\section{Copy dot tex} \subsection{An algebraic notation for identifying FMMD enitities} Consider all `components' to exist as members of a set $\mathcal{C}$. % Each component $c$ has an associated set of failure modes. We can define a function $fm$ that returns a set of failure modes $F$, for the component $c$. Let the set of all possible components be $\mathcal{C}$ and let the set of all possible failure modes be $\mathcal{F}$. We now define the function $fm$ as \begin{equation} \label{eqn:fm} fm : \mathcal{C} \rightarrow \mathcal{P}\mathcal{F}. \end{equation} This is defined by, where $c$ is a component and $F$ is a set of failure modes, $ fm ( c ) = F. $ We can use the variable name $\FG$ to represent a {\fg}. A {\fg} is a collection of components. %We thus define $FG$ as a set of chosen components defining %a {\fg}; all functional groups We can state that {\FG} is a member of the power set of all components, $ \FG \in \mathcal{P} \mathcal{C}. $ We can overload the $fm$ function for a functional group {\FG} where it will return all the failure modes of the components in {\FG} given by $$ fm ({\FG}) = F. $$ Generally, where $\mathcal{{\FG}}$ is the set of all functional groups, \begin{equation} fm : \mathcal{{\FG}} \rightarrow \mathcal{P}\mathcal{F}. \end{equation} %$$ \mathcal{fm}(C) \rightarrow S $$ %$$ {fm}(C) \rightarrow S $$ \paragraph{Abstraction Levels of {\fgs} and {\dcs}} \label{sec:indexsub} We can indicate the abstraction level of a component by using a superscript. Thus for the component $c$, where it is a `base component' we can assign it the abstraction level zero, $c^0$. Should we wish to index the components (for example as in a product parts-list) we can use a sub-script. Our base component (if first in the parts-list) could now be uniquely identified as $c^0_1$. We can further define the abstraction level of a {\fg}. We can say that it is the maximum abstraction level of any of its components. Thus a functional group containing only base components would have an abstraction level zero and could be represented with a superscript of zero thus `${\FG}^0$'. % The functional group set may also be indexed. We can apply symptom abstraction to a {\fg} to find its symptoms. %We are interested in the failure modes %of all the components in the {\fg}. An analysis process We define the symptom abstraction process with the symbol `$\bowtie$'.% is applied to the {\fg}. % The $\bowtie$ function takes a {\fg} as an argument and returns a newly created {\dc}. % %The $\bowtie$ analysis, a symptom extraction process, is described in chapter \ref{chap:sympex}. The symptom abstraction process must always raise the abstraction level for the newly created {\dc}. Using $\abslevel$ to symbolise the fault abstraction level, we can now state: $$ \bowtie({\FG}^{\abslevel}) \rightarrow c^{{\abslevel}+N} | N \ge 1. $$ \paragraph{Functional Groups may be indexed} We will typically have more than one {\fg} on each level of FMMD hierarchy ( expect the top level where there will only be one) we could index the {\fgs} with a sub-script, and can then uniquely identify them using their level and their index. For example ${\FG}^{3}_{2}$ would be the second {\fg} at the third level of abstraction in an FMMD hierarchy. \paragraph{The symptom abstraction process in outline.} The $\bowtie$ function processes each component in the {\fg} and extracts all the component failure modes. With all the failure modes, an analyst can determine how each failure mode will affect the {\fg}, and then collect common symptoms. A new {\dc} is created where its failure modes, are the symptoms from {\fg}. Note that the component must have a higher abstraction level than the {\fg} it was derived from. \paragraph{Surjective constraint applied to symptom collection.