A Taxonomy of Performance Influencing Factors for Human Reliability Analysis of Emergency Tasks(1)

Journal of Loss Prevention in the Process Industries 16 (2003) 479495www.elsevier.com/locate/jlp

A taxonomy of performance influencing factors for humanreliability analysis of emergency tasks

Jae W. Kim, Wondea JungIntegrated Safety Assessment Division, Korea Atomic Energy Research Institute, P.O. Box 105, Yuseong, Daejeon, 305-600, South Korea

Abstract

This paper introduces the process for, and the result of, the selection of performance influencing factors (PIFs) for the use inhuman reliability analysis (HRA) of emergency tasks in nuclear power plants. The approach taken in this study largely consists ofthree steps. First, a full-set PIF system is constructed from the collection and review of existing PIF taxonomies. Secondly, PIFcandidates are selected from the full-set PIF system, considering the major characteristics of emergency situations and the basiccriteria of PIF for use in HRA. Finally, a set of PIFs is established by structuring representative PIFs and their detailed subitemsfrom the candidates. As a result, a set of PIFs comprised of the 11 representative PIFs and 39 subitems was developed. 2003 Elsevier Ltd. All rights reserved.

Keywords: Performance influencing factors; Performance shaping factors; Human reliability analysis; Human error analysis; Emergency operation;Accident management

1. Introduction

Computerized automation has been adopted in largeparts of modern industrial high-risk and complex sys-tems such as nuclear power plants, aircraft and chemicalplants. However, humans still play important roles invarious parts of the design, maintenance, operation andsupervision of such systems. All human activities perfor-med in those parts are influenced by given specific work-ing conditions or task situations, so-called context,which is comprised of the MTO (man, technology andorganization) triad (Dougherty, 1993; Hollnagel, 1998).

In human error analysis (HEA) (Kirwan, 1992a,1992b) or human reliability analysis (HRA) in safetyassessment, such conditions that influence human per-formance have been represented via several context fac-tors. These context factors are referred to by differentterms according to method: PSF (performance shapingfactors), PIF (performance influencing factors), IF(influencing factors), PAF (performance affectingfactors), EPC (error producing conditions), CPC(common performance conditions), and so on. The PSFs

Corresponding author. Tel.:+82-42-868-8886; fax:+82-42-868-8374.

E-mail address: [email protected] (J.W. Kim).

0950-4230/$ - see front matter 2003 Elsevier Ltd. All rights reserved.doi:10.1016/S0950-4230(03)00075-5

or PIFs are used as causes or contributors to unsafe,human actions in event analysis (Paradies, Unger,Haas & Terranova, 1993; Nakanishi et al., 2002), andalso give a basis for assessing human factors in safetyassessment (Hollnagel, 1998; Embrey, 1984).

HRA has been performed as part of the probabilisticsafety assessment (PSA) of large-scale systems, such asnuclear power plants. PSA is an approach that developsall the possible accident scenarios and evaluates theoverall safety of a system probabilistically using theevent tree (ET) and fault tree (FT) techniques. The acci-dent scenarios are composed of two failure components,i.e. human failure events (HFEs) and hardware(system/component) failure events. HRA takes part inestimating the probability of those HFEs. There havebeen various approaches for evaluating humanreliability. In general, those approaches can be classifiedinto two categories, i.e. those using timereliability cor-relation (Hannaman et al., 1984; Moieni, Spurgin &Singh, 1994; Kim and Ha, 1997) and those manipulatingPIFs (Embrey, 1984; Phillips et al., 1990; Gertman etal., 1992). For the methods using PIFs, some of themuse a set of PIFs in adjusting the basic HEP (humanerror probability) such as THERP (Swain and Guttmann,1983), HEART (Williams, 1988), CREAM (Hollnagel,1998), and others in producing HEP by rating and inte-grating PIFs such as SLIM (Embrey, 1984), STAHR

480 J.W. Kim, W. Jung / Journal of Loss Prevention in the Process Industries 16 (2003) 479495

(Phillips, Humphreys, Embrey & Selby, 1990), etc. Onthe other hand, recently developed methods such asCREAM, INCORECT (Kontogiannis, 1997) andATHEANA (US NRC, 2000) use PIFs in the qualitativeanalysis/assessment of overall working conditions orerror-forcing context, as well as in the quantificationof HEP.

