931 lines
30 KiB
TeX
931 lines
30 KiB
TeX
\documentclass{beamer}
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\title[Failure Mode Effects Analysis]{Failure Mode Effects Analysis\\A critical view}
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\usetheme{Warsaw}
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\usepackage[latin1]{inputenc}
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\author{Robin Clark -- Energy Technology Control Ltd}
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\institute{Brighton University}
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\setbeamertemplate{footline}[page number]
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\newcommand{\fg}{\em functional~group}
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\newcommand{\fgs}{\em functional~groups}
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\newcommand{\dc}{\em derived~component}
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\newcommand{\dcs}{\em derived~components}
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\newcommand{\bc}{\em base~component}
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\newcommand{\bcs}{\em base~components}
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\newcommand{\irl}{in~real~life}
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\begin{document}
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\section{F.M.E.A.}
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\begin{frame}
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\frametitle{Outline}
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\tableofcontents[currentsection]
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\end{frame}
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\begin{frame}
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\begin{itemize}
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\pause \item Failure
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\pause \item Mode
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\pause \item Effects
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\pause \item Analysis
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\end{itemize}
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\end{frame}
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% % \begin{itemize}
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% \item Failure
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% \item Mode
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% \item Effects
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% \item Analysis
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% \end{itemize}
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\subsection{FMEA basic concept}
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\begin{frame}
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\begin{itemize}
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\pause \item \textbf{F - Failures of given component} Consider a component in a system
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\pause \item \textbf{M - Failure Mode} Look at one of the ways in which it can fail (i.e. determine a component `failure~mode')
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\pause \item \textbf{E - Effects} Determine the effects this failure mode will cause to the system we are examining
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\pause \item \textbf{A - Analysis} Analyse how much impact this symptom will have on the environment/people/the system its-self
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\end{itemize}
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\end{frame}
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\begin{frame}
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\frametitle{ FMEA Example: Milli-volt reader}
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Example: Let us consider a system, in this case a milli-volt reader, consisting
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of instrumentation amplifiers connected to a micro-processor
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that reports its readings via RS-232.
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\begin{figure}
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\centering
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\includegraphics[width=175pt]{./mvamp.png}
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% mvamp.png: 561x403 pixel, 72dpi, 19.79x14.22 cm, bb=0 0 561 403
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\end{figure}
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\end{frame}
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\begin{frame}
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\frametitle{FMEA Example: Milli-volt reader}
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Let us perform an FMEA and consider how one of its resistors failing could affect
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it.
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For the sake of example let us choose resistor R1 in the OP-AMP gain circuitry.
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\begin{figure}
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\centering
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\includegraphics[width=175pt]{./mvamp.png}
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% mvamp.png: 561x403 pixel, 72dpi, 19.79x14.22 cm, bb=0 0 561 403
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\end{figure}
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\end{frame}
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\begin{frame}
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\frametitle{FMEA Example: Milli-volt reader}
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\begin{itemize}
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\pause \item \textbf{F - Failures of given component} The resistor (R1) could fail by going OPEN or SHORT (EN298 definition).
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\pause \item \textbf{M - Failure Mode} Consider the component failure mode SHORT
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\pause \item \textbf{E - Effects} This will drive the minus input LOW causing a HIGH OUTPUT/READING
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\pause \item \textbf{A - Analysis} The reading will be out of normal range, and we will have an erroneous milli-volt reading
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\end{itemize}
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\end{frame}
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\begin{frame}
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Note here that we have had to look at the failure~mode
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in relation to the entire circuit.
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We have used intuition to determine the probable
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effect of this failure mode.
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We have not examined this failure mode
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against every other component in the system.
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Perhaps we should.... this would be a more rigorous and complete
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approach in looking for system failures.
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\end{frame}
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\subsection{Rigorous FMEA - State Explosion}
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\begin{frame}
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\frametitle{Rigorous Single Failure FMEA}
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Consider the analysis
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where we look at all the failure modes in a system, and then
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see how they can affect all other components within it.
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\end{frame}
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\begin{frame}
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\frametitle{Rigorous Single Failure FMEA}
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We need to look at a large number of failure scenarios
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to do this completely (all failure modes against all components).
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This is represented in the equation below. %~\ref{eqn:fmea_state_exp},
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where $N$ is the total number of components in the system, and
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$cfm$ is the number of failure modes per component.
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\begin{equation}
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\label{eqn:fmea_single}
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N.(N-1).cfm % \\
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%(N^2 - N).cfm
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\end{equation}
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\end{frame}
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\begin{frame}
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\frametitle{Rigorous Single Failure FMEA}
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This would mean an order of $N^2$ number of checks to perform
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to undertake a `rigorous~FMEA'. Even small systems have typically
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100 components, and they typically have 3 or more failure modes each.
