Sunday 25th April 2010 Edits
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\abstract{ This chapter defines what is meant by the terms
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\abstract{ This chapter defines what is meant by the terms
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components, component fault modes and `unitary~state' component fault modes.
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components, component fault modes and `unitary~state' component fault modes.
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The application of Bayes theorem in current methodologies, and
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%The application of Bayes theorem in current methodologies, and
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the suitability of the `null hypothesis' or `P' value statistical approach
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%the suitability of the `null hypothesis' or `P' value statistical approach
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are discussed.
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%are discussed.
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Data types and their relationships are described using UML.
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Mathematical constraints and definitions are made using set theory.
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Mathematical constraints and definitions are made using set theory.
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}
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}
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\section{Introduction}
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\section{Introduction}
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When analysing a safety critical system using the
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FMMD technique, 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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These failure modes have a constraint such that
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the compoent failure modes must be mutually exclusive.
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This and the definition of a component are
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described in this chapter.
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%When building a system from components,
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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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%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 most common electrical and mechanical components, the failure modes
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@ -21,7 +29,7 @@ Mathematical constraints and definitions are made using set theory.
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%% Paragraph component and its relationship to its failure modes
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%% Paragraph component and its relationship to its failure modes
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%%
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%%
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\subsection{ What is a Component ?}
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\section{ What is a Component ?}
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Let us first define a component. This is anything we use to build a
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Let us first define a component. This is anything we use to build a
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@ -42,7 +50,7 @@ structure with its failure modes.
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\begin{figure}[h]
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\begin{figure}[h]
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\centering
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\centering
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\includegraphics[width=400pt,bb=0 0 437 141,keepaspectratio=true]{./component.jpg}
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\includegraphics[width=400pt,bb=0 0 437 141,keepaspectratio=true]{component_failure_modes_definition/component.jpg}
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% component.jpg: 437x141 pixel, 72dpi, 15.42x4.97 cm, bb=0 0 437 141
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% component.jpg: 437x141 pixel, 72dpi, 15.42x4.97 cm, bb=0 0 437 141
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\caption{A Component and its Failure Modes}
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\caption{A Component and its Failure Modes}
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\label{fig:component}
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\label{fig:component}
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@ -63,7 +71,7 @@ For our UML diagram the parts list is simply a collection of components
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as shown in figure \ref{fig:componentpl}.
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as shown in figure \ref{fig:componentpl}.
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\begin{figure}[h]
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\begin{figure}[h]
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\centering
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\centering
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\includegraphics[width=400pt,bb=0 0 712 68,keepaspectratio=true]{./componentpl.jpg}
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\includegraphics[width=400pt,bb=0 0 712 68,keepaspectratio=true]{component_failure_modes_definition/componentpl.jpg}
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% componentpl.jpg: 712x68 pixel, 72dpi, 25.12x2.40 cm, bb=0 0 712 68
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% componentpl.jpg: 712x68 pixel, 72dpi, 25.12x2.40 cm, bb=0 0 712 68
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\caption{Parts List of Components}
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\caption{Parts List of Components}
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\label{fig:componentpl}
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\label{fig:componentpl}
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@ -76,7 +84,7 @@ as shown in figure \ref{fig:componentpl}.
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%% Paragraph using failure modes to build from bottom up
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%% Paragraph using failure modes to build from bottom up
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%%
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%%
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\subsection{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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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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They identify faults that can occur in a system, and then work down
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@ -112,12 +120,27 @@ We can represet this in a UML diagram see figure \ref{fig:cfg}
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\begin{figure}[h]
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\begin{figure}[h]
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\centering
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\centering
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\includegraphics[width=400pt,bb=0 0 712 235,keepaspectratio=true]{./cfg.jpg}
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\includegraphics[width=400pt,bb=0 0 712 235,keepaspectratio=true]{component_failure_modes_definition/cfg.jpg}
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% cfg.jpg: 712x205 pixel, 72dpi, 25.12x7.23 cm, bb=0 0 712 205
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% cfg.jpg: 712x205 pixel, 72dpi, 25.12x7.23 cm, bb=0 0 712 205
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\caption{Components Derived from Functional Groups}
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\caption{Components Derived from Functional Groups}
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\label{fig:cfg}
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\label{fig:cfg}
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\end{figure}
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\end{figure}
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\section{Set theory description}
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$$ System \stackrel{has}{\longrightarrow} PartsList $$
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$$ PartsList \stackrel{has}{\longrightarrow} Components $$
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$$ Component \stackrel{has}{\longrightarrow} FailureModes $$
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$$ FunctionalGroup \stackrel{has}{\longrightarrow} Components $$
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Using the symbol $\bowtie$ to indicate an analysis process that takes a
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functional group and converts it into a new component.
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$$ \bowtie ( FG ) \mapsto Component $$
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%
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%
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% \subsection{Systems, functional groups, sub-systems and failure modes}
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% \subsection{Systems, functional groups, sub-systems and failure modes}
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@ -280,7 +303,7 @@ We can represet this in a UML diagram see figure \ref{fig:cfg}
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% % \end{figure}
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% % \end{figure}
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\subsection{Unitary State Component Failure Mode sets}
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\section{Unitary State Component Failure Mode sets}
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An important factor in defining a set of failure modes is that they
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An important factor in defining a set of failure modes is that they
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should be as clearly defined as possible.