} We can stipulate that symptom collection process is surjective. % i.e. $ \forall f in F $ By stipulating surjection for symptom collection, we ensure that each component failure mode maps to at least one symptom. We also ensure that all symptoms have at least one component failure mode (i.e. one or more failure modes that caused it). % \subsection{FMMD Hierarchy} By applying stages of analysis to higher and higher abstraction levels, we can converge to a complete failure mode model of the system under analysis. Because the symptom abstraction process is defined as surjective (from component failure modes to symptoms) the number of symptoms is guaranteed to be less than or equal to the number of component failure modes. In practise however, the number of symptoms greatly reduces as we traverse up the hierarchy. This is a natural process. When we have complicated systems they always have a small number of system failure modes in comparison to the number of failure modes in its sub-systems/components.. \section{Examples of Derived Component like concepts in safety literature} Idea stage on this section, integrated circuits and some compond parts (like digital resistors) are treated like base components. i.e. this sets a precedent for {\dcs}. \begin{itemize} \item Look at OPAMP circuits, pick one (say $\mu$741) \item Digital transistor perhaps, inside two resistors and a transistor. \item outline a proposed FMMD analysis \item Show FMD-91 OPAMP failure modes -- compare with FMMD \end{itemize} The gas burner standard (EN298~\cite{en298}), only considers OPEN and SHORT for resistors (and for some types of resistors OPEN only). FMD-91~\cite{fmd91}(the US military failure modes guide) also includes `parameter change' in its description of resistor failure modes. Now a resistor will generally only suffer parameter change when over stressed. EN298 stipulates down rating by 60\% to maximum stress possible in a circuit. So even if you have a resistor that preliminary tells you would never be subjected to say more than 5V, but there is say, a 24V rail on the circuit, you have to choose resistors able to cope with the 24V stress/load and then down rate by 60\%. That is to say the resitor should be rated for a maximum voltage of $ > 38.4V$ and should be rated 60\% higher for its power consumption at $38.4V$. Because of down-rating, it is reasonable to not have to consider parameter change under EN298 approvals. \clearpage Two areas that cannot be automated. Choosing {\fgs} and the analysis/symptom collection process itself. \subsection{{\fgs} Sharing components and Hierarchy} With electronics we need to follow the signal path to make sense of failure modes effects on other parts of the circuit further down that path. %{\fgs} will naturally have to be in the position of starter A power-supply is naturally first in a signal path (or failure reasoning path). That is to say, if the power-supply is faulty, its failure modes are likely to affect the {\fgs} that have to use it. This means that most electronic components should be placed higher in an FMMD hierarchy than the power-supply. A shorted de-coupling capactitor caused a `symptom' of the power-supply, and an open de-coupling capactitor should be considered a `failure~mode' relevant to the logic chip. % to consider. If components can be shared between functional groups, this means that components must be shareable between {\fgs} at different levels in the FMMD hierarchy. This hierarchy and an optionally shared de-coupling capacitor (with line highlighted in red and dashed) are shown in figure~\ref{fig:shared_component}. \begin{figure} \centering \includegraphics[width=250pt,keepaspectratio=true]{CH5_Examples/shared_component.png} % shared_component.png: 729x670 pixel, 72dpi, 25.72x23.64 cm, bb=0 0 729 670 \caption{Optionally shared Component} \label{fig:shared_component} \end{figure} \subsection{Hierarchy and structure} By having this structure, the logic circuit element, can accept failure modes from the power-supply (for instance these might, for the sake of example include: $NO\_POWER$, $LOW\_VOLTAGE$, $HIGH\_VOLTAGE$, $NOISE\_HF$, $NOISE\_LF$. Our logic circuit may be able to cope with $LOW\_VOLTAGE$ and $NOISE\_LF$, but react with a serious symptom to $NOISE\_HF$ say. But in order to process these failure modes it must be at a higher stage in the FMMD