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$100*99*3=29,700$.
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\end{frame}
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\begin{frame}
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\frametitle{Rigorous Double Failure FMEA}
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For looking at potential double failure scenarios (two components
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failing within a given time frame) and the order becomes
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$N^3$.
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\begin{equation}
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\label{eqn:fmea_double}
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N.(N-1).(N-2).cfm % \\
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%(N^2 - N).cfm
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\end{equation}
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$100*99*98*3=2,910,600$.
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The European Gas burner standard (EN298:2003), demands the checking of
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double failure scenarios (for burner lock-out scenarios).
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\end{frame}
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\section{PFMEA - Production FMEA : 1940's to present}
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\begin{frame}
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Production FMEA (or PFMEA), is FMEA used to prioritise, in terms of
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cost, problems to be addressed in product production.
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It focuses on known problems, determines the
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frequency they occur and their cost to fix.
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This is multiplied together and called an RPN
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number.
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Fixing problems with the highest RPN number
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will return most cost benefit.
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\end{frame}
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\begin{frame}
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% benign example of PFMEA in CARS - make something up.
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\frametitle{PFMEA Example}
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{
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\begin{table}[ht]
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\caption{FMEA Calculations} % title of Table
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%\centering % used for centering table
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\begin{tabular}{|| l | l | c | c | l ||} \hline
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\textbf{Failure Mode} & \textbf{P} & \textbf{Cost} & \textbf{Symptom} & \textbf{RPN} \\ \hline \hline
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relay 1 n/c & $1*10^{-5}$ & 38.0 & indicators fail & 0.00038 \\ \hline
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relay 2 n/c & $1*10^{-5}$ & 98.0 & doorlocks fail & 0.00098 \\ \hline
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% rear end crash & $14.4*10^{-6}$ & 267,700 & fatal fire & 3.855 \\
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% ruptured f.tank & & & & \\ \hline
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\hline
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\end{tabular}
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\end{table}
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}
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%Savings: 180 burn deaths, 180 serious burn injuries, 2,100 burned vehicles. Unit Cost: $200,000 per death, $67,000 per injury, $700 per vehicle.
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%Total Benefit: 180 X ($200,000) + 180 X ($67,000) + $2,100 X ($700) = $49.5 million.
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%COSTS
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%Sales: 11 million cars, 1.5 million light trucks.
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%Unit Cost: $11 per car, $11 per truck.
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%Total Cost: 11,000,000 X ($11) + 1,500,000 X ($11) = $137 million.
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\end{frame}
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%\subsection{Production FMEA : Example Ford Pinto : 1975}
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\begin{frame}
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\frametitle{PFMEA Example: Ford Pinto: 1975}
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\begin{figure}[h]
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\centering
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\includegraphics[width=200pt]{./ad_ford_pinto_mpg_red_3_1975.jpg}
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% ad_ford_pinto_mpg_red_3_1975.jpg: 720x933 pixel, 96dpi, 19.05x24.69 cm, bb=0 0 540 700
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\caption{Ford Pinto Advert}
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\label{fig:fordpintoad}
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\end{figure}
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\end{frame}
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\begin{frame}
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\frametitle{PFMEA Example: Ford Pinto: 1975}
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\begin{figure}[h]
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\centering
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\includegraphics[width=200pt]{./burntoutpinto.png}
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% burntoutpinto.png: 376x250 pixel, 72dpi, 13.26x8.82 cm, bb=0 0 376 250
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\caption{Burnt Out Pinto}
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\label{fig:burntoutpinto}
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\end{figure}
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\end{frame}
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\begin{frame}
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\frametitle{PFMEA Example: Ford Pinto: 1975}
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{
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\begin{table}[ht]
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\caption{FMEA Calculations} % title of Table
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%\centering % used for centering table
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\begin{tabular}{|| l | l | c | c | l ||} \hline
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\textbf{Failure Mode} & \textbf{P} & \textbf{Cost} & \textbf{Symptom} & \textbf{RPN} \\ \hline \hline
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relay 1 n/c & $1*10^{-5}$ & 38.0 & indicators fail & 0.00038 \\ \hline
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relay 2 n/c & $1*10^{-5}$ & 98.0 & doorlocks fail & 0.00098 \\ \hline
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rear end crash & $14.4*10^{-6}$ & 267,700 & fatal fire & 3.855 \\
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ruptured f.tank & & & allow & \\ \hline
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rear end crash & $1$ & $11$ & recall & 11.0 \\
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ruptured f.tank & & & fix tank & \\ \hline
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\hline
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\end{tabular}
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\end{table}
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}
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http://www.youtube.com/watch?v=rcNeorjXMrE
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\end{frame}
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\section{FMECA - Failure Modes Effects and Criticallity Analysis}
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\begin{frame}
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\frametitle{ FMECA - Failure Modes Effects and Criticallity Analysis}
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\begin{figure}
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\centering
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%\includegraphics[width=100pt]{./military-aircraft-desktop-computer-wallpaper-missile-launch.jpg}
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\includegraphics[width=100pt]{./A10_thunderbolt.jpg}
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% military-aircraft-desktop-computer-wallpaper-missile-launch.jpg: 1024x768 pixel, 300dpi, 8.67x6.50 cm, bb=0 0 246 184
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\caption{A10 Thunderbolt}
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\label{fig:f16missile}
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\end{figure}
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Emphasis on determining criticallity of failure.
