diff --git a/fmmd_concept/fmmd_concept.tex b/fmmd_concept/fmmd_concept.tex index 010568e..5488911 100644 --- a/fmmd_concept/fmmd_concept.tex +++ b/fmmd_concept/fmmd_concept.tex @@ -492,6 +492,11 @@ and the probablistic failure rate of each classification is represented by lambda variables (i.e. $\lambda_{SD}$, $\lambda_{SU}$, $\lambda_{DD}$, $\lambda_{DU}$). +\glossary{name={SD},description={Safe Detected; a SYSTEM level failure mode that is considered safe, and is detected by self checking mechanisms}} +\glossary{name={SU},description={Safe Undetected; a SYSTEM level failure mode that is considered safe, and is not detected by self checking mechanisms}} +\glossary{name={DD},description={Dangerous Detected; a SYSTEM level failure mode that is considered dangerous, and is detected by self checking mechanisms}} +\glossary{name={DU},description={Dangerous Undetected; a SYSTEM level failure mode that is considered dangerous, and is not detected by self checking mechanisms}} + Because it is recognised that some failure modes may not be discovered theoretically during the static analysis, the % admission of how daft it is to take a component failure mode on its own @@ -601,6 +606,7 @@ apply to an installed plant, i.e. a complete installed and working SYSTEM. SIL ratings for individual components or sub-systems are meaningless, and the nearest equivalent would be the FIT/PFD and SFF and diagnostic coverage figures.}. +\glossary{name={FIT}, description={Failure in Time (FIT). The number of times a particular failure is expected to occur in a $10^{9}$ hour time period.}} diff --git a/introduction/introduction.tex b/introduction/introduction.tex index 7959e66..4875097 100644 --- a/introduction/introduction.tex +++ b/introduction/introduction.tex @@ -15,9 +15,12 @@ The methodology developed was designed to cope with both the deterministic\footnote{Deterministic failure mode analysis traces failure mode effects} and probablistic approaches \footnote{Probablistic failure mode analysis tries to determine the probability of given SYSTEM failure modes, and pfrom these can determine an overall failure rate, in terms of probability of failure on demand, or failure in time (or Mean Time to Failure (MTTF).}. +\glossary{name={safety critical},description={A safety critical system is one in which its failure may result in death or serious injury to humans, an environemntal catastophy or severe loss or damage}} + \paragraph{Safety Critical Controllers, knowledge and culture sub-disiplines} The maturing of the application of the programmable electronic controller (PEC) +\glossary{name={PEC},description={A Programmable Electronic controller, will typically consist of sensors and actucators interfaced electronically, with some firmware/software component in overall control}} for a wide range safety critical applications, has led to a fragmentation of subdisiplines which speak imperfectly to one another. The main three sub-disiplines are Electrical, Software and Mechanical Engineering. @@ -31,6 +34,7 @@ For failure mode analysis a common notation, across disiplines is a very desirab tool. \paragraph{Safety Assessment/analysis of PEC's} +\glossary{name={safety assessment},description={A critical appraisal, typically following legal or formal guidelines, which will encompass design, and failure effects analysis}} For a anyone responsible for ensuring or proving the safety of a PEC must be able to understand the process being controlled, the mechanical and electrical sensors and actuators and the software. Not only must the @@ -238,6 +242,7 @@ a process of modularisation from the bottom~up. \end{list} \section{Safety Critical Systems} +\glossary{name={safety critical},description={A safety critical system is one in which its failure may result in death or serious injury to humans, an environemntal catastophy or severe loss or damage}} % %How safe is "safe"? %The word "safety" is too general—it really doesn't mean anything definitive. Therefore, we use terms such as safety-related and safety-critical. @@ -266,6 +271,8 @@ hours of operation} of operation or a given statistical failure on demand. This is the probablistic approach and is embodied in the European Standard EN61508 \cite{en61508} (international standard IOC1508). +\glossary{name={deterministic},description={Deterministic in the context of failure mode analysis, traces the causes of SYSTEM level events to base level component failure modes}} +\glossary{name={probablistic},description={Probablistic in the context of failure mode analysis, traces the probability of base level failure modes causing of SYSTEM level events/failure modes}} \paragraph{Deterministic safety Measures} The second philosophy, applied to application specific standards, is to investigate @@ -332,7 +339,8 @@ unhandled failures could create dangerous faults. %designed correctly no `undetected faults' should be present here. % \section{An Outline of the FMMD Technique} - +{\fmmdgloss} +%\glossary{name={FMMD},description={Failure Mode Modular De-Composition}} The FMMD methodology takes a bottom up approach to the design of an integrated system. % diff --git a/millivoltamp/millivoltamp.tex b/millivoltamp/millivoltamp.tex index 4eacd7d..1b9ae52 100644 --- a/millivoltamp/millivoltamp.tex +++ b/millivoltamp/millivoltamp.tex @@ -839,3 +839,6 @@ from an FMEA perspective as a component itself, with a set of known failure mode %\vspace{20pt} % %%typeset in {\Huge \LaTeX} \today +\glossary{name={FIT}, description={Failure in Time (FIT). The number of times a particular failure is expected to occur in a $10^{9}$ hour time period.