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Journal of Loss Prevention in the Process Industries 24 (2011) 90e97

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Journal of Loss Prevention in the Process Industries

journal homepage: www.elsevier .com/locate/ j lp

CREAM-based communication error analysis method (CEAM) for nuclearpower plant operators’ communication

Seung Min Lee a, Jun Su Ha b, Poong Hyun Seong a,*

aDepartment of Nuclear and Quantum Engineering, KAIST, 373-1, Guseong-Dong, Yuseong-Gu, Daejeon 305-701, South KoreabRisk Assessment Department, Korea Institute of Nuclear Safety (KINS), P.O.Box 114, Yuseong-Gu, Daejeon 305-600, South Korea

a r t i c l e i n f o

Article history:Received 23 April 2010Received in revised form1 September 2010Accepted 19 October 2010

Keywords:NPPsCommunication errorError analysis method

* Corresponding author.E-mail address: phseong@kaist.ac.kr (P.H. Seong).

0950-4230/$ e see front matter � 2010 Published bydoi:10.1016/j.jlp.2010.10.002

a b s t r a c t

Communication error has been considered a primary cause of many incidents and accidents in thenuclear industry. In order to prevent these accidents, a method for the analysis of such communicationerrors is proposed here. This paper presents a qualitative and a quantitative method to analyzecommunication errors. The qualitative method focuses on finding a root cause of the communicationerror and predicting the type of communication error which could happen in nuclear power plants. Wedevelop context conditions and antecedenteconsequent links of influential factors related to commu-nication errors. The quantitative analysis method focuses on estimating the probability of communica-tion errors. To accomplish the quantification of communication errors, the Cognitive Speaking Process(CSP) is defined and a method to estimate the weighting factors and the probability is suggested. Finally,case studies conducted to validate the applicability of the proposed methods are detailed. From theresults, we can foresee the effects of given plant conditions on communication errors and reduce theerror occurrences.

� 2010 Published by Elsevier Ltd.

1. Introduction

Communication error has been considered one of the maincauses of accidents and incidents in Nuclear Power Plants (NPPs).According to a study by Lee (2007), poor communication orcommunication error was a major or minor reason for incidentsfrom 2001 to 2007 in NPPs in Korea (20 out of 27 cases). Hirotsu,Suzuki, Kojima, and Takano (2001) reported that 25% of humanerror incidentsweredue to communication failure in JapaneseNPPs.

There are a lot of studies on communication failures and manyevaluation methods to improve communication. Berman andGibson (1994) reported a statistical analysis of accidents relatedto communication failure and they observed the frequent types ofcommunication failures and usual patterns of communicationgenerated in NPPs. Carvalho, Santos, Gomes, Silva Borges, andHuber (2006) provided advice for achieving effective humancooperation through an analysis of the communications amongcontrol room operators in NPPs. Min, Chung, and Yoon (2004)developed a standard communication protocol with a ComputerBased Procedure (CBP) situation in a Main Control Room (MCR). Inorder to evaluate the quality of communication among human

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operators in an MCR, Chung (2007) developed a communicationanalysis model and Kim, Park, and Jung (2008) proposed a quali-tative analysis method. These works provide considerable insightsinto the communication process and patterns in NPPs, and shouldhelp improve communication among operators. However, thesystems and procedures thus far defined cannot form a completesolution to prevent accidents or incidents related to communica-tion failure. Without an analysis of the root causes of miscommu-nication events, we cannot prevent these events and are limited inour ability to improve performance. Therefore, the identification offactors leading to communication error must be accomplished.Influential factors affecting communication errors should also beanalyzed.

To treat human performance in probabilistic risk assessment(PRA) and other applications, a diversity of human reliabilityanalysis (HRA) methods is available. Boring, Hendrickson, Forester,Tran, and Lois (2010) show examples of benchmarking study onvarious HRA methods. In this work, analysis methods to evaluateroot causes of communication error and to quantify the probabilityof communication errors are proposed. These methods areprimarily based on the Cognitive Reliability Error Analysis Method(CREAM).

The purpose of CREAM is to offer a bi-directional approach toboth performance analysis and prediction based on a well-con-structed model, causeeeffect relationships, and method. It is

S.M. Lee et al. / Journal of Loss Prevention in the Process Industries 24 (2011) 90e97 91

essential to acknowledge that any information processing andhuman actions are coupled and mutually dependent (Hollagel,1998).