hierarchy. \pagebreak[4] \section{Defining the concept of `comparison~complexity' in FMEA} % % DOMAIN == INPUTS % RANGE == OUTPUTS % When performing FMEA we have a system under investigation, which will comprise of a collection of components which have associated failure modes. The object of FMEA is to determine cause and effect: from the failure modes (the causes) to the effects (or symptoms of failure). % To perform FMEA rigorously we could stipulate that every failure mode must be checked for effects against all the components in the system. We could term this `rigorous~FMEA'~(RFMEA). The number of checks we have to make to achieve this gives an indication of the complexity of the task. % We could term this `comparison~complexity', as it is the number of paths between failure modes and components, necessary to achieve RFMEA, for a given system/functional~group. % (except its self of course, that component is already considered to be in a failed state!). % Obviously, for a small number of components and failure modes we have a smaller number of checks to make than for a complicated larger system. % We can consider the system as a large {\fg} of components. We represent the number of components in the {\fg} $G$, by $ | G | $ (an indexing and sub-scripting notation to identify particular {\fgs} within an FMMD hierarchy is given in section~\ref{sec:indexsub}). The function $fm$ has a component as its domain and the components failure modes as its range (see equation~\ref{eqn:fm}). We can represent the number of potential failure modes of a component $c$, to be $ | fm(c) | .$ If we index all the components in the system under investigation $ c_1, c_2 \ldots c_{|\FG|} $ we can express the number of checks required to rigorously examine every failure mode against all the other components in the system. We can define this as a function, Comparison Complexity, $CC$, with its domain as the system or {\fg}, $\FG$, and its range as the number of checks to perform to satisfy a rigorous FMEA inspection. Where $\mathcal{\FG}$ represents the set of all {\fgs}, and $ \mathbb{N} $ any natural integer, $CC$ is defined by, \begin{equation} %$$ CC:\mathcal{\FG} \rightarrow \mathbb{N}, %$$ \end{equation} and, where n is the number of components in the system/{\fg}, $|fm(c_i)|$ is the number of failure modes in component ${c_i}$, is given by \begin{equation} \label{eqn:CC} %$$ %%% when it was called reasoning distance -- 19NOV2011 -- RD(fg) = \sum_{n=1}^{|fg|} |fm(c_n)|.(|fg|-1) CC(\FG) = (n-1) \sum_{1 \le i \le n} fm(c_i). %$$ \end{equation} 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)|}$); equation~\ref{eqn:CC} becomes %$$ \begin{equation} \label{eqn:rd2} CC(\FG) = K.(|\FG|-1). \end{equation} %$$ %Equation~\ref{eqn:rd} can also be expressed as % % \begin{equation} % \label{eqn:rd2} % %$$ % CC(G) = {|G|}.{|fm(c_n)|}.{(|fg|-1)} . % %$$ % \end{equation} \subsection{A general formula for counting Comparison Complexity in an FMMD hierarchy} An FMMD Hierarchy will have reducing numbers of functional groups as we progress up the hierarchy. In order to calculate its comparison~complexity we need to apply equation~\ref{eqn:CC} to all {\fgs} on each level. 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), defined by \begin{equation} %$$ g(H, i) \rightarrow \forall {\FG}^{\xi} \;where\; ({\xi} = {i}) \wedge ({\FG}^{\xi} \in H) . %$$ \end{equation} Where $L$ represents the number of levels in the FMMD hierarchy, $|g(\xi)|$ represents the number of functional groups on the level and $H$ represents an FMMD hierarchy, we overload the comparison complexity thus: %$$ \begin{equation} \label{eqn:gf} CC(H) = \sum_{\xi=0}^{L} \sum_{j=1}^{|g(H,\xi)|} CC({\FG}_{j}^{\xi}). %$$ \end{equation} \pagebreak[4] \subsection{Complexity Comparison Examples} The potential divider discussed in section~\ref{potdivfmmd} has four failure modes and two components and therefore has $CC$ of 4. $$CC(potdiv) = \sum_{n=1}^{2} |2|.(|1|) = 4 $$ Even considering a $fictitious$ system with just 81 components (with these components having 3 failure modes each) we would have an $CC$ of $$CC(fictitious) = \sum_{n=1}^{81} |3|.