Generally, PIF taxonomies are so developed as to besuitable for a specific purpose and application area. HRAmethodologies also have their own PIF taxonomies, orthe PIF sets considered for HRA are somewhat differentdepending on the developer or the analyst. This maycause some important problems. The first one is of thetrust between the HEP values calculated from differentmethodologies that use a different set of PIFs. Also,comparison between different HRA results would bemeaningless, and, in order to obtain error reduction mea-sures, different PIFs would be dealt with according tothe used method. The second problem may be applicablefor some methods with a limited number of PIFs. Theuse of a limited number of PIFs might not only causeanalysts to omit important error reduction measures, butalso make the contribution of human error to the overallsafety of a system to be assessed lower than reality. Thethird problem is that the definition and the specific itemsto be assessed for each PIF are deficient or different bymethod, which can cause an inconsistent assessment ofthe individual PIF between assessors and, accordingly,produce different HRA results.

In this study, we suggest a new PIF taxonomy forhuman error/reliability analysis of emergency and acci-dent management tasks in nuclear power plants, withconsideration of the above-described problems of theexisting PIF taxonomies. The approach taken in thestudy to achieve the goal is summarized as follows.

Firstly, approximately 220 PIFs are collected from theexisting PIF taxonomies and other literature, and thosefactors are collated into a new set of PIFs. Among them,HRA PIFs are examined for the characteristics and trendof selection and usage, and the insights from the examin-ation are considered in the development of the new tax-onomy.

Second, the principal context under which humanoperators respond to emergency and severe accident situ-ations is analyzed, and PIFs relevant to such situationalcharacteristics are selected from the full-set of PIFs col-lated in the first step.

Third, the criteria of the PIF sets to be adequate forHRA are described, and, on the basis of these criteria,the candidate PIFs selected in the second step arerescreened out and structured in a two-layer hierarchy,i.e. the representative PIFs and their subitems.

The paper is structured as follows according to theabove-described approach. Section 2 includes a briefreview of the existing PIF taxonomies, the full-set ofPIFs collated, and the characteristics and trend of the

HRA PIFs. In Section 3, the principal context affectinghuman reliability during accident management and theselection of PIFs based on the context is described. Sec-tion 4 provides the final set of PIFs structured based onthe criteria of a PIF sets for HRA. Finally, Section 5concludes the study with a summary and remarks.

2. Collection and analysis of the existing PIFtaxonomies

2.1. Review of the existing PIF taxonomies

Two types of PIF taxonomies were collected in thestudy: one is composed of the detailed set of PIF, whichwas mainly developed for human error/factor analysis,and the other is the PIF set for the use in HRA. The firstone is referred to as the full set PIF taxonomy. Seventaxonomies among the detailed PIF sets and 11 taxo-nomies in HRA methodologies have been reviewed inthis study. HRA taxonomies are categorized accordingto the type of use as below. A brief description on thereviewed taxonomies is provided in Table 1. The list ofHRA PIFs is shown in Table 2.

The taxonomies of full-set of PIFs

CSNI taxonomy (Rasmussen, 1981) THERP (Swain and Guttman, 1983) HEART (Williams, 1988) PHECA (Whalley, 1987) PSF taxonomy (Bellamy, 1991) Influencing factors (Gerdes, 1997) K-HPES (KEPRI, 1998).