By adopting an approach based on CREAM, this study can showthat the human communication process and human actions dependon the conditions under which the action takes place. Causeeeffectrelationships specified in communication can describe a largenumber of potential pathways through the use of classificationgroups. The Communication Error Analysis Method (CEAM), basedon CREAM, provides communication specified causeeeffect links toaccomplish communication error prediction and communicationerror-related accident analysis. Systematic analysis of erroneousactions due to communication failure and prediction of potentialcommunication errors can be conducted through CEAM.

This paper is organized as follows: Section 2 presents a qualita-tive analysis method for analyzing communication errors andprovides supporting case studies. Section 3 describes a quantitativeanalysismethod andprovides examples. Finally, Section 4 concludesthis paper with a summary and final remarks.

2. Qualitative analysis methods

To avoid communication error, a qualitative analysis method isused to analyze communication-related accidents and to find thereason for a given communication error. For such a qualitativeapproach, CREAM can be used both in a retrospective anda predictive manner. The retrospective method allows CREAM to beused for accident and event analysis. The purpose of the retro-spective method is to make a path of probable causeeeffect rela-tionships from the observed effect. The predictive methoddescribes how CREAM can be used for human reliability assess-ment. In this study, we use the retrospectivemethod tomake a pathof causeeeffect links and describe how CEAM method analyzescommunication-related accidents to find causes. The purpose ofapplying the predictive method is to describe which type ofcommunication errors can happen.

To build up communication specified causeeeffect links, manyinfluential factors based on the fields of ergonomics, communica-tion process, human reliability analysis (HRA) and accident analysisare added.

2.1. Descriptive modeling of human communication

The descriptive model of the human communication processdefines the elements involved in that process as the sender,the channel and the receiver (Richmond & McCroskey, 2009). Forthe encoding process at the sender and the decoding process at the

Fig. 1. Descriptive model

receiver, we can consider factors affecting each process. As shownin Fig. 1, arrows coming in and going out at each step of the processindicate the effect of influential factors that either increase ordecrease communication performance. For the encoding process,the H(XS|XE) factors, which are situation awareness, long termmemory (expertise) and stress (psychological state), attitude, timepressure can contribute to the success of the communicationprocess. Conversely, the H(XE|XS) factors, which are short-termmemory, mutual awareness and stress (psychological state), atti-tude, time pressure, can negatively affect this process. In fact, bothH(XS|XE) and H(XE|XS) may contribute to either the success orfailure of communication. For example, in the case of stress, toolittle stress makes humans feel indolent, while too much stressmakes humans feel fatigued. An appropriate level of stress,however, can make humans concentrate on their situation andwork (Swain & Guttman, 1983). Whether each factor ultimatelycontributes to good or bad human performance depends on envi-ronmental conditions. Therefore, an environment in which humancommunication is conducted should be analyzed to better under-stand this process.

2.2. Context conditions

The factors that influence human communication performancecan have different effects according to the prevailing environmentalcondition. Thus, in order to find the root causes of communicationerror, an evaluation of environmental conditions should be con-ducted. Environmental conditions are also emphasized in CREAMas a starting point of retrospective and predictive analysis. Propo-nents of CREAM provide 9 categorizations to evaluate the envi-ronmental conditions. For our purposes, we suggest contextconditions (CCs) based on CREAM as shown in Table 1. To tailorthese CCs for communication, we have edited the original CREAMcategory lists.

2.3. Communication error types in NPPs

Error modes denote particular forms of erroneous actions. Fiveerrormodes are defined and categorized as timing, acoustic feature,channel, contents, and sequence, while each error is classified intoone or more specific modes as shown in Table 2. Nine types ofcommunication errors are defined according to the error modes.

The message is sent at the wrong time. Communication fails if thesender transmits amessage to the receivereither tooearlyor too late.

The message is not sent at all. The sender fails to transmita message needed by the receiver (NUREG-1545, 1997).

of communication.

Table 1Context conditions and performance reliability.

Context condition Definition Level Performance reliability

Adequacy of organization The quality of the roles and responsibilities of team members,organizational characteristics, etc.

Very efficient ImprovedEfficient Not significantInefficient ReducedDeficient

Working condition The nature of the physical (ambient) working condition. Advantageous ImprovedCompatible Not significantIncompatible Reduced

Adequacy of equipments The quality of the communication-related devices. Supportive ImprovedAdequate Not significantTolerableInappropriate Reduced

Availability ofprocedure

The quality of the procedures. Appropriate ImprovedAcceptable Not significantInappropriate Reduced

Workload The number of tasks a person is required at the same time. Less than capacity ImprovedMatching current capacity Not significantMore than capacity Reduced

Available time The time available to carry out a task. Adequate ImprovedTemporarily inadequate Not significantContinuously inadequate Reduced

Time of day Disruption of the normal circadian rhythm or biorhythm. Adjusted Not significantUn adjusted Reduced

Expertise level The level of the expertise (training, experience, technologicalknowledge, etc.).

