Reliability for NDT

Tutorial: POD Basic

POD data collection & analysis – Tools for beginners

June

200

9

4th European-American Workshop

on Reliability of NDE

4th European-American Workshop on Reliability of NDE - We.4.A.4

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w.ndt.net/index.php?id=

8327

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w.ndt.net/index.php?id=

8311

Introduction Round:- How are you involved with NDE reliability in your present role?

- What do you hope to accomplish in the next 6 months with the tools learned here?

Goals:

Comfortable using typical POD software and presentation tools

Can produce valid results Aware of sources of variation and mitigation steps

POD data collection & analysis – Tools for beginners

- Before the start: Background on NDE Reliability Measurement Practice

- Vetting and assessing existing databases of POD capability- Completing experimental gap analysis- Calibrations & transfer functions- Protocols for partial/full capability demonstrations- Quality checking the data- Selecting a model- Understanding capability relationships behind POD curves- Understanding & addressing experimental variation- Substantiating and presenting the results

Basics Roadmap –

Goal: 1/3 Orientation & Discussion, 2/3 Performing POD calculations

POD data collection & analysis – Tools for beginners- Before the start: Background on NDE Reliability Measurement

Practice- Vetting and assessing existing databases of POD capability- Completing experimental gap analysis- Calibrations & transfer functions- Protocols for partial/full capability demonstrations- Quality checking the data- Selecting a model- Understanding capability relationships behind POD curves- Understanding & addressing experimental variation- Substantiating and presenting the results

Basics Roadmap –

NDT Reliability - Background

Degree that an NDT system is capable of achieving its purpose regarding detection, characterization and false calls

– American European Workshop on NDT reliability 99 Quantitative measure of the efficiency of the NDT

procedure in finding flaws of specific type and size– Metals Handbook

Quantification

Ideally Cracks larger than a certain

size can be detected

Defect Size

Det

ect

No

Det

ect

Probability of Detection Reality

There is a probability of detection for every crack

NDT Reliability Measurement

POD - Probability of Detection- Is it an adequate representation ?

POFA - Probability of False Alarm- Equally important from economic consideration

ROC - POD vs. POFA- A measure of reliability

Coefficient of Contingency- A measure of individual performance

POD Curve (Safety)

Defect Size

POD

95% Confidencebound0.9

90/95 Crack size

POD = F(Finds)

ROC Curve (Economics)

PO False Call

PO T

rue

Call

> 80% Finds< 20% False calls

ROC = F(Finds, False Calls)

Coefficient of Contingency

Flawed Unflawed

Marked Finds (TP) False Calls (FP)

Not Marked Misses (FN) True no-calls (TN)

Coeff of Contingency = F (TP, TN, FP, FN)

Challenge

Human Factors Variables Identification Control Quantification

Operator-Equipment-Environment interaction

What Do We Need to Understand?

NDT is not viewed as a friend of production The program is in operational interest Identify and eliminate deficiencies in NDT system Ultimately operate ‘safer, cheaper, longer’

Popular Characteristics of POD

POD is Expensive Certified inspectors do not need POD Experienced and high salaried inspectors have better

POD 90/95 Crack size information is adequate Imp to find small flaws

How is the product of NDE measurement Engineering used?

Damage Tolerance Concept

Service

Dam

age

size

Opportunity for damage detection

Assumed detectable Damage size

Inspection Interval

Opportunity for damage detection

Poorer than assumed

Inspection Interval

Safe?

Better than assumed

Estimated tolerable damage size

Economic ?

Damage Tolerance Concept

Service

Dam

age

size

Tolerable damage

Inspection Interval

Detectable damage Assessed reliability

Opportunity for damage detection

Improved Reliability

Relation of system response to POD curve

50% POD “point”for an 83 unit decisionthreshold

50% POD “point”for an 129 unit decisionthreshold

Regression equation from A-hat.exe program

L. Schaefer – NIST 1998 A-E NDE Reliability

First things first!

