J. Howse comments -> changes
From meeting on 19NOV2010
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@ -30,7 +30,15 @@ Mathematical constraints and definitions are made using set theory.
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\section{Introduction}
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This chapter describes the data types and concepts for the Failure Mode Modular De-composition (FMMD) method.
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This
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\ifthenelse {\boolean{paper}}
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{
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paper
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}
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{
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chapter
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}
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describes the data types and concepts for the Failure Mode Modular De-composition (FMMD) method.
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When analysing a safety critical system using
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this methodology, we need clearly defined failure modes for
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all the components that are used to model the system.
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@ -43,7 +51,7 @@ build hierarchical bottom-up models of failure mode behaviour.
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%When building a system from components,
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%we should be able to find all known failure modes for each component.
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%For most common electrical and mechanical components, the failure modes
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%for a given type of part can be obtained from standard literature\cite{mil1991}
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%for a given type of part can be obtained from standard literature~\cite{mil1991}
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%\cite{mech}. %The failure modes for a given component $K$ form a set $F$.
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@ -62,8 +70,9 @@ build hierarchical bottom-up models of failure mode behaviour.
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\label{fig:component}
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\end{figure}
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Let us first define a component. This is anything with which we use to build a
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product or system.
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Let us first define a component.
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%This is anything with which we use to build a product or system.
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This is anything we use to build a product or system.
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It could be something quite complicated
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like an integrated microcontroller, or quite simple like the humble resistor.
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We can define a
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@ -72,7 +81,7 @@ a vendors' reference number.
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What these components all have in common is that they can fail, and fail in
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a number of well defined ways. For common components
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there is established literature for the failure modes for the system designer to consider (often with accompanying statistical
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failure rates)\cite{mil1991}. For instance, a simple resistor is generally considered
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failure rates)~\cite{mil1991}. For instance, a simple resistor is generally considered
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to fail in two ways, it can go open circuit or it can short.
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Thus we can associate a set of faults to this component $ResistorFaultModes=\{OPEN, SHORT\}$.
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The UML diagram in figure
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@ -96,7 +105,7 @@ A product naturally consists of many components and these are traditionally
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kept in a `parts list'. For a safety critical product this is usually a formal document
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and is used by quality inspectors to ensure the correct parts are being fitted.
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The parts list is shown for
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completeness here, as people involved with PCB and electronics production, verification
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completeness here, as people involved with Printed Circuit Board (PCB) and electronics production, verification
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and testing would want to know where it lies in the model.
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The parts list is not actively used in the FMMD method.
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For the UML diagram in figure \ref{fig:componentpl} the parts list is simply a collection of components.
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@ -119,7 +128,7 @@ we are concerned with here.}, and will
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not require a vendor reference, but must be named locally in the FMMD model.
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We can term `modularising a system', to mean recursively breaking it into smaller sections for analysis.
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When modularising a system from the top~down, as in Fault Tree Analysis\cite{nasafta}\cite{nucfta} (FTA)
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When modularising a system from the top~down, as in Fault Tree Analysis~\cite{nasafta}\cite{nucfta} (FTA),
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it is common to term the modules identified as sub-systems.
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When building from the bottom up, it is more meaningful to call them `derived~components'.
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@ -128,23 +137,23 @@ When building from the bottom up, it is more meaningful to call them `derived~co
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%% Paragraph using failure modes to build from bottom up
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%%
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\section{Fault Mode Analysis, \\ top down or bottom up?}
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\section{Fault Mode Analysis, top down or bottom up?}
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Traditional static fault analysis methods work from the top down.
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They identify faults that can occur in a system, and then work down
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to see how they could be caused. Some apply statistical techniques to
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determine the likelihood of component failures
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causing specific system level errors. For example, Bayes theorem \ref{bayes}, the relation between a conditional probability and its inverse,
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causing specific system level errors. For example, Bayes theorem \ref{bayes}, the relation between a conditional probability and its reverse,
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can be applied to specific failure modes in components and the probability of them causing given system level errors.
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Another top down methodology is to apply cost benefit analysis
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to determine which faults are the highest priority to fix\cite{bfmea}.
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to determine which faults are the highest priority to fix~\cite{bfmea}.
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The aim of FMMD analysis is to produce complete failure
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models of safety critical systems from the bottom-up,
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starting, where possible with known base~component failure~modes.
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An advantage of working from the bottom up is that we can ensure that
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all component failure modes must be considered. A top down approach
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can miss individual failure modes of components\cite{faa}[Ch.~9],
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can miss individual failure modes of components~\cite{faa}[Ch.~9],
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especially where they are non obvious top-level faults.
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In order to analyse from the bottom-up, we need to take
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@ -161,8 +170,12 @@ and from this determine the failure modes of all the components that belong to i
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% expand 21sep2010
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%The `{\fg}' as used by the analyst is a collection of component failures modes.
