm}).
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We can represent the number of potential failure modes of a component $c$, to be $ | fm(c) | .$
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If we index all the components in the system under investigation $ c_1, c_2 \ldots c_{|\FG|} $ we can express
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the number of checks required to rigorously examine every
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failure mode against all the other components in the system.
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We can define this as a function, Comparison Complexity, $CC$, with its domain as the system
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or {\fg}, $\FG$, and
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its range as the number of checks to perform to satisfy a rigorous FMEA inspection.
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Where $\mathcal{\FG}$ represents the set of all {\fgs}, and $ \mathbb{N} $ any natural integer, $CC$ is defined by,
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\begin{equation}
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%$$
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CC:\mathcal{\FG} \rightarrow \mathbb{N},
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%$$
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\end{equation}
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and, where n is the number of components in the system/{\fg}, $|fm(c_i)|$ is the number of failure modes
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in component ${c_i}$, is given by
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\begin{equation}
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\label{eqn:CC}
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%$$
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%%% when it was called reasoning distance -- 19NOV2011 -- RD(fg) = \sum_{n=1}^{|fg|} |fm(c_n)|.(|fg|-1)
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CC(\FG) = (n-1) \sum_{1 \le i \le n} fm(c_i).
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%$$
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\end{equation}
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This can be simplified if we can determine the total number of failure modes in the system $K$, (i.e. $ K = \sum_{n=1}^{|G|} {|fm(c_n)|}$);
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equation~\ref{eqn:CC} becomes
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%$$
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\begin{equation}
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\label{eqn:rd2}
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CC(\FG) = K.(|\FG|-1).
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\end{equation}
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%$$
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%Equation~\ref{eqn:rd} can also be expressed as
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%
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% \begin{equation}
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% \label{eqn:rd2}
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% %$$
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% CC(G) = {|G|}.{|fm(c_n)|}.{(|fg|-1)} .
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% %$$
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% \end{equation}
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\subsection{A general formula for counting Comparison Complexity in an FMMD hierarchy}
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An FMMD Hierarchy will have reducing numbers of functional groups as we progress up the hierarchy.
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In order to calculate its comparison~complexity we need to apply equation~\ref{eqn:CC} to
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all {\fgs} on each level.
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We define a helper function $g$ with a domain of the level $i$ in an FMMD hierarchy $H$, and a co-domain of a set of {\fgs} (specifically all the {\fgs} on the given level),
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defined by
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\begin{equation}
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%$$
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g(H, i) \rightarrow \forall {\FG}^{\xi} \;where\; ({\xi} = {i}) \wedge ({\FG}^{\xi} \in H) .
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%$$
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\end{equation}
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Where $L$ represents the number of levels in the FMMD hierarchy,
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$|g(\xi)|$ represents the number of functional groups on the level
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and $H$ represents an FMMD hierarchy,
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we overload the comparison complexity thus:
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%$$
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\begin{equation}
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\label{eqn:gf}
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CC(H) = \sum_{\xi=0}^{L} \sum_{j=1}^{|g(H,\xi)|} CC({\FG}_{j}^{\xi}).
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%$$
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\end{equation}
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\pagebreak[4]
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\subsection{Complexity Comparison Examples}
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The potential divider discussed in section~\ref{potdivfmmd} has four failure modes and two components and therefore has $CC$ of 4.
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$$CC(potdiv) = \sum_{n=1}^{2} |2|.(|1|) = 4 $$
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Even considering a $example$ system with just 81 components (with these components
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having 3 failure modes each) we would have an $CC$ of
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$$CC(example) = \sum_{n=1}^{81} |3|.(|80|) = 19440 .$$
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Ensuring all component failure modes are checked against all other components in a system
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-- applying FMEA rigorously -- could be termed
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Rigorous FMEA (RFMEA).
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The computational order for RFMEA would be polynomial ($O(N^2.K)$) (where $K$ is the variable number of failure modes).
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This order may be acceptable in a computational environment: However, the choosing of {\fgs} and the analysis
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process are by-hand/human activities. It can be seen that it is practically impossible to achieve
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RFMEA for anything but trivial systems.
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%
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% Next statement needs alot of justification
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%
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It is the authors belief that FMMD reduces the comparison complexity enough to make
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rigorous checking feasible.
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\pagebreak[4]
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%\subsection{Using the concept of Complexity Comparison to compare RFMEA with FMMD}
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\begin{figure}
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\centering
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\includegraphics[width=400pt,keepaspectratio=true]{CH5_Examples/three_tree.png}
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% three_tree.png: 851x385 pixel, 72dpi, 30.02x13.58 cm, bb=0 0 851 385
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\caption{FMMD Hierarchy with number of components in {\fg} fixed to 3 $(|G| = 3)$ } % \wedge (|fm(c)| = 3)$}
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\label{fig:three_tree}
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\end{figure}
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\subsection{Comparing FMMD and RFMEA comparison complexity}
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Because components have variable numbers of failure modes,
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and {\fgs} have variable numbers of components, it is difficult to
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use the general formula for comparing the number of checks to make for
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RFMEA and FMMD.
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%
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If we were to create an example by fixing the number of components in a {\fg}
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and the number of failure modes per component, we can derive formulae
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to compare the number of checks to make from an FMMD hierarchy to RFMEA applied to
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all components in a system.
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Consider $k$ to be the number of components in a {\fg} (i.e. $k=|{\FG}|$),
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$f$ is the number of failure modes per component (i.e. $f=|fm(c)|$), and
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$L$ to be the number of levels in the hierarchy of an FMMD analysis.
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We can represent the number of failure scenarios to check in a (fixed parameter for $|{\FG}|$ and $|fm(c_i)|$) FMMD hierarchy
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with equation~\ref{eqn:anscen}.
