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Robin 2010-04-25 12:29:23 +01:00
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component_failure_modes_definition/component_failure_modes_definition.tex
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@ -1,15 +1,23 @@
\abstract{ This chapter defines what is meant by the terms
components, component fault modes and `unitary~state' component fault modes.
The application of Bayes theorem in current methodologies, and
the suitability of the `null hypothesis' or `P' value statistical approach
are discussed.
%The application of Bayes theorem in current methodologies, and
%the suitability of the `null hypothesis' or `P' value statistical approach
%are discussed.
Data types and their relationships are described using UML.
Mathematical constraints and definitions are made using set theory.
}
\section{Introduction}
When analysing a safety critical system using the
FMMD technique, we need clearly defined failure modes for
all the components that are used to model the system.
These failure modes have a constraint such that
the compoent failure modes must be mutually exclusive.
This and the definition of a component are
described in this chapter.
%When building a system from components,
%we should be able to find all known failure modes for each component.
%For most common electrical and mechanical components, the failure modes
@ -21,7 +29,7 @@ Mathematical constraints and definitions are made using set theory.
%% Paragraph component and its relationship to its failure modes
%%
\subsection{ What is a Component ?}
\section{ What is a Component ?}
Let us first define a component. This is anything we use to build a
@ -42,7 +50,7 @@ structure with its failure modes.
\begin{figure}[h]
\centering
\includegraphics[width=400pt,bb=0 0 437 141,keepaspectratio=true]{./component.jpg}
\includegraphics[width=400pt,bb=0 0 437 141,keepaspectratio=true]{component_failure_modes_definition/component.jpg}
% component.jpg: 437x141 pixel, 72dpi, 15.42x4.97 cm, bb=0 0 437 141
\caption{A Component and its Failure Modes}
\label{fig:component}
@ -63,7 +71,7 @@ For our UML diagram the parts list is simply a collection of components
as shown in figure \ref{fig:componentpl}.
\begin{figure}[h]
\centering
\includegraphics[width=400pt,bb=0 0 712 68,keepaspectratio=true]{./componentpl.jpg}
\includegraphics[width=400pt,bb=0 0 712 68,keepaspectratio=true]{component_failure_modes_definition/componentpl.jpg}
% componentpl.jpg: 712x68 pixel, 72dpi, 25.12x2.40 cm, bb=0 0 712 68
\caption{Parts List of Components}
\label{fig:componentpl}
@ -76,7 +84,7 @@ as shown in figure \ref{fig:componentpl}.
%% Paragraph using failure modes to build from bottom up
%%
\subsection{Fault Mode Analysis, top down or bottom up?}
\section{Fault Mode Analysis, top down or bottom up?}
Traditional static fault analysis methods work from the top down.
They identify faults that can occur in a system, and then work down
@ -112,12 +120,27 @@ We can represet this in a UML diagram see figure \ref{fig:cfg}
\begin{figure}[h]
\centering
\includegraphics[width=400pt,bb=0 0 712 235,keepaspectratio=true]{./cfg.jpg}
\includegraphics[width=400pt,bb=0 0 712 235,keepaspectratio=true]{component_failure_modes_definition/cfg.jpg}
% cfg.jpg: 712x205 pixel, 72dpi, 25.12x7.23 cm, bb=0 0 712 205
\caption{Components Derived from Functional Groups}
\label{fig:cfg}
\end{figure}
\section{Set theory description}
$$ System \stackrel{has}{\longrightarrow} PartsList $$
$$ PartsList \stackrel{has}{\longrightarrow} Components $$
$$ Component \stackrel{has}{\longrightarrow} FailureModes $$
$$ FunctionalGroup \stackrel{has}{\longrightarrow} Components $$
Using the symbol $\bowtie$ to indicate an analysis process that takes a
functional group and converts it into a new component.
$$ \bowtie ( FG ) \mapsto Component $$
%
% \subsection{Systems, functional groups, sub-systems and failure modes}
@ -280,7 +303,7 @@ We can represet this in a UML diagram see figure \ref{fig:cfg}
% % \end{figure}
\subsection{Unitary State Component Failure Mode sets}
\section{Unitary State Component Failure Mode sets}
An important factor in defining a set of failure modes is that they
should be as clearly defined as possible.