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Applies some Bayesian statistics (probabilities of component failures and those causing given system level failures).
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\end{frame}
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\section{FMECA - Failure Modes Effects and Criticallity Analysis}
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\begin{frame}
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\frametitle{ FMECA - Failure Modes Effects and Criticallity Analysis}
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Very similar to PFMEA, but instead of cost, a criticallity or
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seriousness factor is ascribed to putative top level incidents.
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FMECA has three probability factors for component failures.
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\textbf{FMECA ${\lambda}_{p}$ value.}
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This is the overall failure rate of a base component.
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This will typically be the failure rate per million ($10^6$) or
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billion ($10^9$) hours of operation.
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\textbf{FMECA $\alpha$ value.}
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The failure mode probability, usually denoted by $\alpha$ is the probability of
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is the probability of a particular failure
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mode occurring within a component.
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%, should it fail.
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%A component with N failure modes will thus have
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%have an $\alpha$ value associated with each of those modes.
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%As the $\alpha$ modes are probabilities, the sum of all $\alpha$ modes for a component must equal one.
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\end{frame}
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\begin{frame}
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\frametitle{ FMECA - Failure Modes Effects and Criticallity Analysis}
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\textbf{FMECA $\beta$ value.}
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The second probability factor $\beta$, is the probability that the failure mode
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will cause a given system failure.
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This corresponds to `Bayesian' probability, given a particular
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component failure mode, the probability of a given system level failure.
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\textbf{FMECA `t' Value}
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The time that a system will be operating for, or the working life time of the product is
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represented by the variable $t$.
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%for probability of failure on demand studies,
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%this can be the number of operating cycles or demands expected.
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\textbf{Severity `s' value}
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A weighting factor to indicate the seriousness of the putative system level error.
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%Typical classifications are as follows:~\cite{fmd91}
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\begin{equation}
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C_m = {\beta} . {\alpha} . {{\lambda}_p} . {t} . {s}
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\end{equation}
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Highest $C_m$ values would be at the top of a `to~do' list
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for a project manager.
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\end{frame}
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\section{FMEDA - Failure Modes Effects and Diagnostic Analysis}
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\begin{frame}
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\frametitle{ FMEDA - Failure Modes Effects and Diagnostic Analysis}
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\begin{figure}
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\centering
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\includegraphics[width=200pt]{./SIL.png}
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% SIL.jpg: 350x286 pixel, 72dpi, 12.35x10.09 cm, bb=0 0 350 286
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\caption{SIL requirements}
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\end{figure}
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\end{frame}
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\begin{frame}
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\frametitle{ FMEDA - Failure Modes Effects and Diagnostic Analysis}
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FMEDA is the methodology behind statistical (safety integrity level)
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type standards (EN61508/IOC5108).
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It provides a statistical overall level of safety
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and allows diagnostic mitigation for self checking etc.
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It provides guidelines for the design and architecture
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of computer/software systems for the four levels of
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safety Integrity.
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%For Hardware
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FMEDA does force the user to consider all components in a system
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by requiring that a MTTF value is assigned for each failure~mode.
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This MTTF may be statistically mitigated (improved)
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if it can be shown that self-checking will detect failure modes.
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\end{frame}
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\begin{frame}
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\frametitle{ FMEDA - Failure Modes Effects and Diagnostic Analysis}
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Failure modes are classified as Safe or Dangerous according
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to the putative system level failure they will cause.
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The Failure modes are also classified as Detected or
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Undetected.
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This gives us four level failure mode classifications:
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Safe-Detected (SD), Safe-Undetected (SU), Dangerous-Detected (DD) or Dangerous-Undetected (DU),
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and the probabilistic failure rate of each classification
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is represented by lambda variables
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(i.e. $\lambda_{SD}$, $\lambda_{SU}$, $\lambda_{DD}$, $\lambda_{DU}$).
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\end{frame}
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\begin{frame}
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\frametitle{ FMEDA - Failure Modes Effects and Diagnostic Analysis}
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\textbf{Diagnostic Coverage.}
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The diagnostic coverage is simply the ratio
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of the dangerous detected probabilities
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against the probability of all dangerous failures,
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and is normally expressed as a percentage. $\Sigma\lambda_{DD}$ represents
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the percentage of dangerous detected base component failure modes, and
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$\Sigma\lambda_D$ the total number of dangerous base component failure modes.