(|80|) = 19440 .$$ Ensuring all component failure modes are checked against all other components in a system -- applying FMEA rigorously -- could be termed Rigorous FMEA (RFMEA). The computational order for RFMEA would be polynomial ($O(N^2.K)$) (where $K$ is the variable number of failure modes). This order may be acceptable in a computational environment: However, the choosing of {\fgs} and the analysis process are by-hand/human activities. It can be seen that it is practically impossible to achieve RFMEA for anything but trivial systems. % % Next statement needs alot of justification % It is the authors belief that FMMD reduces the comparison complexity enough to make rigorous checking feasible. \pagebreak[4] %\subsection{Using the concept of Complexity Comparison to compare RFMEA with FMMD} \begin{figure} \centering \includegraphics[width=400pt,keepaspectratio=true]{CH5_Examples/three_tree.png} % three_tree.png: 851x385 pixel, 72dpi, 30.02x13.58 cm, bb=0 0 851 385 \caption{FMMD Hierarchy with number of components in {\fg} fixed to 3 $(|G| = 3)$ } % \wedge (|fm(c)| = 3)$} \label{fig:three_tree} \end{figure} \subsection{Comparing FMMD and RFMEA comparison complexity} Because components have variable numbers of failure modes, and {\fgs} have variable numbers of components it is difficult to use the general formula for comparing the number of checks to make for RFMEA and FMMD. If we were to create an example by fixing the number of components in a {\fg} and the number of failure modes per component, we can derive formulae to compare the number of checks to make from an FMMD hierarchy to RFMEA applied to all components in a system. Consider $k$ to be the number of components in a {\fg} (i.e. $k=|{\FG}|$), $f$ is the number of failure modes per component (i.e. $f=|fm(c)|$), and $L$ to be the number of levels in the hierarchy of an FMMD analysis. We can represent the number of failure scenarios to check in a (fixed parameter for $|{\FG}|$ and $|fm(c_i)|$) FMMD hierarchy with equation~\ref{eqn:anscen}. \begin{equation} \label{eqn:anscen} \sum_{n=0}^{L} {k}^{n}.k.f.(k-1) \end{equation} The thinking behind equation~\ref{eqn:anscen}, is that for each level of analysis -- counting down from the top -- there are ${k}^{n}$ {\fgs} within each level; we need to apply RFMEA to each {\fg} on the level. The number of checks to make for RFMEA is number of components $k$ multiplied by the number of failure modes $f$ checked against the remaining components in the {\fg} $(k-1)$. If, for the sake of example we fix the number of components in a {\fg} to three and the number of failure modes per component to three, an FMMD hierarchy would look like figure~\ref{fig:three_tree}. \subsection{Worked Example} Using the diagram in figure~\ref{fig:three_tree}, we have three levels of analysis. Starting at the top, we have a {\fg} with three derived components, each of which has three failure modes. Thus the number of checks to make in the top level is $3^0.3.2.3=18$. On the level below that, we have three {\fgs} each with a an identical number of checks, $3^1.3.2.3=56$.%{\fg} On the level below that we have nine {\fgs}, $3^2.3.2.3=168$. Adding these together gives $242$ checks to make to perform FMMD (i.e. RFMEA {\em{within the}} {\fgs}). If we were to take the system represented in figure~\ref{fig:three_tree}, and apply RFMEA on it as a whole system, we can use equation~\ref{eqn:CC}, $CC(G) = \sum_{n=1}^{|G|} |fm(c_n)|.(|G|-1)$, where $|G|$ is 27, $fm(c_n)$ is 3 and $(|G|-1)$ is 26. This gives: $CC(G) = \sum_{n=1}^{27} |3|.(|27|-1) = 2106$. In order to get general equations with which to compare RFMEA with FMMD we can re-write equation~\ref{eqn:CC} in terms of the number of levels in an FMMD hierarchy. % The number of components in the system, is number of components in a {\fg} raised to the power of the level plus one. Thus we re-write equation~\ref{eqn:CC} as: \begin{equation} \label{eqn:fmea_state_exp21} \sum_{n=1}^{k^{L+1}}.