POD data collection & analysis – Tools for beginners

- Before the start: Background on NDE Reliability Measurement Practice

- Vetting and assessing existing databases of POD capability- Completing experimental gap analysis- Calibrations & transfer functions- Protocols for partial/full capability demonstrations- Quality checking the data- Selecting a model- Understanding capability relationships behind POD curves- Understanding & addressing experimental variation- Substantiating and presenting the results

Roadmap Basics –

30 years of NDE Reliability studies

Step 1: Mimimize cost of knowledge acquisition by reviewing

literature first! NTIAC Karta MAPOD FAA-ETC Abundant peer reviewed NASA, DoD, EPRI data

Working with data sets:

Lets try a few!

Exercises1 Review POD Rev 3 user instructions Examine and plot in excel the data located under the

FPI directory (26 Perfect, L3NQ) of a-hat vs a data Prepare a separate sheet with the data transformed into

hit/miss (0, 1), based on “hit” = 30 Conduct a-hat vs a and pass/fail analyses with the

provided threshold information Compare & discuss results

Caution for Excel treatment of commas vs point! – Use whole numbers

Lets try a few!

Exercises2 Examine and plot in excel the data located under the ET

directory (26Parent) of a-hat vs a data Prepare a separate sheet with the data transformed into

hit/miss (0, 1) where “hit” = 100 Conduct a-hat vs a and pass/fail analyses with the

provided threshold information Discuss results

Lets try a few!

Exercises3 Examine and plot in excel the data located under the UT

directory (UT270) of a-hat vs a data Conduct a-hat vs a with the provided threshold

information Present & Discuss results

More or continue?

POD data collection & analysis – Tools for beginners- Before the start: Background on NDE Reliability Measurement

Practice- Vetting and assessing existing databases of POD capability- Completing experimental gap analysis- Calibrations & transfer functions- Protocols for partial/full capability demonstrations- Quality checking the data- Selecting a model- Understanding capability relationships behind POD curves- Understanding & addressing experimental variation- Substantiating and presenting the results

Roadmap Basics –

Gap Analysis –

We dove into the deep end, now lets reflect:What needs to be done now to assure the results are correct?Did we obey our process?Substantiating and presenting the results: Understanding & addressing experimental variation Calibrations & transfer functions Protocols for partial/full capability demonstrations Quality checking the data Selecting a model

NDT system performance

Knowledge on

reasons for the gap ?

Recommendactions

to bridge the gap

NDT system capability

Objective: Identify and Eliminate Deficiencies

Designed Experiment

Data base

ReliabilityInformation

Knowledge - a) System Capability, b) Improvement Avenues

ImprovedReliability

POD Analysis

RecommendedActions

Approach to Inspection Reliability

Classic POD Program

Advanced Reliability Program

What Constitutes an NDT System?

HumanApplication

Equipment

Environment

What Factors Influence the Most?

Human Factors Application condition, access, … Equipment sensitivity, resolution, complexity, … Process, Materials, … Interactions

Human Factors – still a challenge

Factors that impact inspector’s discrimination and decision-making ability Organizational Physical Mental

Training and skill level is a major factor Inspections with predictable outcome

Routine and monotonous

POD data collection & analysis – Tools for beginners- Before the start: Background on NDE Reliability Measurement

Practice- Vetting and applying existing databases of POD capability- Completing experimental gap analysis- Calibrations & transfer functions- Protocols for partial/full capability demonstrations- Quality checking the data- Selecting a model- Understanding capability relationships behind POD curves- Understanding & addressing experimental variation- Substantiating and presenting the results

Roadmap Basics –

What Constitutes an NDT System?

HumanApplication

Equipment

Environment

Typical NDT Assessment Program

Creation of specimens with defects Visit to an NDT facility Identification of a sample of inspectors Conduct of NDT on set of specimens Acquisition of inspection data Data analysis and POD plots

NDT Assessment Program Elements…and sources of variation

Facility Sampling Inspector Sampling Specimens Scheduling Inspections Data Acquisition Data Analysis Human factors

Specimens

Ideally, real parts with real cracks Typically, synthetic parts or a combination of real and

synthetic parts Configuration as close to critical inspections as possible Presentation as close to real situation as possible Special care in handling and maintenance

Specimens

Multiple identical specimens Mounted on framework (racks) with quick interchangeability

feature Multiple inspection sites per specimen Uniquely numbered for tracking Specimen inspection guideline similar to written procedures Routine surface cleaning process without damage