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The analysts interest is the ways in which the components within the {\fg}
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can fail. All the failure modes of all the components with an {\fg} are collected
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into a flat set of failure modes.
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can fail. All the failure modes of all the components within an {\fg} are collected.
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As each component mode holds a set of failure modes, these set of sets of failure modes
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is converted into
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into a flat set
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of failure modes
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(i.e. a set containg just containg failure modes not sets of failure mosdes).
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%
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Each of these failure modes, and optionally combinations of them, are
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formed into `test cases' which are
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@ -180,12 +193,19 @@ with its own set of failure modes.
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The process for taking a {\fg}, considering
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all the failure modes of all the components in the group,
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and analysing it is called `symptom abstraction' and
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and analysing it is called `symptom abstraction'.
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\ifthenelse {\boolean{paper}}
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{
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}
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{
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This
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is dealt with in detail in chapter \ref{symptom_abstraction}.
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}
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% define difference between a \fg and a \dc
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A {\fg} is a collection of components, a {\dc} is a new `theorectical'
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component which has a set of failure modes, which
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correspond to the failure modes of the {\fg} is was derived from.
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correspond to the failure modes of the {\fg} it was derived from.
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We could consider a {\fg} as a black box, or component
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to use, and in this case it would have a set of failure modes.
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Looking at the {\fg} in this way is seeing it as a {\dc}.
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@ -206,13 +226,13 @@ these `derived~failure~modes'.
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We thus have a `new' component, or system building block, but with a known and traceable
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fault behaviour.
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The UML representation shows a `functional group' having a one to one relationship with a derived~component,
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which we represent in the UML diagram in figure \ref{fig:cfg}.
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The UML representation (in figure \ref{fig:cfg}) shows a `functional group' having a one to one relationship with a derived~component.
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The symbol $\bowtie$ is used to indicate the analysis process that takes a
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functional group and converts it into a new component.
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This can be expresed as $ \bowtie ( FG ) \rightarrow DerivedComponent $ .
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with $\mathcal{FG}$ represeting the set of all functional groups, and $\mathcal{DC}$ the set of all derived components,
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this can be expresed as $ \bowtie : \mathcal{FG} \rightarrow \mathcal{DC} $ .
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\begin{figure}[h]
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@ -224,7 +244,7 @@ This can be expresed as $ \bowtie ( FG ) \rightarrow DerivedComponent $ .
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\end{figure}
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\subsection{Keeping track of the derived \\ components position in the hierarchy}
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\subsection{Keeping track of the derived components position in the hierarchy}
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The UML meta model in figure \ref{fig:cfg}, shows the relationships
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between the classes and sub-classes.
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@ -306,7 +326,7 @@ fm : \mathcal{FG} \rightarrow \mathcal{F}
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\end{equation}
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\section{Unitary State Component \\ Failure Mode sets}
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\section{Unitary State Component Failure Mode sets}
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\paragraph{Design Descision/Constraint}
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An important factor in defining a set of failure modes is that they
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@ -325,7 +345,7 @@ within one package.
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This property, failure modes being mutually exclusive, is termed `unitary state failure modes'
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in this study.
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This corresponds to the `mutually exclusive' definition in
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probability theory \cite{probstat}.
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probability theory~\cite{probstat}.
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\begin{definition}
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@ -342,7 +362,7 @@ the component failure modes in each of its members are unitary~state.
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Thus if the failure modes of a component $F$ are unitary~state, we can say $F \in \mathcal{U}$ is true.
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\end{definition}
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\section{Component failure modes:\\ Unitary State example}
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\section{Component failure modes: Unitary State example}
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An example of a component with an obvious set of ``unitary~state'' failure modes is the electrical resistor.
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@ -397,7 +417,7 @@ with several modules that could all fail simultaneously, a process
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of reduction into smaller theoretical components will have to be made
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\footnote{A modern microcontroller will typically have several modules, which are configured to operate on
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pre-assigned pins on the device. Typically voltage inputs (\adcten / \adctw), digital input and outputs,
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PWM (pulse width modulation), UARTs and other modules will be found on simple cheap microcontrollers \cite{pic18f2523}}.
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PWM (pulse width modulation), UARTs and other modules will be found on simple cheap microcontrollers~\cite{pic18f2523}}.
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For instance the voltage reading functions which consist
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of an ADC multiplexer and ADC can be considered to be components
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inside the microcontroller package.
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@ -410,14 +430,14 @@ in a {\fg} impractical due to the sheer size of the task.
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%%- Need some refs here because that is the way gastec treat the ADC on microcontroller on the servos
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\section{Handling Simultaneous \\ Component Faults}
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\section{Handling Simultaneous Component Faults}
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For some integrity levels of static analysis, there is a need to consider not only single
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failure modes in isolation, but cases where more then one failure mode may occur
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simultaneously.