(k^{L+1}-1).f \; , % \\ %(N^2 - N).f \end{equation} or \begin{equation} \label{eqn:fmea_state_exp22} k^{L+1}.(k^{L+1}-1).f \;. % \\ %(N^2 - N).f \end{equation} We can now use equation~\ref{eqn:anscen} and \ref{eqn:fmea_state_exp22} to compare (for fixed sizes of $|G|$ and $|fm(c)|$) the two approaches, for the work required to perform rigorous checking. For instance, having four levels of FMMD analysis, with these fixed numbers, %(in addition to the top zeroth level) will require 81 base level components. $$ %\begin{equation} \label{eqn:fmea_state_exp22} 3^4.(3^4-1).3 = 81.(81-1).3 = 19440 % \\ %(N^2 - N).f %\end{equation} $$ $$ %\begin{equation} % \label{eqn:anscen} \sum_{n=0}^{3} {3}^{n}.3.3.(2) = 720 %\end{equation} $$ % \subsection{Exponential squared to Exponential} % % can I say that ? \section{Problems in choosing membership of functional groups} \subsection{Side Effects: A Problem for FMMD analysis} A problem with modularising according to functionality is that we can have component failures that would intuitively be associated with one {\fg} that may cause unintended side effects in other {\fgs}. For instance were we to have a component that on failing $SHORT$ could bring down a voltage supply rail, this could have drastic consequences for other functional groups in the system we are examining. \pagebreak[3] \subsubsection{Example de-coupling capacitors in logic circuits} A good example of this, are de-coupling capacitors, often used over the power supply pins of all chips in a digital logic circuit. Were any of these capacitors to fail $SHORT$ they could bring down the supply voltage to the other logic chips. To a power-supply, shorted capacitors on the supply rails are a potential source of the symptom, $SUPPLY\_SHORT$. In a logic chip/digital circuit {\fg} open capacitors are a potential source of symptoms caused by the failure mode $INTERFERENCE$. So we have a `symptom' of the power-supply, and a `failure~mode' of the logic chip to consider. A possible solution to this is to include the de-coupling capacitors in the power-supply {\fg}. % decision, could they be included in both places ???? % I think so Because the capacitor has two potential failure modes (EN298) this raises another issue for FMMD. A de-coupling capacitor going $OPEN$ might not be considered relevant to a power-supply module (but there might be additional noise on its output rails). But in {\fg} terms the power supply, now has a new symptom that of $INTERFERENCE$. Some logic chips are more susceptible to $INTERFERENCE$ than others. A logic chip with de-coupling capacitor failing, may operate correctly but interfere with other chips in the circuit. 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}. This allows for the general principle of a component failure affecting more than one {\fg} in a circuit. This allows functional groups to share components where necessary. This does not break the modularity of the FMMD technique, because, as {\irl} one component failure may affect more than one sub-system. It does uncover a weakness in the FMMD methodology though. It could be very easy to miss the side effect and include the component causing the side effect into the wrong {\fg}, or only one germane {\fg}. \section{Double Simultaneous Failures} The probability for independent double simultaneous component failures (because we would multiply the probabilities of failure) is very low. However, some critical systems have to consider these type of eventualities. The burner control industry has to consider double failures, as specified in European Norm EN298~\cite{en298}. EN298 does not specifically state that double simultaneous failures must be considered. What it does say is that in the event of a lockout---a condition where an error has been detected and the equipment moves to a safe non-functioning state---no secondary failure may cause a dangerous condition. % This is slightly vague: there are so many possible component failures that could cause a secondary failure, that it is very difficult not to interpret this as meaning we have to cater for double simultaneous failures