Specimen Defects

40-60 defects per set Most flaws in the zone of increasing POD

Preferred 10-90% Typically 1-99% (Hard to judge) Preferred size distribution linear on ‘log a’ scale

Flawed : Unflawed site :: 1 : 2.5-3 Well characterized initially and regularly For details refer to MIL-HDBK-1823

Specimen Fabrication

Raw Specimen Flaw growth Final shape and size Characterize and mark

Cracked Metal Specimens

Raw Specimen

SpecimenEDMThrough

Crack

Raw SpecimenSpecimen Crack

EDMRaw SpecimenSpecimen

EDM

Surface crack

Raw SpecimenSpecimen

EDMRaw SpecimenSpecimen

EDM

Corner crack

Raw Specimen

Specimen

Grip Area

Margin

Raw Specimen

Specimen

Grip Area

Margin

Corroded Metal Specimens

ASTM Standards

SpecimenCorrosionMachined

SpecimenRaw Specimen

CorrosionMachined

Specimen

Grip Area

Margin

Raw Specimen

Specimen

Grip Area

Margin

Environment

Painted

ExposedSpecimen

Grip Area

Margin

Raw Specimen

Specimen

Grip Area

Margin

Environment

Painted

Exposed

Response Matrix

Marked Presence or absence Size quantified

Flaw No Flaw

Marked Find False Call

Not marked Miss True no-call

Signal/noise Discrimination

Decision

Misses False Calls

SignalNoise

Signal amplitude

Prob

abili

ty

dens

ity

func

tion

Signal/noise Discrimination

Poor process/setupPoor DiscriminationPoor reliability

SignalNoise

Good procedure, equipment, … Inspector dependent reliability

Good

Poor Poor

SignalNoise

Data Analysis

Demonstration of capability at one crack length

Determination of POD function through single inspection of cracks covering a range of lengths

Estimation of POD function and confidence bounds through multiple inspections of cracks covering a range of lengths

Binomial Distribution Theory (Grouping)

Regression Analysis (Curve fitting)

Data Analysis

Two Steps Generate a point estimate of

detection probability for various crack lengths over a range of interest

Fit an appropriate curve that offers minimum deviation or maximum likelihood to the scattered data

Log-odds Model

−=−=

−−=

caxca

py

caeca

ln ; ˆlnln

;1

)( PODβα

v

Indi

cate

d cr

ack

leng

th (a

)

True crack length (a)

a vs. a Analysis

Consider a lognormal scatter in indicated crack length for various cracks lengths

POD is the probability of indicated crack length exceeding the threshold of detection

Requires quantification of signal leading to detect call

Threshold

True crack length (a)

POD

Experimental quality assessmentsExample One

Human Factors quantification in Eddy Current POD Study

Demonstration Study - Introduction

Protocol for Human Factors Quantification Field lab visited in Sept 2000 L8 with 3 DOE variables

Job Type (Part Time vs Full Time)Physical comfort (Comfortable vs Uncomfortable)Speed of inspection (Normal vs Accelerated)

Demonstration Study - Plan

Eddy Current specimen set (Mfg at SwRI) 15 specimens, 8 sites/specimen 30 cracks, 35-228 mil

15 inspectors (8 full time, 7 part time) 4 rounds per inspector

Uncomfortable/comfortable, normal/fast 58 inspections on 120 sites

Demonstration Study – Specimens

Demonstration Study - Inspections

Demonstration Study – POD Curves

Effect of Job Type on POD6 Part time inspectors, 24 inspections9 Full time inspectors, 34 inspections

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Crack Size (mils)

POD

Part time95%Full Time95%

Effect of Physical Comfort on PODUncomfortable Posture, 28 inspections

Comfortable Posture, 30 inspections

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Crack Size (mils)

POD

Uncomfortable95%Comfortable95%

Effect of Schedule Comfort on PODNormal speed, 29 inspectionsAccelerated, 29 inspections

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Crack Size (mils)

