GUIDELINES FoR DEVELoPMENT OF NDEAccEPTANcE CBtTEBtA

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Nordtest Project 141 5-98GuroEunes roR DevetopMENT oF NDE AccEprnruce CRreRtn

Page 5 of 191999-02-22

2.2 Symbols

x Defect size, also used for the combination of more size (e.g. height and length) and other

defect severity parameters (e.g. location), when relevant

xa Ælowable defect size

w(x) Defect severity, often an expression for the probability of a defect leading to failure

i Defect number suffixf(x) = dF(x/dx, defect distribution (often also commonly denoted defect probability denstty

function)F(x) Cumulative defect distribution, F(-) - 1

N Number of defects in an objectn(x) = N'f(x), defect densitY

N(x) - N.F(x), cumulative defect density

E NDE responseg(E;x) Response distributionG(E;x) Response cumulative distribution

& NDE sensitivity levelp Probability of detection, often p = p(x;l%), if detection when E>Eo then

p(x;Eo) = J e(E; x)' dE = I - G(Eo;x)Eo

A Acceptance criteria, often including definition of Eo

pr Probability of rejection, often p. = pr(x;A)pa = 1-p,, probabilitYof accePtance

ps Probability of false call per unit of object being examined (e.9. per m of weld) or related

to insignifi cant defects

C NDE cost element

Further information on the definitions and used symbols can be found in Chapter 4.

3. REF'ERENCES

These guidelines rely on the principles laid down in the following two documents and a cross-

reference is made to them on relevant topics not covered here:

1. Guidelines for NDE Reliability Determination and Desuiption Nr TscHN REPORT 394.

NonotBsr, Espoo, Finland. Approved 1998-04.

2. Guidelines for replacing NDE Techniques with One Another. Nr TBcUN REponr 300.

NoRprrsr, Espoo, Finland. Approved 1995-10.

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(iEa3e) ryrEdb

Nordtest Project 1 41 5-98Guroeurr.iEs roR DeveuopnrEi\,rr oF NDE AcceprnNce CRtrEnle

Page 7 of 191999-02-22

For defect sizes it might, dependant on application, be relevant to give absolute or relativedeviations.

4. 1.4 Acceptance criteria

Prirnary detection and characterisation is often followed by an assessment based on defectcharacterisation values, and acceptance or rejection based on set acceptance criteria. Usually the

main steps followed in formulating the acceptance criteria are:

1. Determination of an NDE sensitivity level to facilitate detection of all defects which might be

unacceptable

2. Formulation of the acceptance criteria themselves. This is usually done in terms ofrequirements to NDE indication and measured or recorded location, size (height and length)and defect type, which might be supplemented by a requirement to maximum allowablecumulative amount of defects.

4.1.5 Probability of rejection

After having applied the acceptance criteria an NDE system will have a certain probability ofrejecting a defect. If p,p(x) denotes the probability of a defect being rejected when it has beendetected (with a probability p), the total Probability of Rejection (PoR) for a defect amounts to

P'P.ld.

If rejection is based on sizing, sizing is done with a systematic error of e and a random error of 6with a cumulative distribution H(6) and rejection is based on measuring a size larger than xo, theprobability of rejecting a detected defect of size x amounts to

P,p(x)=l-H(xo-x-e)

By properly selecting xo it might be possible to achieve a PoR which is not significantly lowerthan the primary PoD for larger or more severe defects.

An illustrative comparison of PoD andPoR is shown in the left hand figure.

The probability of accepting a defect,the Probability of Acceptance (PoA),equals 1 minus PoR.

If NDE system and assessment

according to the set acceptance criteriaare seen as one total system, the PoDfor this total system is then equal tothe PoR. PoR can thus in many respectbe treated in the same manner as PoD.

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På96 9 of 191999-t2-22

T.6dnq obloct D.f.ctg NDEtechnlque Tectlno condldons NDE p€llonnel. Måt6dat(s)

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4-4 l)efect contents

The defects contained in an object is described by their number N and sizes (and other

characteristics) xr, x2, ..., xi, ..., xN, which can be descdbed by a fitted distribution function f(x).