Adequate, high ImprovedAdequate, low Not significantInadequate Reduced

Crew collaboration quality The quality of the collaboration between crew members. Very efficient ImprovedEfficient Not significantInefficientDeficient Reduced

S.M. Lee et al. / Journal of Loss Prevention in the Process Industries 24 (2011) 90e9792

The message is sent with an uncommon acoustic feature. Thisoccurs when the sender fails to successfully transmit a message dueto inadequate volume, inadequate speed, or an uncommon accentfrom speaking with a particular dialect (Berlo, 1960).

The message is sent to the wrong place or person. This type offailure defines errors that range from the sender not knowingwhere or to whom a message should be sent, to simple mistakessuch as dialing the wrong phone number (NUREG-1545, 1997).

The message is sent through an inadequate route. The sendertransmits a message through an unofficial route (Berlo, 1960).

The message production is inadequate. When an accurate andcomplete message has been composed and tailored to the needs ofthe receiver, communication can still fail if the message is notadequately produced.

The message content is inappropriate for the receiver. The senderfails to tailor the message in terms of either the receiver’s workcontext, the receiver’s role for the task at hand, the receiver’s levelof technical knowledge, or the receivers familiarity with theterminology used in composing the message.

Table 2Error modes and error types.

Error modes Specific modes Definition of communication erro

Timing Too early Message is sent at the wrong timToo lateOmission Message is not sent at all.

Acoustic feature Uncommon Message is sent with an uncommfeature.

Channel Wrong direction Message is sent to the wrong plaWrong route Message is sent through inadequ

Contents Wrong terminology Message production is inadequatUnexpected contentsfor receiver

Message content is inappropriate

Unrelated contents Message content is wrong.Sequence Jump forward Message content is inconsistent w

information.RepetitionReversal

The message content is wrong. Communication fails because theinformation contained in the message is incorrect (NUREG-1545,1997).

The message content is inconsistent with other information. Theinformation in the message is correct but is partially or completelyinconsistent with other information available to the receiver(NUREG-1545, 1997).

For each error mode, root causes leading to the error modes arerelated to general antecedents. For example, the one or moregeneral antecedents among “inadequate timing,” “excessivedemand,” “memory failure,” “inadequate team characteristic” and“psychological stress” causes the timing error mode.

2.4. Antecedenteconsequent links

Antecedenteconsequent links are an essential part of thequalitative analysis method and are defined as causeeeffect rela-tionships between influential factors. Influential factors identifiedas causes in these links are also known as genotypes. According to

r type General antecedent

e. Inadequate timing, memory failure, excessive demand,inadequate team characteristic, psychological stress

on acoustic Psychological stress, physiological stress, functionalimpairment, uncommon linguistic expression

ce or person. Inadequate team characteristic, threaten, easygoingness,inadequate procedureate route.

e. Inadequate team characteristic, management problem,threaten, easygoingnessfor the receiver.

ith other Inadequate procedure, threaten, inadequate teamcharacteristic, psychological stress, easygoingness,management problem, inadequate team characteristic

Table 4Technology related genotypes.

Genotype General consequent General antecedent Specific antecedent

Equipment Equipment failure None defined Power failure,external impact

Procedure Insufficient writtenprocedure

None defined Insufficient ofmanagement ofprocedure

Wrong work methods None defined None definedInconsistent oralinstruction

Insufficient writtenprocedure

None defined

S.M. Lee et al. / Journal of Loss Prevention in the Process Industries 24 (2011) 90e97 93

CREAM, genotype is defined as a possible cause, such as the func-tional characteristics of the human involved in the incident, that isassumed to contribute to an erroneous action (Hollagel, 1998).

There are three such genotypes: person related genotypes, thetechnology related genotype, and the organization related geno-type. The person related genotypes defined in this work are plan-ning, temporary person related function, and permanent personrelated function.

