MIL-HDBK-1823A
"Nondestructive Evaluation System
Reliability Assessment"
mh1823 Site Map
Background
Overview:
MIL-HDBK-1823A tells how to plan an NDE experiment, design and
fabricate reliability demonstration specimens, acquire the system
performance data, and provides statistical methods for analyzing the
data to produce POD(a) curves, 95% confidence bounds, noise
analysis, and noise vs. detection trade-off curves. It presents
worked-out examples using real Hit/Miss and â data, and serves as a
user’s manual for the mh1823 POD software.
These methods are statistical best-practices and have universal applicability – NDE of engines, airframes, ground vehicles – subject to the following limitations:
- The NDE systems must produce output that can be reduced to either a quantitative signal, â, or a binary response, hit/miss. (Images therefore will require some pre-processing to provide either â or Hit/Miss as input to these analysis methods.)
- The specimens must have targets with measurable characteristics, like size or chemical composition. This precludes amorphous targets like corrosion unless a specific measure can be associated with it, such that other corrosion having that same measure will produce the same output from the NDE equipment.
- This mh1823 POD software assumes that the input data are correct. That is, if the size is X, then that is the true size. If the response is Y, then that is the true response. Situations where these conditions cannot be ensured (e.g. where target sizing is only approximate) will necessarily provide only approximate results. (The problem of accurate crack sizing is discussed in Handbook Appendix I.1 Departures from Underlying Assumptions – Crack Sizing and POD Analysis of Images.)
- This mh1823 POD software assumes that a POD curve goes to zero on the left, and to one on the right. Data for which min(POD) > 0 (perhaps due to signal contamination by excessive background noise), or max(POD) < 1 (resulting from random misses not related to target size) cannot be correctly represented by a model for which min(POD) = 0 and max(POD) =1. (See MIL-HDBK-1823, Appendix I-4 "Asymptotic POD Functions.") http://www.statisticalengineering.com/mh1823/QNDE/POD-floor-ceiling.htm
If the input data do not meet MIL-HDBK-1823 requirements, the mh1823 POD software may still produce an answer, but it will be WRONG.
History:
- Mid 1980s: A working group from the USAF, UDRI, GEAE, P&W, and Allied-Signal (now Honeywell), produced MIL-HDBK-1823, "Nondestructive Evaluation System Reliability Assessment." While it would be some years before an official publication was available, the draft became the de facto world standard for establishing quantitatively the effectiveness of inspections by measuring POD (Probability of Detection). (I was the primary author and overall editor of the first edition of MIL-HDBK-1823 also.)
- 1993: NATO AGARD (North Atlantic Treaty Organization, Advisory Group for Aerospace Research and Development) sponsored 2-day POD Short Course based on MIL-HDBK-1823 that I presented in Ankara, Turkey, Lisbon, Portugal, Patras, Greece, and Ottawa, Canada.
- Late 1990s: USAF officially publishes MIL-HDBK-1823, 30 April, 1999, and again in April 2004.
- Early 2000s: Model-Assisted POD - The MAPOD Working Group was formed in Austin in 2003 with impetus from James Malas, Ph.D., Chief, Nondestructive Evaluation Branch, Materials and Manufacturing Directorate, Air Force Research Laboratories.
- 2006: Under AFRL sponsorship work began to incorporate two decades of NDE progress in an update of MIL-HDBK-1823, including updated Probability of Detection (POD) software. The work was largely funded by USAF AFRL/MLLP, Nondestructive Evaluation Branch, Materials and Manufacturing Directorate, James C. Malas, Ph.D., Branch Chief, under Agreement: 06-S508-010-16-C1, Prime contract: F33615-03-D-5204. Special thanks to Charles Buynak, and to Jeremy Knopp who was the technical monitor. The work was completed in February, 2007.
- 7 April, 2009: The 2007 update was released by the USAF. Download a copy here.
NOTE: The mh1823 POD algorithms use R, the most powerful statistical
and graphics engine available anywhere, for all data manipulation,
statistical analysis, and graphics. Because R is open-source (and
free), and because all of the algorithms and methods developed here
are based on modern, well documented statistical best practices
described in the open literature, there is nothing proprietary in
this mh1823 POD software. Since there are no restrictions on its
use, the mh1823 POD software can be used as a universal standard for
performing Probability of Detection (POD) analysis.
Click here to see the mh1823 POD software version history.
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mail to:
Charles.Annis@StatisticalEngineering.com |