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$$ DiagnosticCoverage = \Sigma\lambda_{DD} / \Sigma\lambda_D $$
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\end{frame}
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\begin{frame}
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\frametitle{ FMEDA - Failure Modes Effects and Diagnostic Analysis}
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The \textbf{diagnostic coverage} for safe failures, where $\Sigma\lambda_{SD}$ represents the percentage of
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safe detected base component failure modes,
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and $\Sigma\lambda_S$ the total number of safe base component failure modes,
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is given as
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$$ SF = \frac{\Sigma\lambda_{SD}}{\Sigma\lambda_S} $$
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\end{frame}
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\begin{frame}
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\frametitle{ FMEDA - Failure Modes Effects and Diagnostic Analysis}
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\textbf{Safe Failure Fraction.}
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A key concept in FMEDA is Safe Failure Fraction (SFF).
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This is the ratio of safe and dangerous detected failures
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against all safe and dangerous failure probabilities.
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Again this is usually expressed as a percentage.
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$$ SFF = \big( \Sigma\lambda_S + \Sigma\lambda_{DD} \big) / \big( \Sigma\lambda_S + \Sigma\lambda_D \big) $$
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SFF determines how proportionately fail-safe a system is, not how reliable it is !
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\end{frame}
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\begin{frame}
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\frametitle{ FMEDA - Failure Modes Effects and Diagnostic Analysis}
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To achieve SIL levels, diagnostic coverage and SFF levels are prescribed along with
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hardware architectures and software techniques.
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Over all the aim of SIL is classify the safety of a system,
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by statistically determining how frequently it can fail dangerously.
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\end{frame}
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\begin{frame}
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\frametitle{ FMEDA - Failure Modes Effects and Diagnostic Analysis}
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{
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\begin{table}[ht]
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\caption{FMEA Calculations} % title of Table
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%\centering % used for centering table
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\begin{tabular}{|| l | l | c | c | l ||} \hline
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\textbf{SIL} & \textbf{Low Demand} & \textbf{Continuous Demand} \\
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& Prob of failing on demand & Prob of failure per hour \\ \hline \hline
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4 & $ 10^{-5}$ to $< 10^{-4}$ & $ 10^{-9}$ to $< 10^{-8}$ \\ \hline
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3 & $ 10^{-4}$ to $< 10^{-3}$ & $ 10^{-8}$ to $< 10^{-7}$ \\ \hline
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2 & $ 10^{-3}$ to $< 10^{-2}$ & $ 10^{-7}$ to $< 10^{-6}$ \\ \hline
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1 & $ 10^{-2}$ to $< 10^{-1}$ & $ 10^{-6}$ to $< 10^{-5}$ \\ \hline
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\hline
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\end{tabular}
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\end{table}
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}
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Table adapted from EN61508-1:2001 [7.6.2.9 p33]
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\end{frame}
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\begin{frame}
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\frametitle{ FMEDA - Failure Modes Effects and Diagnostic Analysis}
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FMEDA is a modern extension of FMEA, in that it will allow for
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self checking features, and provides detailed recommendations for computer/software architecture.
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It also has a simple final result, a Safety Integrity Level (SIL) from 1 to 4 (where 4 is safest).
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%FMEA can be used as a term simple to mean Failure Mode Effects Analysis, and is
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%part of product approval for many regulated products in the EU and the USA...
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\end{frame}
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\section{FMEA used for Safety Critical Approvals}
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\begin{frame}
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\frametitle{DESIGN FMEA: Safety Critical Approvals FMEA}
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Experts from Approval House and Equipment Manufacturer
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discuss selected component failure modes
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judged to be in critical sections of the product.
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\begin{figure}[h]
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\centering
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\includegraphics[width=100pt,keepaspectratio=true]{./tech_meeting.png}
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% tech_meeting.png: 350x299 pixel, 300dpi, 2.97x2.53 cm, bb=0 0 84 72
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\caption{FMEA Meeting}
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\label{fig:tech_meeting}
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\end{figure}
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\end{frame}
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\begin{frame}
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\frametitle{DESIGN FMEA: Safety Critical Approvals FMEA}
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\begin{figure}[h]
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\centering
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\includegraphics[width=70pt,keepaspectratio=true]{./tech_meeting.png}
|
|
% tech_meeting.png: 350x299 pixel, 300dpi, 2.97x2.53 cm, bb=0 0 84 72
|
|
\caption{FMEA Meeting}
|
|
\label{fig:tech_meeting}
|
|
\end{figure}
|
|
|
|
\begin{itemize}
|
|
\pause \item Impossible to look at all component failures let alone apply FMEA rigorously.