For calculations averaging a quantity z(x) over all xi it can then in cases be convenient and

releyant to replace the su[unation over the xi by an integral over f(x) accoding to the following:

N

!z(x,) = N.Jz(x).f(x) dx

i=l o

when it is advantageous for analysis to assume a form of a defe{t size distribution, the lognormalor the Weibull distdbution might be suitable. For assumption on defect contents, previous

experiencg as also occasionally reported in open literatuF, from applications similar to the one

in question, can be used,

4,5 Defect severity information

An evaluation of defect severity should ideally yield an estimate for a defect of size (and othersignificant parameters) x in terms of a Fobability w(x) for leading to failure One should then

rclate to w(x) for fomulating NDE acceptance cdteria.

In most practical cases today (1999) this routc is, however, not followed, but an allowable defect

size x" calculated (or experimentally determined) based on certain assumptions and utilisingsafety factors on important defect significance input panmeters. Such a calculated allowableyalue will then correspond to a certain (mostly ulknown and low) probability for failure of

w. = w(xJ

xu and not w, will then in most cases be the quantity to relate to when formulating acceptance

criteria.

Nordlest Proisct 1 41 5-98GUIOELINES FOR DEVEIOruEMT OF NDE ACCEPIANCE CHIIERIA

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4.6 Effect of performing NDE

4,6. 1 Number of defects

When NDE is perfomed on an object and discrete acceptance criteda per æcorded indication are

used, then the defect content after NDE and corective actions is described by a defect density

n""""p,"d(x;A) = n(x) (1 - P(x;A))

when the initial defect density is n(x) and the acc€ptance criteria A. The total number of defectsrcmaining in the object is reduced ftom N to

N.**tA) = Jn*no(x;A).ax = Jn(x).(l-p.(x;A)).dx = N Jf(x)(1-p.(x;A)).dx00

whercas the number of rejected defects amounts to

N"j*d(A) = N-N*e,"d(A) = N' Jft x) p,(x;A) dx

4.6.2 Prcbabilitv of failure

If w(x) is the probability that a defect of size x may lead to an unacceptable condition, theprcbability that any ofN defects would lead to an unacceptable condition without NDE is

N

w" =l-II(1-w(x,))i=l

which yields

ln(t-wb) = ih(l- w1x,i)= N. jrlx;.tn(r -wix;).axi=l 0

w" = r - "-n[ir"fr - *t-, )) = r - "-n[N'

jit-l r"tr - *<"il a,.

)

After NDE and conective actions the probability that any defect would lead to an unacceptable

condition is reduced to

*<ot =,-",.0[ittl- w(x,).(1-p,(x,;Alil)= t-*n[N. j<-).h(l- w(x).(l-p,(x;A)).dx)

Nordtest ProFct t41 5,98GutDsLtNEs FoR DEvEr-opMEtFoF NDE AocEpTANcE CBrIER|a

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4,7 Acceptatrce and rejection

4.7. I Acceptance criteria development steps

On the steps to be undertaken during development of NDE acceptance criteria rcference is madeto Sections 4. I .4 and 6. 1 , l.

4.7.2 Probabilistic acceptance criteria

If Wo is an acceptable limit for the probability of failure of an object, the relation for W(A)deriyed at in Section 4.6.2 can, in principle, be used to tune the acceptance criteria A, so that

w(A)<wo

The problem with dircctly doing this is that neither the numbq of defects, N, nor theirdistribution f(x), or ever the type of distribution, Ne a prio'|kno.[n. An assessment would haveto be based on an assumed number of defects and an assumed distribution based on previousexperience.

If, however, the NDE performed would give information on the defect conteots of an object (seeSection 4.8) this relation could be used to determine whether an object is acceptable or not. Infact one would then not have to rely on Fedelermined acceptance cdteria, but decide on thesebased on the outcome of the llDE and the knowledge of defect seyedty. When following thisapproach, it would be advantageous to do the NDE with a high sensitivity to gain as muchinformation on the object as possible. The setting of the sensitivity would then have to beproperly balanced against the probability for false calls (see atso Section 4.9).

