Synchrotron-based high-pressure research in materials science Page: 6 of 10
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7 DEVELOPMENT OF THE INITIAL
RELIABILITY CHARACTERIZATION
To develop component reliabilities for elements A,
B, and C, the estimates for IPTV at 12 months (un-
reliability) were first converted to reliabilities as
shown in Table 1. Estimates for A were then calcu-
lated using eq (1) and the estimate for #, also shown
in Table 1. Curve fitting techniques were then used
to transform the uncertainty expressed in the expert
elicitations into distributional information for the
failure rate A. For component C, a distribution of
reliability at 36 months (that point being of interest
to the project team) was developed using a Monte
Carlo simulation of eq (1) and distributions for A, as
shown in Figure 2. Reliability distributions for
components A and B were also calculated in a
similar manor. Just as Monte Carlo simulations
were used to develop the reliability characteriza-
tions for elements A, B, and C, they are also used to
propagate the reliability characterizations through
to subsystem SS, as shown in Figure 2, and also to
the total system S, with the accuracy being depend-
ent on the number of simulations. For example,
subsystem SS is made up of components A and B in
a series reliability arrangement. The reliability of
subsystem SS is therefore the product of the com-
ponent reliabilities. The same technique may be
used to propagate the reliability characterizations
through to the system level, as shown in Figure 3.
Note also in Figure 3 that the calculation of reli-
ability distributions at various times is also straight
forward.
With regard to element MP, curve fittingtechniques were again used to transform the uncer-
tainty expressed in the expert elicitations regarding
first time through defects, Table 2. That distribution
was also scaled to represent the distribution of gen-
erated defects, the most likely value of which (in
PPM) is also shown in Table 2.
The manufacturing process impact on prod-
uct reliability is represented by a distribution made
up of samples from both of the aforementioned dis-
tributions. The proportion of each is determined by
the estimate of "spill", or the period during which
process inspections are not functioning as intended.
The spill percentage is calculated from the estimate
of the frequency of spills and their estimated dura-
tion, as shown in Table 2.
The #3 and A parameters for the defect sub-
population generated by this manufacturing process
are calculated from eq (1), and the estimates (Table
2) of failed product at time zero, and the length of
time at which the entire subpopulation is estimated
to have failed (two equations in two unknowns).
The impact of the manufacturing process on
product reliability, at 36 months in this case study,
is again developed using eq (1) and Monte Carlo
techniques, and shown in Figure 2. This informa-
tion is then available for further analysis, in the
same form as the reliability information developed
for components A, B, and C.
8 DESCRIPTION OF UPDATING
METHODOLOGY
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Synchrotron-based high-pressure research in materials science, article, Date Unknown; [Los Alamos, New Mexico]. (https://digital.library.unt.edu/ark:/67531/metadc927600/m1/6/: accessed March 28, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; crediting UNT Libraries Government Documents Department.