|
|
\pause \item In practise, failure scenarios for critical sections are contested, and either justified or extra safety measures implemented.
|
|
\pause \item Often Meeting notes or minutes only. Unusual for detailed arguments to be documented.
|
|
\end{itemize}
|
|
|
|
\end{frame}
|
|
|
|
\section{FMEA - General Criticism}
|
|
\begin{frame}
|
|
\frametitle{FMEA - General Criticism}
|
|
|
|
\begin{itemize}
|
|
\pause \item Reasoning Distance - component failure to system level symptom
|
|
\pause \item State explosion - impossible to perform rigorously
|
|
\pause \item Difficult to re-use previous analysis work
|
|
\pause \item FMEA type methodologies were designed for simple electro-mechanical systems of the 1940's to 1960's.
|
|
\end{itemize}
|
|
|
|
%
|
|
|
|
\end{frame}
|
|
|
|
|
|
\subsection{FMEA - Better Metodology - Wish List}
|
|
|
|
\begin{frame}
|
|
\frametitle{FMEA - Better Metodology - Wish List}
|
|
|
|
\begin{itemize}
|
|
|
|
\pause \item State explosion
|
|
\pause \item Rigorous
|
|
\pause \item Reasoning Traceable
|
|
\pause \item re-useable
|
|
%\pause \item
|
|
\end{itemize}
|
|
|
|
%FMEDA is a modern extension of FMEA, in that it will allow for
|
|
%self checking features, and provides detailed recommendations for computer/software architecture,
|
|
%but
|
|
|
|
\end{frame}
|
|
\section{Failure Mode Modular De-Composition}
|
|
\begin{frame}
|
|
\frametitle{FMMD - Failure Mode Modular De-Composition}
|
|
% Consider the FMEA type methodologies
|
|
% where we look at all the failure modes in a system, and then
|
|
% see how they can affect all other components within it,
|
|
% to determine its system level symptom or failure mode.
|
|
% We need to look at a large number of failure scenarios
|
|
% to do this completely (all failure modes against all components).
|
|
% This is represented in equation~\ref{eqn:fmea_state_exp},
|
|
% where $N$ is the total number of components in the system, and
|
|
% $cfm$ is the number of failure modes per component.
|
|
%
|
|
% \begin{equation}
|
|
% \label{eqn:fmea_state_exp}
|
|
% N.(N-1).cfm % \\
|
|
% %(N^2 - N).cfm
|
|
% \end{equation}
|
|
|
|
|
|
The FMMD methodology breaks the analysis down into small stages,
|
|
by making the analyst choose {\fgs} of components, to which FMEA is applied.
|
|
When analysed, a set of symptoms of failure for the {\fg} is used create a derived~component.
|
|
The derived components failure modes, are the symptoms of the {\fg}
|
|
from which it was derived.
|
|
We can use derived components to form `higher~level' {\fgs}.
|
|
This creates an analysis hierarchy.
|
|
\end{frame}
|
|
|
|
|
|
\subsection{FMMD Outline of Methodology}
|
|
\begin{frame}
|
|
\frametitle{FMMD - Outline of Methodology}
|
|
\begin{itemize}
|
|
\pause \item Select `{\fgs}' of components ( groups that perform a well defined function).
|
|
\pause \item Using the failure modes of the components create failure scenarios.
|
|
\pause \item Analyse each failure scenario of the {\fg}.
|
|
\pause \item Collect Symptoms.
|
|
\pause \item Create a '{\dc}', where its failure modes are the symptoms of the {\fg} it was derived from.
|
|
\pause \item The {\dc} is now available to be used in higher level {\fgs}.
|
|
\end{itemize}
|
|
\end{frame}
|
|
|
|
|
|
|
|
\subsection{FMMD - Example - Milli Volt Amplifier}
|
|
\begin{frame}
|
|
\frametitle{FMMD - Example - Milli Volt Amplifier}
|
|
We can return to the milli-volt amplifier as an example to analyse.
|
|
|
|
We can begin by looking for functional groups.
|
|
The resistors would together to perform a fairly common function in electronics, that of the potential divider.
|
|
So our first functional group is $\{ R1, R2 \}$.
|
|
We can now take the failure modes for the resistors (OPEN and SHORT EN298) and see what effect each of these failures will have on the {\fg} (the potential divider).
|
|
\begin{figure}
|
|
\centering
|
|
\includegraphics[width=100pt]{./mvampcircuit.png}
|
|
% mvampcircuit.png: 243x143 pixel, 72dpi, 8.57x5.04 cm, bb=0 0 243 143
|
|
\end{figure}
|
|
|
|
\end{frame}
|
|
|
|
|
|
\begin{frame}
|
|
\frametitle{FMMD - Example - Resistor and failure modes}
|
|
Resistor and its failure modes represented as a directed graph.