For certain applications, however, such a /atal evaluation ^pproaah

for an object is not practical,This applies for instance dudng offshore pipelaying, where a decision on the integrity of a weldhas to be decided upon before the weld is lowered onto the seabed, precluding an assessment ofthe pipeline as a whole for decision on acceptance or rejection. Fø this case a solution per weldhas to be sought.

If different parts numbercd I to m of an object have to be evaluated separately the individualprcbability of failure of part j, Wj, should, if Wo is the acceprable limit for the probability offailurc of the object, tulfil the condition

1-II(l-wr)<woFI

4.7,3 Deterministic acceptance criteria

If defect sevedty w(x) is not known from an Eryineering Critical Assessment (ECA), but only adetermined allowable defect size xn (see Section 4.5), it is very difficult to assess theprobabilities involved including the requirernents to PoD and PoR. It must, however, be assumedthat the failure probability related to x. is low and that the safety factors involved provide for anextra safety rnargin, allowing PoR values less than I (this should be known to personnelperforming the ECA), The assessment of PoD and PoR will then also be subject to anengineering judgment by an NDE expert. In general one should aim for high, but not

Nordl€rt Projecl l4ls-98GutoEuNEs FoR OEVEIoPMENT oF NDE AccEptaNcE CFTER|A

Pag€ 12 ol191æS-O2-22

unreasonabty high, Fobabilities. It is Factically difficult to document with sufficient confidencevalues above 80 - 90 % PoD or PoR. One altemative is !o show PoD values well above thoseachieved by an empirically accepted quality conhol NDE technique (see Chapters 5 and 6).

4.7,4 Volume effect

Frorn the fomulae for W(A) deducted in Section 4.6.2 arother, quite expected, observation isclearly evident: The largq the number of defects, or the larger the object, the larger is theprobability of failure, or, - many small defects can be as dangerous as one large one. This rofurzeelåct is usually completely disregarde4 when acceptance criteria are fomulated for individualdefects, but some common criteda contain a cumulative clause (e.g, the total length of defects ina specified length of weld shall not exceed a cedain value), taking this, at least partly, intoaccount.

4,8 Dcfect cont€nts determination

4.8. 1 Simplified aoproach

If ni is the number of observations of a quantity xi for i = l, 2, ..., n and the observed xis are allassuned to be outcomes of a distribution f(x), then the parameters of f(x) can, accoding to the

maximun likelihood principle,be detemircd, by maximizing the likelihood expression

flf(x,)'' or, equivalently, rnaximizing the expression !n,.lnf(x,)i=l i=l

If now NDE has rcyealed n defects of sizes xr, x2, ..., xi, ..., x, in an object and the conesponding,known probabilities of dete{tion are p(x) the estimated 'expected number' of defects of size xi isl/O(x), The parameters of an expe{ted defect size distribution f(x) can then be determined bymaximizing the expression

* lnf(x,)k p\-)

In padicular, the expected number of defects in the object becomes

N=$ I

?i p(x, )

4.8,2 Maximum likelihood estimation of detected distdbution

The density of defects detected during NDE should amount to

ni"*"d(x) = n(x) P(x)

and the total number of defects detected to

Nordl€st Proiect 141 5-98GutoEuNEs FoF DEVELopMENT oF NDE AccEpraNcE cRllERra

Påg€ 13 ol 191999-02-22

No"-* = Jn(x). p(x). dx = N .J(x). p(x).dx

with a coresponding distribution

r*."-c) = "(.). pGy'i"<fl nrel. uf = <"1 e@f i"K\. e@. d€

If the form of f(x) is assurned known, but with unknown pammeter, p(x) is known, and the NDEhas included sizing (and other characterization) giving the sizes xi b = 1,2,...,Naa-r"a), theparameters of f(x) can be determined by maximizing the likelihood expression

If the sizes xj have not been detemined by the NDE, a similar approach can be followed for theobserved NDE indications E (se€ the relation given in Section 2.2 baween PoD and thedistribution of NDE indications).

If only the form of p(x) is known (or assumed), but not its parameters, the maximum likelihoodprinciple can be used to detemine also these paranrete$.