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Note that the `unitary state' conditions apply to failure modes within a component.
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The scenarios presented here are where two or more components fail simultaneously.
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It is an implied requirement of EN298 \cite{en298} for instance to
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It is an implied requirement of EN298~\cite{en298} for instance to
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consider double simultaneous faults\footnote{This is under the conditions
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of LOCKOUT in an industrial burner controller that has detected one fault already.
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However, from the perspective of static failure mode analysis, this amounts
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@ -460,7 +480,7 @@ $$ \mathcal{P}_{1} S = \{ \{a\},\{b\},\{c\} \} $$
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A $k$ combination is a subset with $k$ elements.
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The number of $k$ combinations (each of size $k$) from a set $S$
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with $n$ elements (size $n$) is the binomial coefficient \cite{probstat} shown in equation \ref{bico}.
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with $n$ elements (size $n$) is the binomial coefficient~\cite{probstat} shown in equation \ref{bico}.
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\begin{equation}
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C^n_k = {n \choose k} = \frac{n!}{k!(n-k)!}
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@ -485,7 +505,7 @@ from $1$ to $cc$ thus
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\subsection{Actual Number of combinations to check \\ with Unitary State Fault mode sets}
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\subsection{Actual Number of combinations to check with Unitary State Fault mode sets}
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If all of the fault modes in $S$ were independent,
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the cardinality constrained powerset
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@ -502,7 +522,7 @@ For example, say
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the cardinality constraint was 3, we would need to subtract both
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$|{n \choose 2}|$ and $|{n \choose 3}|$ for each component in the functional~group.
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\subsubsection{Example: Two Component functional group \\ cardinality Constraint of 2}
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\subsubsection{Example: Two Component functional group cardinality Constraint of 2}
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For example: suppose we have a simple functional group with two components R and T, of which
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$$fm(R) = \{R_o, R_s\}$$ and $$fm(T) = \{T_o, T_s, T_h\}$$.
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@ -545,7 +565,7 @@ $$
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\pagebreak[1]
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\subsubsection{Establishing Formulae for unitary state failure mode \\
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\subsubsection{Establishing Formulae for unitary state failure mode
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cardinality calculation}
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The cardinality constrained powerset in equation \ref{eqn:ccps}, can be modified for % corrected for
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@ -636,7 +656,7 @@ A recursive algorithm and proof is described in appendix \ref{chap:vennccps}.
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%%
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\pagebreak[1]
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\section{Component Failure Modes \\ and Statistical Sample Space}
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\section{Component Failure Modes and Statistical Sample Space}
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%\paragraph{NOT WRITTEN YET PLEASE IGNORE}
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A sample space is defined as the set of all possible outcomes.
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For a component in FMMD analysis, this set of all possible outcomes is its normal correct
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@ -656,7 +676,7 @@ $$ F = \Omega(C) \backslash \{OK\} $$
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The $OK$ statistical case is the largest in probability, and is therefore
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of interest when analysing systems from a statistical perspective.
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This is of interest for the application of conditional probability calculations
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such as Bayes theorem \cite{probstat}.
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such as Bayes theorem~\cite{probstat}.
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%%-
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@ -4,6 +4,7 @@
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\usepackage{fancyhdr}
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\usepackage{tikz}
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\usepackage{amsfonts,amsmath,amsthm}
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\usepackage{lastpage}
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\usepackage{ifthen}
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\newboolean{paper}
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\setboolean{paper}{true} % boolvar=true or false
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@ -14,13 +15,21 @@
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\begin{document}
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\pagestyle{fancy}
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\fancyhf{}
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%\renewcommand{\chaptermark}[1]{\markboth{ \emph{#1}}{}}
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\fancyhead[LO]{}
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\fancyhead[RE]{\leftmark}
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%\fancyfoot[LE,RO]{\thepage}
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\cfoot{Page \thepage\ of \pageref{LastPage}}
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\rfoot{\today}
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\lhead{Definitions, Components, Functional Groups and Unitary State Failure Mode Sets}
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%\outerhead{{\small\bf Definitions, Components, Functional Groups and Unitary State Failure Mode Sets}}
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%\innerfoot{{\small\bf R.P. Clark } }
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% numbers at outer edges
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\pagenumbering{arabic} % Arabic page numbers hereafter
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\author{R.P.Clark}
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\title{Definitions, Components, Functional Groups \\ and Unitary State Failure Mode Sets}
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\title{Definitions, Components, Functional Groups and Unitary State Failure Mode Sets}
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\maketitle
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\input{component_failure_modes_definition_paper}
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@ -29,3 +38,7 @@
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\today
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\end{document}
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\begin{document}
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