}} + + diff --git a/pt100/pt100.tex b/pt100/pt100.tex index 6fc56f9..e96bcda 100644 --- a/pt100/pt100.tex +++ b/pt100/pt100.tex @@ -426,6 +426,9 @@ failure statistics we calculate the reliability of this circuit. The formula for given in MIL-HDBK-217F\cite{mil1991}[9.2] for a generic fixed film non-power resistor is reproduced in equation \ref{resistorfit}. The meanings and values assigned to its co-efficients are described in table \ref{tab:resistor}. +\glossary{name={FIT}, description={Failure in Time (FIT). The number of times a particular failure is expected to occur in a $10^{9}$ hour time period.}} + + \begin{equation} % fixed comp resistor{\lambda}_p = {\lambda}_{b}{\pi}_{R}{\pi}_Q{\pi}_E @@ -510,6 +513,8 @@ Thus thermistor, bead type, non military spec is given a FIT of 315.0 Using the RIAC finding we can draw up the following table (table \ref{tab:stat_single}), showing the FIT values for all faults considered. +\glossary{name={FIT}, description={Failure in Time (FIT). The number of times a particular failure is expected to occur in a $10^{9}$ hour time period.}} + @@ -840,6 +845,8 @@ because here we have found a fault that we cannot detect at this level. This means that should we wish to cope with this fault, we need to devise a way of detecting this condition in higher levels of the system. +\glossary{name={FIT}, description={Failure in Time (FIT). The number of times a particular failure is expected to occur in a $10^{9}$ hour time period.}} + diff --git a/related_papers_books/AIAA2010.pdf b/related_papers_books/AIAA2010.pdf new file mode 100644 index 0000000..88d4152 Binary files /dev/null and b/related_papers_books/AIAA2010.pdf differ diff --git a/related_papers_books/engineering_a_safer_world_NANCY_LEVESON_draft.pdf b/related_papers_books/engineering_a_safer_world_NANCY_LEVESON_draft.pdf new file mode 100644 index 0000000..09518c5 Binary files /dev/null and b/related_papers_books/engineering_a_safer_world_NANCY_LEVESON_draft.pdf differ diff --git a/style.tex b/style.tex index 2b94581..9d8e513 100644 --- a/style.tex +++ b/style.tex @@ -81,7 +81,9 @@ \newcommand{\pin}{\ensuremath{\stackrel{pi}{\longleftrightarrow}}} %\newcommand{\pic}{\em pure~intersection~chain} \newcommand{\pic}{\em pair-wise~intersection~chain} -\newcommand{\wrt}{\em with-respect~to} +\newcommand{\wrt}{\em with~respect~to} +\newcommand{\fmmdgloss}{\glossary{name={FMMD},description={Failure Mode Modular De-Composition, a bottom-up methodolgy for incrementally building failure mode models, using a procedure taking functioal groups of components and creating derived components representing them, and in turn using the derived components to crate higher level functional groups, and so on, that are used to build a failure mode model of a SYSTEM}}} + %----- Display example text (#1) in typewriter font diff --git a/survey/survey.tex b/survey/survey.tex index 0b2ab0b..39d0748 100644 --- a/survey/survey.tex +++ b/survey/survey.tex @@ -79,6 +79,12 @@ This means that each system level error (or undesireable event) requires its own This increases the amount of work to do, and in the case of updates to particular sub-systems, introduces the requirement to update every FTA tree modelling that sub-system. +From an FTA tree sets of base level events can be traced to SYSTEM level failures. +Thes are termed `cut sets'. A further refinement of this is the minimal cut set, +a reduced from of the `cut set' that contains the minimum number of base level +events to cause a particular SYSTEM failure. +\glossary{name={cut set}, description={A cut set in a fault tree is a set of base component failure modes, whose occurrence ensures that a TOP (or SYSTEM) event occurs} } +\glossary{name={minimal cut set}, description={A cut set in a fault tree that cannot be reduced (i.e. \textbf{all} the base component failure modes are required to cause the SYSTEM level event) } } \subsubsection{ FTA weaknesses } \begin{itemize} @@ -285,6 +291,9 @@ The following gives an outline of the procedure. FMEDA is a statistical analysis methodology and is used from one of two perspectives, Probability of Failure on Demand (PFD), and Probability of Failure in continuous Operation, or Failure in Time (FIT). +\glossary{name={FIT}, description={Failure in Time (FIT). The number of times a particular failure is expected to occur in a $10^{9}$ hour time period.}} + + \label{survey:fit} \paragraph{Failure in Time (FIT).