Probabilistic inspection strategies for minimizing service failures

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_ .................. _ _: _ __ Ap detected:

3

0.0100%

7

0.02333%

SELECTING

INSPECTION

The INSlM computer program minimize the probability be shown to demonstrate

STRATEGIES

USING

can be used to select of failure in service. this feature.

5.48

Percent

29309

Failures:

that will

45463

Max.

Number retired

aircraft:

7104

164488

Aircraft

4000

INSIM

inspection Several

strategies examples

101

The

Primary

Strategy

--

Damage-Tolerance

Methodology

The damage-tolerance regulations implicitly require the use of moderate stress levels and rationally determined NDI methods and intervals. This results in several benefits such as: long crack initiation lives, long crack growth lives, relatively large critical crack sizes and ample opportunities to detect cracks. Thus, damage tolerance methodology can be considered to be the primary strategy for minimizing service failures. Figure designed safe-life

I compares the to damage-tolerance requirements.

PROBABILITY

OF

probability of requirements

FAILURE

failure for a typical location compared to one designed to

(%)

100

10

m

J

14

0.1

0.01 f

0.001

DESIGN

O SAFE-LIFE

_

CRITERION:

DAMAGE-TOLERANCE

0.0001

2

1.5 MEAN

Figure

102

I.

Effect

of

mean

SERVICE

service

life

LIFE/

on the

DESIGN

probability

LIFE

of

failure.

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The safe-life requirements assume a mean crack initiation life of two design lifetimes and an inspection interval of half the design lifetime. Implementation of the FAR-25 damage-tolerance requirements resulted in a 21% reduction in allowable stress level and set an inspection interval of 20% of the design lifetime. Figure I shows that the probability of failure, for a mean service life equal to the design life, is 1.4% for the safe-life design while it is only 0.002% for the location designed according to the damage tolerance criterion. As the mean service life of the fleet increases, so does the probability of failure increase. Figure I indicates, for a mean service life equal to twice the design life, the probability of failure is 31% for the location designed to the safe-life criterion. The corresponding value for the location designed to be damage-tolerant is only 0.04%. There is a commonly expressed belief that a structure, designed to the damage-tolerance requirements, is not affected by an extension in service life, since the assumed fatigue damage reverts to a predetermined value after each inspection that did not detect a crack. If this is true, there need not be any limitations on the acceptable service life of an aircraft. Even without considering corrosion damage, which is time dependant, the total life view of INSIM shows that this premise is not true, and the probability of failure increases with increased service life. This is obviously due to the fact that, for the overwhelming number of locations (more than 99%), aircraft can be expected to retire from service without any cracks being detected, as is shown in Table 2. As the service life increases with respect to the design life, less aircraft retire without cracks being detected. Most of the difference is reflected by the number of cracks detected by NDI. However, it is inevitable that some of the difference is accounted for by unsuccessful inspections which lead to service failures. Therefore, it is clear that the probability of failure increases with service usage -- even in locations designed according to the damage-tolerance criteria.

TABLE

2. Typical

Distribution

OUTCOME

LOCATION

of

Possible

Outcome

MEAN SERVICE POSSIBLE

AT

1.0 Retired detection Crack Failure

from of detected

service crack by NDI

in service T 0 T A L

LIFE 1.5

at

/

a Location

DESIGN

LIFE 2.0

before 99.97%

99.73%

99.06%

0.03%

0.25%

0.90%

0.00%

0.02%

0.04%

100.00%

100.00%

100.00%

IO3

As usage severity increases, it can be expected that the probability of failure will increase. This is illustrated in Figure 2 for locations designed according to the safe-life and damage-tolerance criteria. Usage severity is characterized here by an increase in the spectrum stress level. As i's shown in Figure 2, under a 20% increase in usage severity, the probability of failure for the safe-life design can reach 55%. For the damage-tolerance design, even under these adverse conditions, the probability of failure only reaches 0.13%.

PROBABILITY

OF

FAILURE

(%)

100

10

0.1

0.01

0.001

DESIGN @ SAFE-LIFE

_

CRITERION: DAMAGE-TOLERANCE

0.0001 1

1.1

RELATIVE

Figure

2.

Effect

of usage

USAGE

severity

1.2

SEVERITY

on probability

of failure.

These studies, assisted by the INSlM program, demonstrate that the damage-tolerance methodology can be considered to be the primary strategy for minimizing service failures. As is shown in Figures I and 2, even under adverse conditions of extended service life and usage severity, reasonable probabilities of failures can still be achieved.

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