The taxonomies for use in HRA

Quantification of HEP: SLIM (Embrey, 1984), PLG-SLIM (Chu et al., 1994), INTENT (Gertman et al.,1992), STAHR (Phillips, Humphreys, Embrey &Selby, 1990), and HRMS (Kirwan, 1997)

Analysis of errors of commission: Macwans PIF tax-onomy for errors of commission (Macwan & Mosleh,1994), Julius PIF taxonomy for errors of commission(Julius, Jorgenson, Parry & Mosleh, 1995), andATHEANA (US NRC, 2000)

Overall context assessment and error analysis: HRMS,CREAM (Hollnagel, 1998; Hollnagel, Kaarstad &Lee, 1999), and INCORECT (Kontogiannis, 1997)

Database for HRA: Taylor-Adams PSF taxonomy forCORE-DATA (Taylor-Adams, 1995), and RogersPSF taxonomy for CORE-DATA (Gibson et al.,1998).

481J.W. Kim, W. Jung / Journal of Loss Prevention in the Process Industries 16 (2003) 479495T

able

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able

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the

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asan

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al.,

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phre

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inID

Aar

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pres

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din

ahi

erar

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alst

ruct

ure

usin

gin

fluen

cedi

agra

m.

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Psar

eca

lcul

ated

ina

step

-wis

efa

shio

nto

the

top

hum

anev

ent.

Em

brey

&Se

lby,

1990

)H

RM

S(K

irw

an,

1997

)In

HR

MS,

task

sto

bequ

antifi

edar

eco

mpa

red

with

the

task

with

the

sam

eta

skty

pean

dw

itha

know

nH

EP

invi

ewof

PSF

profi

le.

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then

,th

eH

EPs

are

mod

ified

acco

rdin

gto

the

diff

eren

ces

inth

epr

ofile

sto

obta

inH

EPs

ofta

sks

tobe

quan

tified

.M

acw

ans

(Mac

wan

&M

osle

h,M

acw

ans

set

ofPI

Fsis

basi

cally

for

the

iden

tifica

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ofm

isdi

agno

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orer

rors

inin

tent

ion

form

atio

npr

oces

ses.

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aba

sic

mod

elof

hum

anbe

havi

or19

94)

innu

clea

rpo

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plan

ts,

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sum

esth

atin

tera

ctio

nsbe

twee

nan

oper

ator

and

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ant

occu

ron

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basi

sof

emer

genc

yop

erat

ing

proc

edur

es(E

OPs

).In

acco

rdan

cew

ithth

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,th

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mpo

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set

ofPI

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pris

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the

thre

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ts,

i.e.

oper

ator

,E

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and

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t.A

noth

erfe

atur

ein

Mac

wan

sis

that

PIFs

are

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sifie

din

toth

esc

enar

io-d

epen

dent

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that

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geas

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goes

onan

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ndep

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atis

irre

spec

tive

oftim

e.A

ssh

own

inT

able

2,m

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the

term

inol

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that

iscl

osel

yre

late

dw

itha

situ

atio

n.Ju

lius

(Jul

ius,

Jorg

enso

n,Pa

rry

&Ju

lius

reor

gani

zed

the

PIF

set

onth

eba

sis

ofth

eM

acw

ans

taxo

nom

y.In

the

sam

ew

ayas

Mac

wan

s,

PIFs

are

clas

sifie

din

toth

eco

ntex

t-in

depe

nden

tM

osle

h,19

95)

PIFs

and

the

cont

ext-

depe

nden

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Eac

hgr

oup

cont

ains

thre

esu

b-gr

oups

ofPI

Fs.

(con

tinu

edon

next

page

)

482 J.W. Kim, W. Jung / Journal of Loss Prevention in the Process Industries 16 (2003) 479495T

able

1(c

onti

nued

)

Met

hodo

logy

Des

crip

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EA

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98)

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lnag

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ctor

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esu

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betw

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asse

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ion

asw

ell

asth

equ

antifi

catio

nof

HE

P.IN

CO

RE

CT

(Kon

togi

anni

s,19

97)