POD

Fast95%Normal95%

Demonstration Study – DOE Analysis

DOE Analysis100.0

-20.9

-8.4

6.5

-6.3

3.37.6

0.8

-40

-20

0

20

40

60

80

100

GM J P JP S JS PS E

Nor

mal

ized

90%

PO

D C

rack

siz

e

Example Study

Effect of Physical and Schedule comfort

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Inspector

Coef

ficie

nt

Uncomf-FastUncomf-NormalComf-FastComf-Normal

Indi

vidu

al P

erfo

rman

ce

Day-1

Day-2

Example Two

Considerations in FPI - POD

FPI - Reliability Formula Elements

IC - Chemistry, fluid mechanics AP - Material, surface condition, location HF - Contrast, spatial perception

FPI - Process parameters

FPI - Process parameters

FPI - A-hat vs a, or Pass/Fail?

Pass/fail model-program considerations Process and behavior must conform to model assumptions…. or

no result/non-sense result Asymptotic signal to noise

A-hat vs. a - Preferred Given

- Sufficient quantity of data - as few as 20 points- Measurable strength of response

At minimum, mean performance can be calculated

FPI - Calculations; misses and false call management

Effect of decision threshold changes; 5-30milsPenetrant POD performance as a function of decision threshold

0.00E+00

2.00E-01

4.00E-01

6.00E-01

8.00E-01

1.00E+00

1.20E+00

0.00E+00 5.00E-02 1.00E-01 1.50E-01 2.00E-01 2.50E-01 3.00E-01 3.50E-01 4.00E-01

flaw length (in.)

POD

FPI - Source data from flat platesra001 0.023 0.025ra001 0.115 0.125ra001 0.069 0.07ra003 0.086 0.13ra003 0.065 0.1ra003 0.036 0.03ra003 0.095 0.1ra004 0.086 0.11ra004 0.11 0.115ra004 0.096 0.105ra004 0.05 0.055ra004 0.02 0.015ra004 0.03 0.03ra005 0.026 0.025ra005 0.072 0.085ra005 0.036 0.03ra005 0.102 0.1ra005 0.094 0.1ra006 0.088 0.1ra006 0.076 0.08ra006 0.044 0.05ra006 0.118 0.115ra007 0.067 0.065ra007 0.075 0.07ra007 0.106 0.115ra007 0.082 0.09ra007 0.016 0.002ra008 0.097 0.09ra008 0.017 0.02ra008 0.041 0.035ra008 0.057 0.04ra008 0.119 0.13ra009 0.074 0.075ra009 0.118 0.115ra009 0.027 0.02ra011 0.042 0.055ra011 0.026 0.03ra011 0.028 0.025ra011 0.07 0.075ra012 0.048 0.045ra012 0.04 0.035ra012 0.111 0.115ra012 0.071 0.08ra012 0.088 0.09ra013 0.036 0.03ra013 0.032 0.025ra013 0.019 0.002ra013 0.036 0.002ra014 0.082 0.085ra014 0.03 0.025ra015 0.07 0.07ra015 0.016 0.002ra015 0.034 0.025ra015 0.068 0.075ra015 0.089 0.075

AP - Isolating chemical parameters...

Influences of FPI parameters using flat panels

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0 2 4 6 8 10 12 14 16

Set "A" of NASA-SSME panels used for all exams. Panels include 56 cracks on 15 4"x15" panels (both sides). Size .016" to .118 (.361

extraneous, non-verified flaw)

A-h

at 9

0/95

CIF

(nde

) len

gth

(inch

es)

L 3 W-W A-NQ

L3 W-W AB-NQ

L 4 PE AB-NQ

TL-KN

L4 WW AB-NQ

L3 WW DP

Linear (L3 WW DP)

Linear (L3 W-W AB-NQ)

Linear (L 3 W-W A-NQ)

Linear (L4 WW AB-NQ)

Inspector

-& Group performance...

FPI - Group performance expectations

Influences of FPI parameters using flat panels

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0 2 4 6 8 10 12 14 16

Inspector Group

A-h

at 9

0/95

CIF

(nde

) len

gth

(inch

es)

Example Three

Laser Methods - PODShearography

Application - Bonded Structures, types

Traditionally acoustic inspections UT, resonance, “tap”…

Lasers can sense, map bond related displacement

Engine EndClose-out

BaseClose-out

Thrust Ramp

EdgeAssembly

Ramp SupportStructure

Honeycomb is A-286, .032 facesheets over 1.4” thick .003-.004” core, .5x.2~” cell size. Core is perforated.

facesheet

liner

Shearography - What can we measure?

