diff --git a/mybib.bib b/mybib.bib
index a23aeab..ffa716a 100644
--- a/mybib.bib
+++ b/mybib.bib
@@ -271,10 +271,12 @@ ISSN={Doi:10.1145/2330667.2330683},}
 
 
 @ARTICLE{fftoriginal,
- title={An Algorithm for the Mechine Calculation of Complex Fourier Series},
+ title={An Algorithm for the Machine Calculation of Complex Fourier Series},
  author={James W. Cooley and John W. Tukey},
  journal={Mathematics of Computation},
  year={1965},
+ 
+  
  volume={19},
  pages={297-301},
  publisher={American Mathematical Society}
@@ -483,6 +485,13 @@ Database
   YEAR =         "1991"
 }
 
+@ARTICLE{fmeca,
+  AUTHOR =       "United States DOD",
+  TITLE =        "MIL-STD-1629A: Procedure for performing a failure mode, effects and criticality analysis",
+  JOURNAL =      "United States Department of Defence",
+  YEAR =         "1980"
+}
+
 % $Id: mybib.bib,v 1.3 2009/11/28 20:05:52 robin Exp $
 @article{Clark200519,
 	title = "Failure Mode Modular De-Composition Using Spider Diagrams",
@@ -790,8 +799,8 @@ strength of materials, the causes of boiler explosions",
 
 @BOOK{mil1991,
   AUTHOR =       "United~States~DOD",
-  TITLE =        "Reliability Prediction of Electronic Equipment",
-  PUBLISHER =    "DOD",
+  TITLE =        "MIL-1991: Reliability Prediction of Electronic Equipment",
+  PUBLISHER =    "United States Department of Defence",
   YEAR =         "1991"
 }
 
diff --git a/related_papers_books/FMECA_Mil-Std-1629A.pdf b/related_papers_books/FMECA_Mil-Std-1629A.pdf
new file mode 100644
index 0000000..10346fe
Binary files /dev/null and b/related_papers_books/FMECA_Mil-Std-1629A.pdf differ
diff --git a/submission_thesis/CH7_Evaluation/copy.tex b/submission_thesis/CH7_Evaluation/copy.tex
index 8e04121..07e3958 100644
--- a/submission_thesis/CH7_Evaluation/copy.tex
+++ b/submission_thesis/CH7_Evaluation/copy.tex
@@ -1154,20 +1154,26 @@ $ \Omega(C) = fm(C) \cup \{OK\} $).
 
 The $OK$ statistical case is the (usually) largest in probability, and is therefore
 of interest when analysing systems from a statistical perspective.
+%
 For these examples, the OK state is not represented area proportionately, but is included
 in the diagrams.
+%
 This type of diagram is germane to the application of conditional probability calculations
 such as Bayes theorem~\cite{probstat}. 
-
-The current failure modelling methodologies (FMEA, FMECA, FTA, FMEDA) all use Bayesian
-statistics to justify their methodologies~\cite{nucfta}\cite{nasafta}.
+%
+The current failure modelling methodologies 
+(FMECA~\cite{fmeca}, FTA~\cite{nucfta}\cite{nasafta}, FMEDA~\cite{en61508}) 
+use Bayesian
+statistics to justify their methodologies.
+%
 That is to say, a base component or a sub-system failure
 has a probability of causing given system level failures\footnote{FMECA has a $\beta$ value that directly corresponds 
 to the probability that a given part failure mode will cause a given system level failure/event.}.
-
+%
 Another way to view this is to consider the failure modes of a
 component, with the $OK$ state, as a universal set $\Omega$, where
 all sets within $\Omega$ are partitioned.
+%
 Figure \ref{fig:combco} shows a partitioned set representing 
 component failure modes $\{ B_1 ... B_3, OK \}$: partitioned sets
 where the OK or empty set condition is included, obey unitary state conditions.
@@ -1193,7 +1199,8 @@ This would make it seemingly impossible to model as  `unitary state'.
 There are two ways in which we can deal with this.
 We could consider the component a composite
 of two simpler components, and model their interaction to
-create a derived component (i.e. use FMMD on the simpler components).
+create a derived component (i.e. use FMMD).
+%
 The second way to do this would be to consider the combnations of non-mutually
 exclusive {\fms} as new {\fms}: this approach is discussed below.