|
|
|
|
\begin{figure}
|
|
\centering
|
|
\includegraphics[width=200pt]{./resistor_failure_graph.png}
|
|
% resistor_failure_graph.png: 391x279 pixel, 93dpi, 10.68x7.62 cm, bb=0 0 303 216
|
|
\label{fig:resasfm}
|
|
\end{figure}
|
|
|
|
\end{frame}
|
|
|
|
|
|
\subsubsection{Potential Divider}
|
|
\begin{frame}
|
|
\frametitle{FMMD - Example - Failure mode analysis of Potential Divider}
|
|
|
|
|
|
\begin{table}
|
|
\begin{tabular}{|| l | l | c | c | l ||} \hline
|
|
\textbf{Failure Scenario} & & \textbf{Pot Div Effect} & & \textbf{Symptom} \\
|
|
\hline
|
|
FS1: R1 SHORT & & $LOW$ & & $PDLow$ \\ \hline
|
|
FS2: R1 OPEN & & $HIGH$ & & $PDHigh$ \\ \hline
|
|
FS3: R2 SHORT & & $HIGH$ & & $PDHigh$ \\ \hline
|
|
FS4: R2 OPEN & & $LOW$ & & $PDLow$ \\ \hline
|
|
\hline
|
|
\end{tabular}
|
|
\end{table}
|
|
|
|
\begin{figure}
|
|
\centering
|
|
\includegraphics[width=100pt,keepaspectratio=true]{./pd.png}
|
|
% pd.png: 361x241 pixel, 72dpi, 12.74x8.50 cm, bb=0 0 361 241
|
|
\end{figure}
|
|
\end{frame}
|
|
|
|
|
|
|
|
\begin{frame}
|
|
\frametitle{FMMD - Example - Potential Divider as Derived Component}
|
|
\begin{figure}
|
|
\centering
|
|
\includegraphics[width=175pt]{./pd_failures_as_graph.png}
|
|
% pd_dc_failures_as_graph.png: 389x284 pixel, 93dpi, 10.63x7.76 cm, bb=0 0 301 220
|
|
\label{fig:pd}
|
|
\end{figure}
|
|
\end{frame}
|
|
|
|
|
|
\begin{frame}
|
|
\frametitle{FMMD - Example - Potential Divider as Derived Component}
|
|
\begin{figure}
|
|
\centering
|
|
\includegraphics[width=200pt]{./pd_dc_failures_as_graph.png}
|
|
% pd_dc_failures_as_graph.png: 389x284 pixel, 93dpi, 10.63x7.76 cm, bb=0 0 301 220
|
|
\label{fig:pd}
|
|
\end{figure}
|
|
\end{frame}
|
|
|
|
\begin{frame}
|
|
\frametitle{FMMD - Example - Potential Divider as Derived Component}
|
|
|
|
We can now use this pre-analysed potential divider `derived~component'
|
|
in a higher level design.
|
|
|
|
\begin{figure}
|
|
\centering
|
|
\includegraphics[width=100pt]{./pd_dc_failures_as_graph.png}
|
|
% pd_dc_failures_as_graph.png: 389x284 pixel, 93dpi, 10.63x7.76 cm, bb=0 0 301 220
|
|
\label{fig:pd}
|
|
\end{figure}
|
|
\end{frame}
|
|
|
|
\subsection{Non Inverting OP-AMP}
|
|
|
|
\begin{frame}
|
|
\frametitle{FMMD - Example - Non Inverting OP-AMP}
|
|
\begin{figure}
|
|
\centering
|
|
\includegraphics{./mvampcircuit.png}
|
|
% mvampcircuit.png: 243x143 pixel, 72dpi, 8.57x5.04 cm, bb=0 0 243 143
|
|
\end{figure}
|
|
|
|
\end{frame}
|
|
|
|
|
|
|
|
\begin{frame}
|
|
\frametitle{FMMD - Example - Non Inverting OP-AMP}
|
|
\begin{figure}
|
|
\centering
|
|
\includegraphics[width=300pt]{./non_inv_amp_fmea.png}
|
|
% non_inv_amp_fmea.png: 964x492 pixel, 96dpi, 25.50x13.02 cm, bb=0 0 723 369
|
|
\end{figure}
|
|
|
|
\end{frame}
|
|
|
|
|
|
\begin{frame}
|
|
\frametitle{FMMD - Example - Non Inverting OP-AMP}
|
|
% \begin{figure}
|
|
% \centering
|
|
% \includegraphics[width=200pt]{./opamp_failures_as_graph.png} // op amp failure modes
|
|
% % opamp_failures_as_graph.png: 329x440 pixel, 93dpi, 8.99x12.02 cm, bb=0 0 255 341
|
|
% \end{figure}
|
|
\begin{figure}
|
|
\centering
|
|
\includegraphics[width=150pt]{./fg_opamp_pd_as_graph.png}
|
|
% fg_opamp_pd_as_graph.png: 750x826 pixel, 93dpi, 20.49x22.56 cm, bb=0 0 581 640
|
|
\end{figure}
|
|
\end{frame}
|
|
|
|
|
|
|
|
\begin{frame}
|
|
\frametitle{FMMD - Example - Non Inverting OP-AMP}
|
|
\begin{figure}
|
|
\centering
|
|