for the most critical sections of a burner control system. % In practise---in the field of EN298: burner controllers---this means triple safeguards to ensure the fuel is not allowed to flow under an error condition. This would of course leave the possibility of other more complex double failures tricking the controller into thinking the combustion was actually safe when it was not. % It would be impractical to perform the number of checks (as the checking is time-consuming human process) required of RFMEA on a system as complex as a burner controller. It has been shown that, for all but trivial small systems, double failure mode checking is impossible from a practical perspective. FMMD can reduce the number of checks to make to achieve double simultaneous failure checking -- but by the very nature of choosing {\fgs} we will not (in the initial stages) be cross checking all possible combinations of double failures in all the components. The diagram in figure~\ref{fig:dubsim1}, uses Euler diagrams to model failure modes (as closed contours) and asterisks to model failure mode scenarios. The failure scenario is defined by the contours that enclose it. Consider a system which has four components $c_1 \ldots c_4$. Consider that each of these components may fail in two ways: $a$ and $b$, i.e $fm(c_1) = fm(c_2) = \{a,b\}$. Now consider two {\fgs}, $fg1 = \{ c_1, c_2 \}$ and $fg2 = \{ c_3, c_4 \}$. We list all the possible failure scenarios as $FS1 \ldots FS6$ for each functional group. For instance $FS5$ is the result of component $c_2$ failing with failure mode $a$ and component $c_1$ failing with failure mode $b$. We can express this as $c_2 a \cup c_1 b$. \begin{figure}[h] \centering \includegraphics[width=300pt,keepaspectratio=true]{CH5_Examples/dubsim1.png} % dubsim1.png: 612x330 pixel, 72dpi, 21.59x11.64 cm, bb=0 0 612 330 \caption{Simultaneous Failure Mode Scenarios} \label{fig:dubsim1} \end{figure} From figure~\ref{fig:dubsim1} we can see that the double failure modes within the {\fgs} have been examined. How do we model the double failures that occur across the {\fgs}, for instance $c_4 a \cup c_1 a$. It could be argued that because functional groups are chosen for their functionality, and re-usability that component failures in one should not affect a different {\fg}, but this is a weak argument. Merely double checking within {\fgs} would be marginally better than only applying it to the most obvious critical elements of a system. What is really required is a way that all double simultaneous failures are checked. One way of doing this is to apply double failure mode checking to all {\fgs} higher up in the hierarchy. This guarantees to check the symptoms caused by the failure modes in the other {\fgs} with the symptoms derived from the other {\fgs} modelling for double failures. % By traversing down the tree we can automatically determine which double simultaneous combinations have not been resolved. % By applying double simultaneous checking until no single failures canlead to a top level event, we double failure move coverage. To extend the example in figure~\ref{fig:dubsim1} we can map the failure scenarios. For Functional Group 1 (FG1), let us map: \begin{eqnarray*} FS1 & \mapsto & S1 \\ FS2 & \mapsto & S3 \\ FS3 & \mapsto & S1 \\ FS4 & \mapsto & S2 \\ FS5 & \mapsto & S2 \\ FS6 & \mapsto & S3 \end{eqnarray*} Thus a derived component, DC1, has the failure modes defined by $fm(DC1) = \{ S1, S2, S3 \}$. For Functional Group 2 (FG2), let us map: \begin{eqnarray*} FS1 & \mapsto & S4 \\ FS2 & \mapsto & S5 \\ FS3 & \mapsto & S5 \\ FS4 & \mapsto & S4 \\ FS5 & \mapsto & S6 \\ FS6 & \mapsto & S5 \end{eqnarray*} %This AUTOMATIC check can reveal WHEN double checking no longer necessary %in the hierarchy to cover dub sum !!!!! YESSSS sample text sample text sample text sample text sample text sample text sample text sample text sample text sample text sample text sample text sample text sample text sample text sample text sample text sample text sample text sample text sample text sample text sample text sample text