POD from X-33-LS-01Base Area Width Length

Flaw ID1 .25x.5 0.125 0.25 0.52 .25x.75 0.187 0.25 0.753 .25x1 0.25 0.25 14 .25x1.25 0.3125 0.25 1.255 .25x1.5 0.375 0.25 1.56 .25x1.5 0.375 0.25 1.57 .25x1.25 0.3125 0.25 1.258 .25x1 0.25 0.25 19 .25x.75 0.187 0.25 0.75

10 .25x.5 0.125 0.25 0.511 .2x.25 0.05 0.2 0.2512 .25x.25 0.0625 0.25 0.2513 .2x.25 0.05 0.2 0.2514 .25x.25 0.0625 0.25 0.2515 .2x.5 0.1 0.2 0.516 .2x.75 0.15 0.2 0.7517 .2x1 0.2 0.2 118 .2x1.25 0.25 0.2 1.2519 .2x1.5 0.3 0.2 1.520 .25x.25 0.0625 0.25 0.2521 .5x.5 0.25 0.5 0.522 .25x.5 0.125 0.25 0.523 .25x.75 0.1875 0.25 0.7524 .25x1 0.25 0.25 1

Shearography - A-hat vs a analysis

1st Cycle Braze Liner/Closeout Shearography POD(Valid for unbonds .2" and larger)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.0000 0.0200 0.0400 0.0600 0.0800 0.1000 0.1200 0.1400 0.1600 0.1800

Unbond Area (.2"x.2" Decision threshold)

PO

D

90/95=.104 sq. in.

1st Cycle Braze A-hat Scatter(168 responses)

y = 1.03xR2 = 0.7562

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4Area (sq. in.) - .2" min dim fwd>aft

Sh

earo

grap

hy r

esp

on

se

area (

sq

.in

.)

POD/MTD/Prod. Data Linear (POD/MTD/Prod. Data)

Comparing the old vs. the “challenger”

We can assess the discrete reliability as a function of decision threshold

Ultrasonic A-hat vs a for HC panel

1 2 3ap7 0.375 0.28 0.28 0.28ap8 0.25 0.16 0.16 0.12ap9 0.375 0.28 0.28 0.28ap10 0.25 0.12 0.12 0.12ap11 0.375 0.28 0.28 0.28ap12 0.25 0.2 0.16 0.16ap13 0.375 0.32 0.28 0.24ap14 0.25 0.08 0.04 0.08ap15 0.375 0.28 0.28 0.28ap16 0.25 0.04 0.04 0.08ap17 0.5 0.4 0.44 0.44ap18 0.5 0.4 0.36 0.44ap19 0.5 0.4 0.4 0.4ap20 0.5 0.4 0.4 0.4ap21 0.5 0.4 0.36 0.4at01 0.1875 0.025 0.025 0.025at02 0.1875 0.025 0.04 0.04at03 0.1875 0.025 0.025 0.025at04 0.1875 0.025 0.025 0.025at05 0.1875 0.025 0.025 0.025at06 0.25 0.04 0.04 0.05at07 0.25 0.05 0.08 0.04at08 0.25 0.04 0.04 0.04at09 0.25 0.04 0.04 0.04at10 0.25 0.04 0.04 0.04at11 0.375 0.24 0.24 0.2at12 0.375 0.2 0.2 0.24at13 0.375 0.24 0.24 0.24at14 0.375 0.24 0.24 0.28at15 0.375 0.2 0.24 0.24at16 0.5 0.36 0.36 0.4at17 0.5 0.4 0.4 0.44at18 0.5 0.36 0.36 0.36at19 0.5 0.36 0.36 0.36at20 0.5 0.36 0.36 0.36ab11 0.375 0.04 0.04 0.04ab12 0.375 0.08 0.04 0.08ab13 0.375 0.12 0.12 0.12ab14 0.375 0.16 0.12 0.12ab15 0.375 0.16 0.12 0.12ab16 0.5 0.28 0.28 0.32ab17 0.5 0.2 0.24 0.2ab18 0.5 0.28 0.36 0.32ab19 0.5 0.28 0.24 0.28ab20 0.5 0.4 0.32 0.4bp01 0.25 0.04 0.04 0.08bp02 0.25 0.04 0.025 0.025bp03 0.375 0.16 0.24 0.2bp04 0.375 0.16 0.16 0.2bp05 0.5 0.32 0.36 0.4bp06 0.5 0.36 0.4 0.44bp07 0.375 0.24 0.24 0.2bp08 0.25 0.025 0.025 0.025bp09 0.375 0.2 0.24 0.28bp10 0.25 0.04 0.04 0.04bp11 0.375 0.28 0.28 0.2bp12 0.25 0.12 0.08 0.04bp13 0.375 0.28 0.28 0.28bp14 0.25 0.08 0.12 0.08bp15 0.375 0.24 0.24 0.24