@ -319,7 +342,7 @@ the component failure modes in each of its members are unitary~state.
Thus if the failure modes of $F$ are unitary~state, we can say $F \in U$.
\subsection{Component failure modes : Unitary State example}
\section{Component failure modes : Unitary State example}
A component with simple ``unitary~state'' failure modes is the electrical resistor.
@ -352,7 +375,7 @@ for the failure mode set $C$ to exists in the family of sets $U$
\subsection{Component Failure Modes and Statistical Sample Space}
\section{Component Failure Modes and Statistical Sample Space}
%\paragraph{NOT WRITTEN YET PLEASE IGNORE}
A sample space is defined as the set of all possible outcomes.
Here the outcomes we are interested in are the failure modes
@ -369,24 +392,67 @@ The failure mode set for a given component or sub-system $F$
is therefore
$$ F = \Omega(K) \backslash OK $$
\clearpage
THIS SHOULD BE IN A DIFFERENT CHAPTER
\section{Current Methods for Safety Critical Analysis}
\subsection{Deterministic Approach}
\paragraph{NOT WRITTEN YET PLEASE IGNORE}
No single component fault may lead to a dangerous condition.
EN298 En230 etc
\subsection{Bayes Theorem}
\paragraph{NOT WRITTEN YET PLEASE IGNORE}
\paragraph{NOT WRITTEN YET PLEASE IGNORE}
\label{bayes}
Describe application - likely hood of faults being the cause of symptoms -
probablistic approach - no direct causation paths to the higher~abstraction fault mode.
Often for instance a component in a module within a module within a module etc
that has a probability of causing a SYSTEM level fault.
Used in FTA\cite{NASA}\cite{NUK}. Problems, difficult to get reliable stats
Used in FTA\cite{NASA}\cite{NUK}.
The idea being that probabilities can be assigned to components
failing, causing system level errors.
Problems, difficult to get reliable stats
for probability to cause because of small sample numbers...
FMMD approach can by traversing down the tree use known component failure figures
to
to get {\em accurate} probabilities and potential causes.
%$$ c1 \cap c2 \eq \emptyset | c1 \neq c2 \wedge c1,c2 \in C \wedge C \in U $$
%Thus if the failure~modes are pairwaise mutually exclusive they qualify for inclusion into the
%unitary~state set family.
\subsection{ Saftey Integrity Level Analysis }
\paragraph{NOT WRITTEN YET PLEASE IGNORE}
\label{sil}
This technique looks at all components in the parts list
and asks what the effect of the component failing will be.
Note that particular failure modes of the compoent are not considered.
The component can fail in any of its failure modes from the perspective of this analysis.
The analyst has to make a choice between four conditions:
\begin{itemize}
\item sd - A safe fault that is detected by an automated system
\item su - A safe fault that is undetected by an automated system
\item dd - A potentially dangerous fault that is detected by an automated system
\item du - A potentially dangerous fault that is not detected by an automated system
\end{itemize}
Actually this is almost how sil analysis is done, because
the base components are listed
and their failure result as either sd su dd du
A formula is then applied according to the system architecture 1oo1 2oo3 3oo3 etc
What is not done is the probability for all these conditions, the sil analysis
person simple has to decide which it is.
Another fault in this is that it is very difficult to
extract meaning ful stats
for how likely the detection systems are to pick the fault up, or even to introduce a fault of their own.
\subsection{Tests of Hypotheses and Significance}
\paragraph{NOT WRITTEN YET PLEASE IGNORE}
Linked in with Bayes theorem
@ -400,3 +466,7 @@ but how do you corrollate that with unshielded suppressed contactors...
Maybe looking at the equipment and seeing if there is a 5\%
level of the error being caused ?
i.e. using it to search for these conditions ?
Actually this could be used to refine the SIL method \ref{sil}
and give probabilities for the four conditions.