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\begin{equation}
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\label{eqn:anscen}
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\sum_{n=0}^{L} {k}^{n}.k.f.(k-1)
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\end{equation}
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The thinking behind equation~\ref{eqn:anscen}, is that for each level of analysis -- counting down from the top --
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there are ${k}^{n}$ {\fgs} within each level; we need to apply RFMEA to each {\fg} on the level.
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The number of checks to make for RFMEA is number of components $k$ multiplied by the number of failure modes $f$
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checked against the remaining components in the {\fg} $(k-1)$.
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If, for the sake of example, we fix the number of components in a {\fg} to three and
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the number of failure modes per component to three, an FMMD hierarchy
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would look like figure~\ref{fig:three_tree}.
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\subsection{RFMEA FMMD Comparison Example}
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Using the diagram in figure~\ref{fig:three_tree}, we have three levels of analysis.
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Starting at the top, we have a {\fg} with three derived components, each of which has
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three failure modes.
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Thus the number of checks to make in the top level is $3^0.3.2.3=18$.
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On the level below that, we have three {\fgs} each with a
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an identical number of checks, $3^1.3.2.3=56$.%{\fg}
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On the level below that we have nine {\fgs}, $3^2.3.2.3=168$.
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Adding these together gives $242$ checks to make to perform FMMD (i.e. RFMEA {\em{within the}}
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{\fgs}).
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If we were to take the system represented in figure~\ref{fig:three_tree}, and
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apply RFMEA on it as a whole system, we can use equation~\ref{eqn:CC},
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$CC(G) = \sum_{n=1}^{|G|} |fm(c_n)|.(|G|-1)$, where $|G|$ is 27, $fm(c_n)$ is 3
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and $(|G|-1)$ is 26.
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This gives:
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$CC(G) = \sum_{n=1}^{27} |3|.(|27|-1) = 2106$.
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In order to get general equations with which to compare RFMEA with FMMD,
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we can re-write equation~\ref{eqn:CC} in terms of the number of levels
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in an FMMD hierarchy.
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%
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The number of components in the system, is number of components
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in a {\fg} raised to the power of the level plus one.
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Thus we re-write equation~\ref{eqn:CC} as:
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\begin{equation}
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\label{eqn:fmea_state_exp21}
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\sum_{n=1}^{k^{L+1}}.(k^{L+1}-1).f \; , % \\
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%(N^2 - N).f
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\end{equation}
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or
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\begin{equation}
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\label{eqn:fmea_state_exp22}
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k^{L+1}.(k^{L+1}-1).f \;. % \\
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%(N^2 - N).f
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\end{equation}
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We can now use equation~\ref{eqn:anscen} and \ref{eqn:fmea_state_exp22} to compare (for fixed sizes of $|G|$ and $|fm(c)|$)
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the two approaches, for the work required to perform rigorous checking.
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For instance, having four levels
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of FMMD analysis, with these fixed numbers,
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%(in addition to the top zeroth level)
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will require 81 base level components.
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$$
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%\begin{equation}
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\label{eqn:fmea_state_exp22}
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3^4.(3^4-1).3 = 81.(81-1).3 = 19440 % \\
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%(N^2 - N).f
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%\end{equation}
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$$
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$$
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%\begin{equation}
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% \label{eqn:anscen}
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\sum_{n=0}^{3} {3}^{n}.3.3.(2) = 720
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%\end{equation}
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$$
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% \subsection{Exponential squared to Exponential}
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%
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% can I say that ?
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\section{Problems in choosing membership of functional groups}
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\subsection{Side Effects: A Problem for FMMD analysis}
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A problem with modularising according to functionality is that we can have component failures that would
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intuitively be associated with one {\fg} that may cause unintended side effects in other
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{\fgs}.
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For instance were we to have a component that on failing $SHORT$ could bring down
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a voltage supply rail, this could have drastic consequences for other
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functional groups in the system we are examining.
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\pagebreak[3]
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\subsubsection{Example de-coupling capacitors in logic circuits}
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A good example of this, are de-coupling capacitors, often used
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over the power supply pins of all chips in a digital logic circuit.
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Were any of these capacitors to fail $SHORT$, they could bring down
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the supply voltage to the other logic chips.
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To a power-supply, shorted capacitors on the supply rails
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are a potential source of the symptom, $SUPPLY\_SHORT$.
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In a logic chip/digital circuit {\fg} open capacitors are a potential
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source of symptoms caused by the failure mode $INTERFERENCE$.
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So we have a `symptom' of the power-supply, and a `failure~mode' of
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the logic chip to consider.
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A possible solution to this is to include the de-coupling capacitors
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in the power-supply {\fg}.
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% decision, could they be included in both places ????
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% I think so
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Because the capacitor has two potential failure modes (EN298),
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this raises another issue for FMMD. A de-coupling capacitor going $OPEN$ might not be considered relevant to
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a power-supply module (but there might be additional noise on its output rails).
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But in {\fg} terms the power supply, now has a new symptom that of $INTERFERENCE$.
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Some logic chips are more susceptible to $INTERFERENCE$ than others.
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A logic chip with de-coupling capacitor failing, may operate correctly
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but interfere with other chips in the circuit.
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There is no reason why the de-coupling capacitors could not be included {\em in the {\fg} they would intuitively be associated with as well}.
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This allows for the general principle of a component failure affecting more than one {\fg} in a circuit.
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This allows functional groups to share components where necessary.
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This does not break the modularity of the FMMD technique, because, as {\irl},
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one component failure may affect more than one sub-system.
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It does uncover a weakness in the FMMD methodology though.
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It could be very easy to miss the side effect and include
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the component causing the side effect into the wrong {\fg}, or only one germane {\fg}.
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\section{Critiques}
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\section{Evaluation}
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