Ultrasonic sca tte r da ta fo r .016"sk in, .1875" ce l l pane l

0

0.1

0.2

0.3

0.4

0.5

0.6

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Programme d Unbond D ime ns ion (inche s)

Me asure d Unbond D ime ns ion (in.)

T hre sho ld : 5x5 p ixe ls >= 6db

Shearography A-hat vs a for HC panel

1 2 3ap07 0.375 0.4942 0.4942 0.5295ap08 0.25 0.3353 0.3 0.3177ap09 0.375 0.4589 0.4589 0.4589ap10 0.25 0.3 0.3177 0.3177ap11 0.375 0.4589 0.4589 0.4942ap12 0.25 0.353 0.3 0.3353ap13 0.375 0.4412 0.4236 0.4412ap14 0.25 0.3177 0.3 0.3177ap15 0.375 0.3883 0.4236 0.4236ap16 0.25 0.353 0.353 0.3706ap17 0.5 0.5295 0.5471 0.5648ap18 0.5 0.6883 0.6883 0.653ap19 0.5 0.6177 0.5824 0.6001ap20 0.5 0.653 0.6883 0.6707ap21 0.5 0.5648 0.6001 0.5824at01 0.188 0 0 0at02 0.188 0 0 0at03 0.188 0 0 0at04 0.188 0 0 0at05 0.188 0 0 0at06 0.25 0 0 0at07 0.25 0 0.2824 0.2647at08 0.25 0 0 0at09 0.25 0 0 0at10 0.25 0 0 0.1765at11 0.375 0.3883 0.3883 0.353at12 0.375 0.4236 0.4589 0.4412at13 0.375 0.353 0.3883 0.3883at14 0.375 0.4942 0.5295 0.4942at15 0.375 0.4236 0.4765 0.4765at16 0.5 0.5824 0.5824 0.5824at17 0.5 0.6177 0.6177 0.6177at18 0.5 0.6177 0.6001 0.6001at19 0.5 0.5824 0.6354 0.6001at20 0.5 0.6001 0.653 0.6001ab11 0.375 0.3177 0.3353 0.2824ab12 0.375 0.3 0.2824 0.3ab13 0.375 0.3177 0.3177 0.3ab14 0.375 0.3706 0.353 0.353ab15 0.375 0.3353 0.353 0.353ab16 0.5 0.4589 0.4944 0.4589ab17 0.5 0.353 0.3706 0.353ab18 0.5 0.5648 0.5648 0.5471ab19 0.5 0.5118 0.5648 0.5648ab20 0.5 0.6707 0.653 0.653bp01 0.25 0 0 0bp02 0.25 0 0 0bp03 0.375 0.4236 0.4059 0.4236bp04 0.375 0.4589 0.3883 0.4059bp05 0.5 0.6001 0.5824 0.5824bp06 0.5 0.5824 0.6001 0.5824bp07 0.375 0.4942 0.4765 0.4942bp08 0.25 0 0 0bp09 0.375 0.4765 0.4765 0.4765bp10 0.25 0.2824 0.3 0.3bp11 0.375 0.5118 0.4942 0.4942bp12 0.25 0.2647 0.3117 0.2647bp13 0.375 0.4765 0.4765 0.4765bp14 0.25 0.2647 0.3 0.3bp15 0.375 0.4765 0.4942 0.4942

Shearography response scatter for .016" skin, .1875 cell panels

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

0 0.1 0.2 0.3 0.4 0.5 0.6

Programmed unbond dimension (inches)

Measured unbond (in.)