\includegraphics[width=150pt]{./n_inv_dc.png}
|
|
% n_inv_dc.png: 296x326 pixel, 72dpi, 10.44x11.50 cm, bb=0 0 296 326
|
|
\end{figure}
|
|
|
|
\end{frame}
|
|
|
|
|
|
|
|
\begin{frame}
|
|
\frametitle{FMMD - Example - Non Inverting OP-AMP}
|
|
\begin{figure}
|
|
\centering
|
|
\includegraphics[width=200pt]{./fmmd_exm_h.png}
|
|
% fmmd_exm_h.png: 376x241 pixel, 72dpi, 13.26x8.50 cm, bb=0 0 376 241
|
|
\end{figure}
|
|
|
|
|
|
\end{frame}
|
|
|
|
\begin{frame}
|
|
\frametitle{FMMD - Failure Mode Modular De-Composition}
|
|
We can view the functional groups in FMMD as forming a hierarchy.
|
|
If for the sake of example we consider each functional group to
|
|
be three components, the figure below shows
|
|
how the levels work and converge to a top or system level.
|
|
\begin{figure}
|
|
\centering
|
|
\includegraphics[width=300pt]{./three_tree.png}
|
|
% three_tree.png: 780x226 pixel, 72dpi, 27.52x7.97 cm, bb=0 0 780 226
|
|
\caption{Functional Group Tree example}
|
|
\label{fig:three_tree}
|
|
\end{figure}
|
|
\end{frame}
|
|
|
|
\begin{frame}
|
|
\frametitle{FMMD - Failure Mode Modular De-Composition}
|
|
The fact FMMD analyses small groups of components at a time, and organises them
|
|
into a hierarchy
|
|
addresses the state explosion (where $O$ is order
|
|
of complexity) $O=N^2$ inherent in equation
|
|
|
|
\begin{equation}
|
|
\label{eqn:fmea_single2}
|
|
N.(N-1).cfm % \\
|
|
%(N^2 - N).cfm
|
|
\end{equation}
|
|
|
|
|
|
We can represent the number of failure scenarios to check in an FMMD hierarchy
|
|
with equation~\ref{eqn:anscen}.
|
|
|
|
\begin{equation}
|
|
\label{eqn:anscen}
|
|
\sum_{n=0}^{L} {fgn}^{n}.fgn.cfm.(fgn-1)
|
|
\end{equation}
|
|
Where $fgn$ is the number of components in each functional group,
|
|
and $cfm$ is the number of failure modes per component
|
|
and L is the number of levels, the number of
|
|
analysis scenarios to consider is show in equation~\ref{eqn:anscen}.
|
|
|
|
~\ref{eqn:fmea_state_exp}.
|
|
|
|
\end{frame}
|
|
|
|
|
|
|
|
% So for a very simple analysis with three components forming a functional group where
|
|
% each component has three failure modes, we have only one level (zero'th).
|
|
% So to check every failure modes against the other components in the functional group
|
|
% requires 18 checks.
|
|
%
|
|
% \begin{equation}
|
|
% \label{eqn:anscen2}
|
|
% \sum_{n=0}^{0} {3}^{0}.3.3.(3-1) = 18
|
|
% \end{equation}
|
|
% \clearpage
|
|
%
|
|
%
|
|
%
|
|
% In other words, we have three components in our functional group,
|
|
% and nine failure modes to consider.
|
|
% So taking each failure mode and looking at how that could affect the functional group,
|
|
% we must compare each failure mode against the two other components (the `$fgn-1$' term).
|
|
%
|
|
% For the one `zero' level FMMD case we are doing the same thing as FMEA type analysis
|
|
% (but on a very simple small sub-system).
|
|
% We are looking at how each failure~mode can effect the system/top level.
|
|
% We can use equation~\ref{eqn:fmea_state_exp44} to represent
|
|
% the number of checks to rigorously perform FMEA, where $N$ is the total
|
|
% number of components in the system, and $cfm$ is the number of failures per component.
|
|
|
|
|
|
%
|
|
% Where $N=3$ and $cfm=3$ we can see that the number of checks for this simple functional
|
|
% group is the same for equation~\ref{eqn:fmea_state_exp22}
|
|
% and equation~\ref{eqn:anscen}.