If the number of NDE observatiom is low, or the number of parameters for determination high,the maximum likelihood principle will fail or give very inaccurate results, in which case othersolutions have to be sought.

4.8.3 Bayesian estirnation

As for maximum likelihood estirnation, the distribution type for f(x) is assumed known, whereasthe palametels of this distribution are unknown. The task is to estimate these distributionparameærs. For the purpose of estimating a parameter e in the density function f(x) of the defectsize x, it is assumed that e is a stochastic variable O with known distribution function Fo(o) andcoresponding density function fo(o) = dFe/do. Fo(e) is denoted thep/i,rr distribution of @ and isbased on prior knowledge and experience:

Fo(O) = Fo. p'i.i(Q) = P[O < 0]

The NDE leads to a set of observed defects. The information inherent in these observations isused in conjunction with the prior information about e to produce so-called Bayesian estimatesof g. Two cases are considered for the oulcome of the NDE:

(l) N observed defects: Xt = xt, N, = 12, ..., )(p = 1*

(2) No observed defects ('no findings')

The po.rteliol distribution of @ is a conditional distribution, - given the prior information and thesample data from the NDE:

N.* 1-

flrup.w)f [n€t.p(€t d€

Nordlest Proisct 141 5-98GUTDELTNES FoR DEVELoPMENT oF NDE AccEpraNcE CFrrERra

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For Case (l )i

r..n.**I0 )=p[o.e ltX, =x, nX, =11 6...^xN = xN )]=PP<O nX, =xr 61, =x, n...nX. =x.]

Plxr =xr ^x2 =x2 n...nX* = x*J

For Case (2):

r"",,,n.,(e)=rP<e lx < xol=p[o<e nx <

^o]P[x. *ol

Methods are available to calculate the probabilities in these expressions. Note that x0 is the

magnitude of a non-detectable defect, whose distribution is given by the probability of detection,p(x), which is assumed known.

The estimator 6 for 0 is chosen as the mean value of the posterior dist.ibution of O, hence forCase (1):

6 =E[@ l(x, = x, ^x, = x2 n...nX* = xp)l

and for Case (2):

6=s[olx<xo]

4,9 Cost-effectiveness evaluation

Important cost elements of NDE are:

Cses Costs of performing NDE per unit of object examined

Crar* Costs of one failureCx*6, Costs of one repair

The expected total costs related to NDE can then be represented by a cost function (here given ina simplified fashion) as function of NIDE efforts A (representative for applied acceptance criteriaincluding NDE sensitivity setting):

C(A) = m g*or14; * *'p(A) Cq.rd' + N(l-p(A)) CF"ib + m p,(A) CR'p,i'

N is here the number of defects in the object in question leading to failure, m the number of unitsexamined, p the PoR and p" the number of false calls per unit of object examined ('probability offalse calls').

For cost savings through NDE of course C(A) should be less than zero.

Nord!6st Proi€ct 141 5-98Gu]DELINES FoR DEVELoPIMENI oF NDE AccEPIANcE CF|T€RIA

Pago 15 ol 191999-02-22

{/l.a tnæasns inspscli@ enoæ

- - Costopinlm3lope

o co3t opliduin Polnr

If one for simplicity assume CNDE relativelyindependent of A. a suaighl forward minimi-sation of C yields an optimum NDE effort from

Cr.{,i.9'E

-9

å

dp=dp"

>0N CF,jr*" - CR u,*tv

Probåblllty of fals cåll

The optimal poilt with respect to inspectionefforts A can then be found in the NDEtechniques ROC (Receiver OperatingCharacreristics) diagram (left) showing pagainst p. with inspection efforts A as a

paramelgr. A problem met in this, and other,connection is that N in general is not known.

5. QUALITY CONTROL ACCEPTANCE CRITERIA

5.1 Introduction

Quality control NDE is aimed at checking whether an acceptable workmanship level is met ornot. If this workmanship level is not meq there is a chance, in the long run, to have unacceptabledefects introduced into the object(s) in question. violating the quality requirement shouldthereforc lead to corrective actions. This is often done as a punishment by forcing manufacturersand their personnel (welders, etc.) to do corrective actions by rcpair or replacement. Morcseldom the violation of the workrnanship standards leads to a fitness-for-purpose assessment ofthe findings made, which could avoid damaging repairs to be done.