Kon

togi

anni

sde

fines

PCs

(per

form

ance

cond

ition

s)as

asi

mila

rki

ndof

CPC

s.H

esu

gges

ts,

how

ever

,th

atPC

ssh

ould

beev

alua

ted

atea

chtim

ew

hen

situ

atio

nva

ries

ora

scen

ario

deve

lops

soth

atit

can

beap

plie

dto

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dyna

mic

risk

asse

ssm

ent

fram

esu

chas

the

dyna

mic

even

ttr

ee(A

cost

a&

Siu,

1993

),in

stea

dof

bein

gas

sess

edon

etim

eat

anea

rly

stag

eof

the

anal

ysis

.H

edi

dno

tin

clud

eco

mpo

site

fact

ors

such

asst

ress

,w

orkl

oad

and

task

com

plex

itysi

nce

thos

ear

eco

mbi

ned

effe

ctof

seve

ral

perf

orm

ance

cond

ition

s.T

aylo

r-A

dam

s(T

aylo

r-A

dam

s,T

heta

xono

my

ofPI

Fth

atT

aylo

r-A

dam

sde

velo

ped

aim

sto

beus

edas

aPS

Fan

alys

ism

odul

ein

CO

RE

-DA

TA

(com

pute

rize

dop

erat

orre

liabi

lity

and

1995

)er

ror

data

base

)w

hich

isa

hum

aner

ror

data

base

for

the

supp

ort

ofH

RA

.C

OR

E-D

AT

Aha

sth

eta

xono

mie

sfo

rfiv

ehu

man

relia

bilit

yre

late

del

emen

ts,

i.e.

exte

rnal

erro

rm

ode,

psyc

holo

gica

ler

ror

mec

hani

sm,

perf

orm

ance

shap

ing

fact

ors,

task

-equ

ipm

ent

taxo

nom

y,an

dhu

man

actio

nta

xono

my.

The

PSF

taxo

nom

yw

asde

velo

ped

base

don

PHE

CA

(Wha

lley,

1987

),T

HE

RP

(Sw

ain

&G

uttm

ann,

1983

),H

EA

RT

(Will

iam

s,19

88).

Rog

ers

(Gib

son

etal

.,19

98)

Aft

erw

ard

Rog

ers

deve

lope

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485J.W. Kim, W. Jung / Journal of Loss Prevention in the Process Industries 16 (2003) 479495

2.2. Development of a new full-set of PIF

Besides the 18 taxonomies described in the previoussection, other literature dealing with important influenc-ing factors related to team/organization behaviors havealso been included in the review. For instance, Jacobsand Haber (1994) describe organizational factors thatcan affect system safety, and Hollnagel (1998); Salas,Dickinson, Converse and Tannenbaum (1992); Xiao,Hunter, Mackenzie, Jefferies and Horst (1996), andUrban, Weaver, Bowers and Rhodenizer (1996) dealwith inter/intra team interaction. In addition to those,HRA practitioners opinions were also utilized to deriveimportant factors. Especially, factors related to systemdynamic features were much supplemented.

All the factors collected from the above-mentionedsources were collated into a new full-set PIF taxonomy.It is assumed that the context under which an operatingcrew should perform given tasks can be modeled as inFig. 1. According to the Fig. 1, the collated PIFs areclassified into four main groups: HUMAN, SYSTEM,TASK, and ENVIRONMENT. The boundary of eachgroup is defined as follows.

HUMAN: Personal characteristics and working capa-bilities of the human operator.

SYSTEM: MMI, plant hardware system, and physicalcharacteristics of the plant process.

TASK: Procedures and task characteristics requiredof the operator.

ENVIRONMENT: Team and organization factors,and physical working environment.

The four main groups are again divided into severalsubgroups. The final full set PIF taxonomy collated intothe new classification frame is shown in Table 3.

2.3. Principal trend in the use of PIF for HRA

This section presents the trend of the selection and thelevel of definition of PIFs for use in the HRA, as HRAmethodology develops.

Fig. 1. The task context of nuclear power plants.