} Continuous operation is measured in failures per billion ($10^9$) hours of operation. For a continuously running nuclear powerstation, industrial burner or aircraft engine @@ -333,6 +342,9 @@ if the SYSTEM error it is tied to is dangerous or safe. The decision for this may be based on heuristics or field data. EN61508 uses the $\lambda$ symbol to represent probabilities. +\glossary{name={Lambda $\lambda$},description={Failure rate is often denoted as Lambda ($\lambda$) }} + + Because we have statistics for each component failure mode, we can now now classify these in terms of safe and dangerous lambda values. Detectable failure probabilities are labelled `$\lambda_D$' (for @@ -366,6 +378,11 @@ $\lambda_{SD}$, $\lambda_{SU}$, $\lambda_{DD}$, $\lambda_{DU}$). These new failures are added to the model. %SD, SU, DD, DU. +\glossary{name={SD},description={Safe Detected; a SYSTEM level failure mode that is considered safe, and is detected by self checking mechanisms}} +\glossary{name={SU},description={Safe Undetected; a SYSTEM level failure mode that is considered safe, and is not detected by self checking mechanisms}} +\glossary{name={DD},description={Dangerous Detected; a SYSTEM level failure mode that is considered dangerous, and is detected by self checking mechanisms}} +\glossary{name={DU},description={Dangerous Undetected; a SYSTEM level failure mode that is considered dangerous, and is not detected by self checking mechanisms}} + With these classifications, and statistics for each component we can now calculate statistics for the diagnostic coverage (how good at `self checking' the system is) and its safe failure fraction (how many of its failures are self detected or safe compared to @@ -456,6 +473,8 @@ With one component failure mode per row, all the statistical factors for SIL rating can be produced\footnote{A SIL rating will apply to an installed plant, i.e. a complete installed and working SYSTEM. SIL ratings for individual components or sub-systems are meaningless, and the nearest equivalent would be the FIT/PFD and SFF and diagnostic coverage figures.}. +\glossary{name={FIT}, description={Failure in Time (FIT). The number of times a particular failure is expected to occur in a $10^{9}$ hour time period.}} + @@ -555,6 +574,9 @@ We can perform some tests that give us 60\% coverage etc \subsection{Diagnostic interval} Reducing FIT with detecting a fraction of the faults within an interval. Give formulas etc +\glossary{name={FIT}, description={Failure in Time (FIT). The number of times a particular failure is expected to occur in a $10^{9}$ hour time period.}} + + \subsection{Redundancy - Models} diff --git a/symptom_ex_process/algorithm.tex b/symptom_ex_process/algorithm.tex index 716742d..2e7a2f4 100644 --- a/symptom_ex_process/algorithm.tex +++ b/symptom_ex_process/algorithm.tex @@ -44,6 +44,7 @@ The attribute $\alpha$ can be used to track the level of fault abstraction of components in an FMMD hierarchy. Because base and derived components are collected to form functional groups, a hierarchy is naturally formed with the abstraction levels increasing with each tier. +\fmmdgloss %\FORALL { $c \in FG $ } \COMMENT{Find the highest abstraction level of any component in the functional group} diff --git a/symptom_ex_process/fmmd.tex b/symptom_ex_process/fmmd.tex index cde6fc6..0862c42 100644 --- a/symptom_ex_process/fmmd.tex +++ b/symptom_ex_process/fmmd.tex @@ -5,6 +5,7 @@ \section{Background:\\ FMMD outline} The symptom abstraction process described here, is a core process in the %Failure Mode Modular De-Composition +\fmmdgloss FMMD modelling methodology. FMMD builds a hierarchy of failure mode behaviours from the bottom up. To start with collections of base components are chosen to form functional~groups, which are analysed w.r.t. its failure mode behaviour. diff --git a/symptom_ex_process/introduction.tex b/symptom_ex_process/introduction.tex index 34775a4..9521060 100644 --- a/symptom_ex_process/introduction.tex +++ b/symptom_ex_process/introduction.tex @@ -24,6 +24,7 @@ ensure complete failure mode coverage. Because the process is bottom-up, syntax checking and tracking can ensure that no component failure mode can be overlooked. Once a hierarchy is in place, it can be converted into a fault data model. +\fmmdgloss % From the fault data model, automatic generation of FTA \cite{nasafta} (Fault Tree Analysis) and mimimal cuts sets \cite{nucfta} are possible. diff --git a/symptom_ex_process/topbot.tex b/symptom_ex_process/topbot.tex index c6d4f1e..70a9759 100644 --- a/symptom_ex_process/topbot.tex +++ b/symptom_ex_process/topbot.tex @@ -209,3 +209,14 @@ Base Component & Any bought in component, or \\ \caption{Symptom Extraction Definitions} \label{tab:symexdef} \end{table} + + + + +\glossary{name={system}, description={A product designed to work as a coherent entity}} +\glossary{name={sub-system}, description={A part of a system, sub-systems may contain sub-systems and so-on}} +\glossary{name={derived component}, description={A theoretical component, derived from a collection of components (which may be derived components themselves)}} +\glossary{name={functional group}, description={A collection of sub-systems and/or components that interact to perform a specific function}} +\glossary{name={symptom}, description={A failure mode of a functional group (of components), caused by a combination of its component failure modes}} +\glossary{name={base component}, description={Any bought in component, or lowest level module/or part}} +%\glossary{name={entry name}, description={entry description}}