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should be as clearly defined as possible.
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@ -319,7 +342,7 @@ the component failure modes in each of its members are unitary~state.
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Thus if the failure modes of $F$ are unitary~state, we can say $F \in U$.
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Thus if the failure modes of $F$ are unitary~state, we can say $F \in U$.
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\subsection{Component failure modes : Unitary State example}
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\section{Component failure modes : Unitary State example}
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A component with simple ``unitary~state'' failure modes is the electrical resistor.
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A component with simple ``unitary~state'' failure modes is the electrical resistor.
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@ -352,7 +375,7 @@ for the failure mode set $C$ to exists in the family of sets $U$
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\subsection{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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%\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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A sample space is defined as the set of all possible outcomes.
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Here the outcomes we are interested in are the failure modes
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Here the outcomes we are interested in are the failure modes
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@ -369,24 +392,67 @@ The failure mode set for a given component or sub-system $F$
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is therefore
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is therefore
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$$ F = \Omega(K) \backslash OK $$
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$$ F = \Omega(K) \backslash OK $$
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\clearpage
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THIS SHOULD BE IN A DIFFERENT CHAPTER
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\section{Current Methods for Safety Critical Analysis}
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\subsection{Deterministic Approach}
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\paragraph{NOT WRITTEN YET PLEASE IGNORE}
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No single component fault may lead to a dangerous condition.
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EN298 En230 etc
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\subsection{Bayes Theorem}
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\subsection{Bayes Theorem}
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\paragraph{NOT WRITTEN YET PLEASE IGNORE}
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\paragraph{NOT WRITTEN YET PLEASE IGNORE}
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\label{bayes}
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\label{bayes}
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Describe application - likely hood of faults being the cause of symptoms -
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Describe application - likely hood of faults being the cause of symptoms -
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probablistic approach - no direct causation paths to the higher~abstraction fault mode.
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probablistic approach - no direct causation paths to the higher~abstraction fault mode.
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Often for instance a component in a module within a module within a module etc
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Often for instance a component in a module within a module within a module etc
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that has a probability of causing a SYSTEM level fault.
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that has a probability of causing a SYSTEM level fault.
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Used in FTA\cite{NASA}\cite{NUK}. Problems, difficult to get reliable stats
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Used in FTA\cite{NASA}\cite{NUK}.
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The idea being that probabilities can be assigned to components
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failing, causing system level errors.
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Problems, difficult to get reliable stats
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for probability to cause because of small sample numbers...
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for probability to cause because of small sample numbers...
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FMMD approach can by traversing down the tree use known component failure figures
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FMMD approach can by traversing down the tree use known component failure figures
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to
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to get {\em accurate} probabilities and potential causes.
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%$$ c1 \cap c2 \eq \emptyset | c1 \neq c2 \wedge c1,c2 \in C \wedge C \in U $$
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%$$ c1 \cap c2 \eq \emptyset | c1 \neq c2 \wedge c1,c2 \in C \wedge C \in U $$
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%Thus if the failure~modes are pairwaise mutually exclusive they qualify for inclusion into the
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%Thus if the failure~modes are pairwaise mutually exclusive they qualify for inclusion into the
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%unitary~state set family.
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%unitary~state set family.
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\subsection{ Saftey Integrity Level Analysis }
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\paragraph{NOT WRITTEN YET PLEASE IGNORE}
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\label{sil}
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This technique looks at all components in the parts list
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and asks what the effect of the component failing will be.
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Note that particular failure modes of the compoent are not considered.
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The component can fail in any of its failure modes from the perspective of this analysis.
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The analyst has to make a choice between four conditions:
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\begin{itemize}
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\item sd - A safe fault that is detected by an automated system
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\item su - A safe fault that is undetected by an automated system
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\item dd - A potentially dangerous fault that is detected by an automated system
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\item du - A potentially dangerous fault that is not detected by an automated system
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\end{itemize}
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Actually this is almost how sil analysis is done, because
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the base components are listed
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and their failure result as either sd su dd du
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A formula is then applied according to the system architecture 1oo1 2oo3 3oo3 etc
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What is not done is the probability for all these conditions, the sil analysis
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person simple has to decide which it is.
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Another fault in this is that it is very difficult to
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extract meaning ful stats
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for how likely the detection systems are to pick the fault up, or even to introduce a fault of their own.
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\subsection{Tests of Hypotheses and Significance}
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\subsection{Tests of Hypotheses and Significance}
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\paragraph{NOT WRITTEN YET PLEASE IGNORE}
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\paragraph{NOT WRITTEN YET PLEASE IGNORE}
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Linked in with Bayes theorem
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Linked in with Bayes theorem
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@ -400,3 +466,7 @@ but how do you corrollate that with unshielded suppressed contactors...
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Maybe looking at the equipment and seeing if there is a 5\%
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Maybe looking at the equipment and seeing if there is a 5\%
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level of the error being caused ?
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level of the error being caused ?
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i.e. using it to search for these conditions ?
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i.e. using it to search for these conditions ?
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Actually this could be used to refine the SIL method \ref{sil}
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and give probabilities for the four conditions.
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