Firstly, as HRA methodology has improved, variouskinds of factors have been considered. In early HRAmethods such as THERP, ASEP and HCR, a very limitednumber of PIFs were chosen. For the methods utilizingexpert judgment, such as SLIM and STAHR, team andorganization factors , in addition to individual factors ,could be included. In INTENT, safety culture was con-sidered as one of the important PIFs. Among the recentlydeveloped HRA methods, CREAM and INCORECTconsider team and organization factors , systemcharacteristics , and simultaneous goals/tasks asimportant factors for human error/reliability analysis,and furthermore, the meaning of PIFs becomes moreclearly defined than in the previous quantitative HRAmethods. ATHEANA suggests the plant conditions,including system dynamic conditions, as the constituentsthat create a situation in which human error is stronglylikely to happen, i.e. error-forcing context (EFC). Tosummarize the trend in the selection of PIFs for use inthe HRA, in the initial HRA methods, a few very limitedfactors such as individual factors , procedures , andMMI factors were considered in evaluating humanreliability. Gradually, as HRA method becomes sophisti-cated, the assessment of overall work context is emphas-ized for better analysis and prediction of human error.According to this trend, team and organization factors ,safety culture , plant dynamic features , and simul-taneous tasks/goals appeared as important factors whichshould be assessed.

Secondly, PIFs could be grouped as follows withrespect to the frequency they are used in HRA methods.

Factors that are used in the majority of HRA methods:training, experience, procedure, MMI/information,and time.

Factors that are moderately used in HRA methods:stress, workload, motivation, task complexity, simul-taneous goals/tasks, working condition, supervision,team factors, and communication.

Factors that are used in a minority of HRA methods:adequacy of resources, decision making criteria,response dynamics and system coupling, availabilityof equipment, trend and value of critical parameters,time of day, organization factors, task organization,and safety culture.

Thirdly, the terminology and meanings of the selectedPIFs became more specific and practical. Some of thefactors being used in HRA methods are comprehensivein the meaning of their terminology. For this reason, theassessment results between analysts could be differentbecause they assess the factors with their subjectivemeaning. Such factors, for instance, include stress, work-load, task complexity, safety culture, organization factor,etc. For such factors, it is recommended that more appar-ent terminology be used or that the meaning/assessment


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items be clearly defined so that the consistency betweenanalysts is maintained.

3. Situational characteristics during accidentmanagement

This section describes the situational characteristicsduring accident management (including emergencyoperation) in nuclear power plants. Based on thosedescriptions, performance influencing elements thataffect operator performance during accident manage-ment are determined. Behavioral, phenomenological,organizational and environmental characteristics havebeen examined based on the literature dealing with acci-dent management in nuclear power plants (KEPRI, 1997;Ha et al., 1997; US NRC, 1988).

Firstly, operators tasks required in accident manage-ment (AM) situations are composed of not simplemanipulative actions, but cyclic cognitive activities suchas detection, observation, diagnosis, evaluation, plan-ning, and decision-making. In performing such activities,

Table 4Sample tasks appearing in accident management guidance (adapted from WOG, 1994)

1. Evaluate the following negative impacts associated with implementing the strategy.Check the following two conditions, and if both conditions are satisfied, there will be insufficient injection source .Check if core has not been reflooded.Check the following condition: RWST level (L09)%.2. Evaluate mitigating actions.If there is a possibility of insufficient containment injection source, then evaluate the following mitigating actions.Evaluate the action of Increase RWST refill rateEvaluate the action of Control containment injection flowrate to maintain RWST water level greater than (L09)% .3. Evaluate the consequences of NOT injecting into the containment (Containment challenge due to Basemat Meltthrough, RPV failure maynot be delayed, Fission products from ex-vessel core debris, Consequences of HPME, Combustible gas generation due to CCI, Recirculationproblem)4. Determine if containment injection should be initiated by comparing the consequences of NOT injecting into the containment versus thenegative impacts of injecting into the containment.