Quality levels have often be€n developed over time, and are as such empirically based, often as

expreEsed by the used acceptance criteria fø traditional NDE techniques. Altematively anengineering judgement is used to define quality levels gxpressed by defect severity parameterslike size, type and location as is done in ISO 5817 / EN 25817 Atc-welded joihts in steel -Guidance on qualiE levels for imperfections. In both cases the quality level definition is thus

somewhat arbitrary. This fact can also be taken into account when formulating NDE qualityconfol acceptance criteria.

5.2 Principles

A quality or workmanship level is something that should be met on an 'average' in the long run.

The requirements to the applied NDE and acceptance criteda are thus also not more stringentthan to reject defects coresponding to the quality level on an average, i.e. in 5070 of the cases.

5,3 Formul&tion ofquality level NDE åcceptånce criteria

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Nordte6t Project 141 5-98GutoELrN€s FoF DEVELoPMENToF NDE AccEprANcE CRmRTA

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well above those aphieved by an empirically accepted quality control NDE technique (illustratedbelow). For sizing tolerances the 95 or 99 enor distribution quantile limits may be used.

Such fltness-for-purpose qiteria are often" as ar! additional safety measure, supplemented byspecific quality or workmanship cdteda to maintain weld quality at a prcdeftned, acceptablelevel. Violating these quality criteria may then lead to stricter acceptance criteria to be used forconsecutive welds until the weld quality has bee[ re-established.

Figures are given below illustrating the above approach, PoD adequacy and assessment of sizingaccuracies and limits.

80 100 120

ftofoct length [mml

6.3 Probåbilistic approaches

Probabilistic routines for developing optimised NDE fitness-for-purpose criteria may becomevery complicated (see Section 6.1) and are not yet (1999) fully developed in a simplified form,but approaches can be used or established based on the guidance given in Chapter 4, especiallySections 4.4 to 4.9 (see also Section 6,1.1). Corrunercially available probabilistic softw:repackages are available for doing the required calculations and optimisation. A description ofsuch software does, however, fall beyond the scope of these guidelines, and reference is made toappropriate literature on the topic, including information from relevant software companies.

14

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Er0E

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x50Allowable defoct 8iz6 llmlt t.om u" x 25rl mm6nglnoetlng crltlcal agg€ssmont 0.5 % slrolnor experiments Sutldcå dol6cl'

Ufferencæ larger than sizing accuracres

llon-allowable defect sizes

Accoptable defect sizes Allowebls defoct slzos

Norcltest Project 1 41 $98GUIDELINES FOR DEVELOPMEMT OF NDE ACCEPTANCE CRIEFIA

Page 19 of 19't99go2-22

Examples of reliability dataacceptance criteria for an

used for qualificationåutoDåted ultrasonic

end determination ofexamination system

PrcbaHlitv of dotecttonl-0-

coflparison of Radiography ardAIJT: Dri.cdon lf€cho >

-Rad'.sådiy FoDdm

-Rådiryolr' FoD @re G så%6iddE inn

i' ' F{iq@h, tuDoÆ mns 0,1

ttefect height lmml

Compafison of PoD cunes lor automated uhtdsonic etaaminølion (AUT) at aspecfud sensilivity level and rdiogaphy trdditionø y øccepled fot quølirycoflttol to show adeqaate ølttdsonic sensitivw.

. ToFD båsod obs6Mto.s

. Echo amplitudå båsod obsoMfons

-lvleasured Heisht= tleishl '

-950/0

qlantloln sitno omr di€rributon

- 990Å quanlil€ in sitno ercr

E

I

o

=

D€f€ct Height [mml

Sc.ttter plol showing ,tvw dqect heøht delørnited by autornøted ulttøsot icdat rhøtion against d6tructiveb, detqfiined heøha ø h øccarøcy lirnia used ladetømine,he Afercnce befitee a4c4ploble and alk*w!)Ie defecl sizes.

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