|
|
% \clearpage
|
|
|
|
%\section{Example}
|
|
\begin{frame}
|
|
\frametitle{FMMD - Failure Mode Modular De-Composition}
|
|
To see the effects of reducing `state~explosion' we can use an example.
|
|
% with fixed numbers
|
|
%for components in a functional group, and failure modes per component.
|
|
Let us take a system with 4 levels (with a top/system 0 level),
|
|
with three components per functional group and three failure modes per component,
|
|
and apply these formulae.
|
|
Having 4 levels (in addition to the top zero'th level)
|
|
will require 81 base level components.
|
|
|
|
$$
|
|
%\begin{equation}
|
|
\label{eqn:fmea_state_exp22}
|
|
81.(81-1).3 = 19440 % \\
|
|
%(N^2 - N).cfm
|
|
%\end{equation}
|
|
$$
|
|
|
|
$$
|
|
%\begin{equation}
|
|
% \label{eqn:anscen}
|
|
\sum_{n=0}^{4} {3}^{n}.3.3.(2) = 2178
|
|
%\end{equation}
|
|
$$
|
|
\end{frame}
|
|
|
|
|
|
\begin{frame}
|
|
\frametitle{FMMD - Failure Mode Modular De-Composition}
|
|
Thus for FMMD we needed to examine 2178 failure~modes against functionally adjacent components, and for traditional FMEA
|
|
type analysis methods 19440.
|
|
% In practical example followed through, no more than 9 components have ever been required for a functional
|
|
% group and the largest known number of failure modes has been 6.
|
|
% If we take these numbers and double them (18 components per functional group
|
|
% and 12 failure modes per component) and apply the formulas for a 4 level analysis
|
|
% (i.e.
|
|
|
|
\end{frame}
|
|
|
|
\begin{frame}
|
|
\frametitle{FMMD - Failure Mode Modular De-Composition}
|
|
|
|
Note that for all possible double simultaneous failures the equation~\ref{eqn:fmea_state_exp2} becomes
|
|
equation~\ref{eqn:fmea_state_exp2} essentially making the order $N^3$.
|
|
The FMMD case (equation~\ref{eqn:anscen2}), is cubic within the functional groups only,
|
|
not all the components in the system.
|
|
|
|
\begin{equation}
|
|
\label{eqn:fmea_state_exp2}
|
|
N.(N-1).(N-2).cfm % \\
|
|
%(N^2 - N).cfm
|
|
\end{equation}
|
|
|
|
\begin{equation}
|
|
\label{eqn:anscen2}
|
|
\sum_{n=0}^{L} {fgn}^{n}.fgn.cfm.(fgn-1).(fgn-2)
|
|
\end{equation}
|
|
\end{frame}
|
|
|
|
\begin{frame}
|
|
\frametitle{FMMD - Failure Mode Modular De-Composition}
|
|
\textbf{Traceability}
|
|
Because each reasoning stage contains associations ($FailureMode \mapsto Sypmtom$)
|
|
we can trace the `reasoning' from base level component failure mode to top level/system
|
|
failure, by traversing the tree/hierarchy. This is in effect providing a `framework' of the reasoning.
|
|
|
|
|
|
\end{frame}
|
|
|
|
\begin{frame}
|
|
\frametitle{FMMD - Failure Mode Modular De-Composition}
|
|
\textbf{Re-usability}
|
|
Electronic Systems use commonly re-used functional groups (such as potential~dividers, amplifier configurations etc)
|
|
Once a derived component is determined, it can generally be used in other projects.
|
|
|
|
\end{frame}
|
|
|
|
|
|
\begin{frame}
|
|
\frametitle{FMMD - Failure Mode Modular De-Composition}
|
|
\textbf{Total coverage}
|
|
With FMMD we can ensure that all component failure modes
|
|
have been represented as a symptom in the derived components created from them.
|
|
We can thus apply automated checking to ensure that no
|
|
failure modes, from base or derived components have been
|
|
missed in an analysis.
|
|
\end{frame}
|
|
|
|
|
|
|
|
\subsection{conclusion}
|
|
\begin{frame}
|
|
\frametitle{FMMD - Failure Mode Modular De-Composition}
|
|
\textbf{Conclusion: FMMD}
|
|
|
|
\begin{itemize}
|
|
\pause \item Addresses State Explosion
|
|
\pause \item Addresses total coverage of all components and their failure modes
|
|
\pause \item Provides traceable reasoning
|
|
\pause \item derived components are re-use-able
|
|
\end{itemize}
|
|
\end{frame}
|
|
|
|
\begin{frame}
|
|
\frametitle{FMMD - Failure Mode Modular De-Composition}
|
|
\textbf{Questions?}
|
|
\end{frame}
|
|
|
|
\end{document}
|