Engineers responsible for life prediction and inspection of aerospace components are often tasked with demonstrating the capability of an inspection. It is extremely important to establish that the quality of the particular nondestructive inspection procedure is good enough to satisfy the safety requirements specified by the Federal Aviation Administration and/or the Military Organizations. The established and accepted metric for characterizing the capability of a nondestructive evaluation procedure is the probability of detection (POD) as a function of the crack size. Typically, such a demonstration requires the fabrication of a number of specimens with controlled, quantified defects or cracks. Engineers planning a demonstration need to know how many specimens they should include in the test plan. Determining the number of test specimens to be produced has been more guesswork than science. Producing arbitrarily a large number of defect specimens is not a good option because producing such defect specimens is a very costly activity in most cases. On the other hand, if too few defect specimens are produced in an unplanned way the assessment of the POD function will not be good. Therefore, it is important to use a sample of appropriate minimum size that still achieves the quantitative requirement for demonstrating the capability of a nondestructive inspection scheme. In this article, we will develop a simulation-based algorithm that will help users of the nondestructive evaluation procedures to choose an optimal sample size and a test plan such that the “standard” requirement is satisfied.
[1]
R. Cheng,et al.
One-sided confidence bands for cumulative distribution functions
,
1988
.
[2]
R. Durrett.
Probability: Theory and Examples
,
1993
.
[3]
A. P. Berens,et al.
Characterization of NDE Reliability
,
1982
.
[4]
William Q. Meeker,et al.
Probability of Detection Modeling for Ultrasonic Testing
,
1998
.
[5]
R. Cheng,et al.
Confidence Bands for Cumulative Distribution Functions of Continuous Random Variables
,
1983
.
[6]
William Q. Meeker,et al.
Applications of statistical methods to nondestructive evaluation
,
1996
.
[7]
E. L. Lehmann,et al.
Theory of point estimation
,
1950
.
[8]
Shuen-Lin Jeng.
Improved approximate confidence intervals for censored data
,
1998
.
[9]
A. P. Berens,et al.
Flaw Detection Reliability Criteria. Volume 1. Methods and Results.
,
1984
.