Table 5The situational characteristics of AM tasks and related human factors

Situational characteristics under AM Human factors

Behavioral characteristics Cognitive activities (observation, diagnosis, Knowledge (training, experience)interpretation, planning, decision-making, etc.) Procedure

Manmachine interface

Phenomenological characteristics Dynamic evolution of plant systems Dynamic system statusMultiple events Multiple goals and tasks

Available time for task achievement

Organizational characteristics Inter-/Intrateam cooperation Team and organization factorsDecision-making from higher organizations Decision-making structure

Plant policy and safety culture

Environmental characteristics Local operation Task location and physical environmentHarsh environment

procedures, information, operator support systems, train-ing and experiences are crucial for the proper assessmentof plant dynamic situations and the appropriate planningof how to cope with the given situation. Some exampletasks appearing in accident management guidance areprovided in Table 4.

Secondly, as an accident scenario evolves, plant sys-tems and physical phenomena also change dynamicallyand multiple events can take place. Those complex and

Fig. 2. Emergency organizations and interactions between organiza-tions in nuclear power plant emergency situations.


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Fig. 3. Process of structuring PIFs relevant to AM situations.

Table 7An example of structuring sub-itemsprocedures

Full-set PIFs Sub-items

TASK TASKProcedures Proceduresavailability format or type qualitylevel of detailmargin on interpretationclarity of instruction and terminology level of standardization in use of terminologydecision-making criterion logic structure number of logical conditions (branches)number of simultaneous tasksadequacy of caution/warning

dynamic situations can be a critical influencing factorto operator performance. Multiple tasks, status of majorsystems and components, and temporal factors arerelated to this situational characteristic.

Thirdly, most of AM tasks require inter-/intra-teamcooperation and decision-making in higher-level organi-zations beyond individual execution as in normal oper-ation. Under those situations, various factors related toteam performance, decision-making structure in a teamor organization, and plant policy and safety culture can

be important contributors to task performance. Fig. 2shows the emergency organizations and interactionsbetween those organizations in nuclear power plants.

Fourthly, harsh working environments such as highradioactivity, high pressure/temperature, and potential ofhydrogen detonation, etc., may take place in some tasklocations. Such environmental features can be a directobstacle, i.e. limitation in accessibility, to task perform-ance.

Table 5 summarizes the situational characteristics ofAM tasks and related human factors. Candidate PIFs forstructuring to be fit for HRA are extracted from the full-set PIF taxonomy considering those situational charac-teristics and human factors relevant to AM. The list ofextracted candidate PIFs is shown in Table 6.

4. Structuring PIFs for human reliability analysis

The candidate PIFs for AM obtained in the previoussection should be reorganized to be appropriate for usein HRA. The structuring of PIFs was conducted on thebasis of the insights from the Section 2.3 Principal trendin the use of PIF for HRA. Fig. 3 shows the schematicrepresentation of the process to the construction of a setof PIFs for AM HRA. The PIFs relevant to AM situ-ations have firstly been selected from the full-set PIFtaxonomy, and those PIFs are grouped into ones with


Table 8A set of PIFs for human error analysis of AM tasks

PIF group Representative PIF Subitems

HUMAN 1. Training and experience Adequacy of training (frequency, recent training, fidelity of simulation program)Experiences/practices of real operating eventsLearning of the past events/experiencesCareer of the operators

TASK 2. Availability and quality of procedures AvailabilityFormat or typeClarity of instruction and terminologyDecision-making criterionLogic structure

3. Simultaneous goals/tasks Number of simultaneous goals/tasksPriority between goals/tasksConflict between goals

4. Task type/attributes Type of manmachine interactionDynamic/step-by-stepTask criticality/consequencesDegree of discrepancy with familiar tasks

SYSTEM 5. Availability and quality of information Information availability (instrumentation fail/stuck)Clearness of meaning (direct indication/interpretationrequired/ambiguous/unreliable information)Distinguishability of informationControl display relationships

6. Status and trend of critical parameters Value of critical parametersTrend of critical parameters (rate of change of critical parametersNumber of dynamic changing variablesDegree of alarm avalanche