Example Four

Pressure Vessel PODUltrasonic & Eddy Current

PV-POD Using transfer functions to fill gaps

Often we are asked to develop POD… But we can not create perfect knowledge

Exact material Exact geometry The precise flaws expected in the design

- All orientations- All morphologies

How can we approximate what we do not know?

Pressure vessel POD - Transfer functions

Target application; 120mm welded vessel Internals are expensive, can’t afford false calls Thin - 1mm wall

Situation - Resources to assess with LCF cracks in flat plate - welded to spec

- Non-welded plate 5mm Automated UT & EC - Acquisition & Analysis EDM artifacts for all critical locations

Must estimate differences from lab to field

Transfer process

•Compare family of EDMs across thicknesses

•Compare family of EDMs across geometries & PM vs weld

PV - POD; Results ET

PV ET Scatter of Mean Responses for 26 Crack Sample

010000200003000040000

0 0.05 0.1 0.15

Crack Length (in.)

A/D

PV ET POD for Battery Parent Metal

0

0.5

1

1.5

0 0.01 0.02 0.03 0.04 0.05

Flaw Length (in.)

POD

(from 26parent.pod)

PV - POD; Results UT

Mean ultrasonic response versus length

0

200

400

600

800

1000

1200

1400

0 0.02 0.04 0.06 0.08 0.1 0.12

Crack Length (inches)

Amplitude (mv)

Discipline in calibration will assure estimate holds in practice!!

Example Five

Radiographic POD considerations

Radiography - HF dependant

Despite advances in image processing most applications rely on human interpretation

Detection targets include much beyond simple cracks of length and depth Pores, voids, cast shrink, honeycomb damage

WeldPM

How to achieve valid POD data for RT- without destructive sectioning of natural flaws?

Solution - Consensus evaluation of testset Inspectors differ on which are real flaws

24A/6R 21A/9R 16A/14R

Using baseline consensus to reduce variance Intersection of inspector agreement found valid in

Metallurgical assessment

21A/9R

24A/6R 16A/14R

Example Five

Variation AnalysisMeasuring known unknowns

All Solutions and POD analyses imperfect Control known knowns Measure known unknowns and account for in analysis

Example - EC inspection of aircraft lap splices-Per print fastners not all in a row

Off axis model Parse new peaks based on offset

Take the data and effort to understand what you can see varying…There will be plenty which you can not!

Summary: Sources of variation in NDE processes

“Tight” ellipse defines best practice for an NDE method against a defined flaw range Variation is the “enemy”, and is affected/controlled by:

•Use of transfer function•Master gaging•Quant. cont. resp. model

•Inspector decision variance•Insp. to insp. variance•Creeping procedural elegance

•Operator fatigue•Acquisition rate variance•Interpolation/rounding variance•“Snowflake” crack morphology

Flaw Size

Syst

em R

espo

nse

•Automated Calibration•Soft rule based decision systems•Automated data acquisition

Ensure you account for these in your POD demonstration!

Before the start: Background on NDE Reliability Measurement Practice

Vetting and assessing existing databases of POD capability Completing experimental gap analysis Calibrations & transfer functions Protocols for partial/full capability demonstrations Quality checking the data Selecting a model Understanding capability relationships behind POD curves Understanding & addressing experimental variation Substantiating and presenting the results

Summary & Closure

Feedback:

Did you achieve goals?

Comfortable using typical POD software and presentation tools

Can produce valid results Aware of sources of variation and mitigation steps

References/Resources

http://www.measuringusability.com/wald.htm http://www.causascientia.org/math_stat/ProportionCI.html http://stattrek.com/Help/Glossary http://www.statisticalengineering.com/ http://www.cnde.iastate.edu/MAPOD/ ASM NDT handbook Mil Std 1823 ASQ Reliability Engineering Bible Minitab SPlus R – Open source statistical software www.9095.net New release August 2009