7. Status of safety system/component Success/fail state of safety system/componentLevel of trust on the system/componentNumber of failed/stuck componentsPrevious operation history and current status of safety system

8. Time pressure Available time vs. required time

ENVIRONMENT 9. Working environmental features Task location: (MCR/local CR/local area)Accessibility

10. Team cooperation and communication Clearness in role/responsibility definitionDirection, type, method, protocolStandardization in instruction/information deliveryTeam collaboration/cooperationAdequacy of distributed workload

11. Plant policy and safety culture Plant specific prioritized (or preference for/objection to) goals/strategiesAttitude toward EOP/AMP trainingSafety/economy tradeoffRoutine violations

similar meaning. Then, considering the situationalcharacteristics of AM tasks and the criteria for use inHRA, the final taxonomy is systematized. The criteriafor the selection and structuring of PIFs for HRA areestablished as follows, considering the practical aspectsof HRA.

It should include all the important factors to assessoverall task context as comprehensively as it can.

It should not be overlapped between factors. It gave the keynote for selecting factors that directly

affect human error occurrences.


It selects the factors that could be reflected intohuman error/reliability analysis.

It selects the factors that are assessable in practice. The terminology should be as specific and practical

as possible so that the meanings of the terms mightbe easily understood.

According to these criteria, construction of the rep-resentative PIFs and their subitems was made using oneor mixed method of the following structuring processesby the property of each PIF. The first structuring methodis to use the full-set PIF taxonomy illustrated in Table7. Important subitems for the assessment of a PIF aremarked out from the given detailed items of a PIF. Thesecond method is to choose the representative PIF fromthe PIF group with similar meaning and to organize subi-tems. Thirdly, other factors from the literature and HRAexperts were also incorporated into those processes.

Through repetitive modification, the final set of PIFs,which is composed of 11 representative PIFs and theirsubitems, is presented in Table 8. The proposed tax-onomy will need a continual revision process in associ-ation with the methodology development.

5. Conclusions

In this paper, we introduced a process of the system-atic construction of PIF sets for the use in HRA in aspecific context, especially, AM situations (includingemergency operations) in nuclear power plants. In orderto achieve this goal, firstly, 18 existing PIF taxonomiesincluding the recently developed methods have been col-lected and collated into a new set of PIFs consisting ofapproximately 220 detailed PIFs. In particular, PIF taxo-nomies for HRA were analytically reviewed in view ofthe trend and characteristics of selection and use, andthe insights from the review were considered in thedevelopment of the new taxonomy. In order to reflectthe task context, situational characteristics during theAM realm in nuclear power plants were describedaccording to the behavioral, phenomenological, organi-zational and environmental characteristics. Based on thedescriptions, PIFs relevant to such situational character-istics were selected from the full-set PIFs and, finally,those were structured in a two-layer hierarchical formconsidering the practical aspects of the use of PIFs inHRA.

The proposed taxonomy could be used in the assess-ment of overall task context, prediction of human error,such as internal/external error modes, and quantificationof their probabilities, and so on. In order to use the tax-onomy in those areas, an appropriate analysis/assessmentframework should be developed. For example, thepsychological error mechanisms (PEMs) in human cog-nitive functions may help find a way to consider the PIFs

in a systematic manner. In accordance with the PEM,some PIFs may be directly causing factors and othersbe contributory or shaping factors to human error. Theproposed taxonomy would require continual modifi-cations in association with the development ofHEA/HRA methodology.

Acknowledgements

This research has been carried out under the NuclearR&D Program by MOST (Ministry of Science andTechnology), Republic of Korea.

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A taxonomy of performance influencing factors for human reliability analysis of emergency tasksIntroductionCollection and analysis of the existing PIF taxonomiesReview of the existing PIF taxonomiesDevelopment of a new full-set of PIFPrincipal trend in the use of PIF for HRASituational characteristics during accident managementStructuring PIFs for human reliability analysisConclusionsAcknowledgementsReferences

A Taxonomy of Performance Influencing Factors for Human Reliability Analysis of Emergency Tasks(1)

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