The antecedenteconsequent links for the person related geno-types are described in detail in Table 3. The technology relatedgenotypes defined in this study contain the communication-relatedequipment and procedures shown in Table 4. Equipment failurerefers only to communication-related equipment failure. Thecontents irrelevant to communication are not considered. For thispurpose, the contents relevant to communication are added inorder to define what is meant by a procedure failure. Insufficientwritten procedure, wrong work method, and inconsistent oralinstruction can be considered, according to Kim et al. (2008). Theorganization related genotypes defined in this study are the orga-nizational structure, the expertise level of operators (NUREG/CR-1278, 1983), ambient conditions (the physical circumstance) (Kim,Lee, & Lee, 2006), and psychological working conditions (Hollagel,1998; Nadler & Tushman, 1980) including the social environment.In terms of organizational structure, a management problemmeansthat operators are not clear about their role and inadequate taskallocation means that the operators are not adequate for theirassigned duty. Other detailed links are shown in Table 5. In terms ofeach genotype, general consequent(s), general antecedent(s), andspecific antecedent(s) are identified. The general consequent is thecause of some events. The general antecedent is the cause thatresults in the general consequent. The antecedent and consequentlinks show that the general antecedent is replaced as the generalconsequent: i.e., this general consequent is set by the generalantecedent, resulting in another general consequent. The specificantecedent also causes the general consequent but is not set by thegeneral consequent for circulation: i.e., the specific antecedents arenot contained in the antecedenteconsequent links.

2.5. Case study

The proposed method was applied to a case study of an accidentrelated to communication error. Root causes of the error wereretrospectively identified using the proposed method.

The selected accident caused by communication errors is theDiablo Canyon PWR unit 2 residual heat removal failure that

Table 3Person related genotypes.

Genotype General consequent General antecedent

Planning Inadequate timing Distraction, memory failure, excprocedure, insufficient level of einsufficient level of technical kn

Temporary personrelated function

Memory failure Excessive demand

Boredom None definedEasygoingness Insufficient level of experience o

level of technical knowledgeIrritation Excessive number of peopleDistraction Adverse ambient condition, exceFatigue Adverse ambient condition, irregPhysiological stress Adverse ambient condition, fatig

excessive number of peoplePsychological stress Excessive demand, distraction, i

or training, insufficient level of tPermanent person

related functionFunctional impairment None definedLinguistic expression None defined

happened in 1987 (Berman & Gibson, 1994). The following is a briefexplanation of the accident.

At one stage an engineer opened a drain valve withoutinforming the control room. This led to an unexplained leakagefrom the control tank. Certain actions taken within the controlroom to correct this led to a gradual, undetected decrease in thereactor vessel water level. The loss of water level stopped theremoval of residual heat from the reactor. No decay heat removaloccurred for one and a half hours, during which the temperature ofthe vessel water increased from about 31 �C to 100 �C, with steamresulting from the open primary system.

For this accident, therewere two relevant communication errorsreported:

1. The control room operator tripped a pump prior to notifyingteam members of his intended action.

2. The informal communication route into and out of the controlroom was via a senior control room operator.

It was reported that the first error in this case was caused by thebreakdown of the teamwork concept (Berman & Gibson, 1994).Thus, this error is designated as a “message is not sent at all” errortype for the timing error mode. Through the relationship betweenerrormode andgeneral antecedent shown inTable 2, the inadequateteam characteristic is assigned to a “timing” error mode. Throughthe organization related antecedenteconsequent links shown inTable 5, it is decided that inadequate membership is the reason andthere are no more antecedent links for membership. It is thereforededuced that inadequate membership is the root cause in this case.It was further reported that the second error in the case was causedby the senior control room operator, who was accustomed to thework in NPPs (Berman & Gibson, 1994). Thus, this second errordesignated as a “message is sent through an inadequate route” error

Specific antecedent

essive demand, inadequatexperience or training,owledge

None defined

Temporary incapacitation, long time sincelearningMonotonous work, repetitiveness of action

r training, insufficient Conceit, overconfidence

None definedssive demand None definedular working time Exhaustionue, irregular working time, Lack of physical exercise, vigilance,

Exhaustion, time pressurensufficient level of experienceechnical knowledge

None defined

None definedInsufficient linguistic knowledge, uncommonlinguistic expression

Fig. 2. Prediction of the probability of CSP errors.

Table 5Organization related genotypes.

Genotype General consequent General antecedent Specific antecedent

Organizational structure Management problem None defined None definedInadequate task allocation None defined None definedSocial pressure None defined None defined

Expertise level Insufficient experience None defined None definedInsufficient training None defined None definedInsufficient technical knowledge None defined None defined

Ambient conditions Inadequate level of noise None defined None definedInadequate temperature None defined None definedInadequate humidity None defined None definedInadequate illumination None defined None definedInadequate level of vibration None defined None definedFar distance None defined None definedAdverse ambient conditions None defined Narrow space, high risk space

Working conditions Excessive demand Inadequate task allocation Unexpected task, sudden eventInadequate team characteristic None defined Membership, trust, forthrightnessIrregular working hours None defined Shift work, changing schedule, perseverance

S.M. Lee et al. / Journal of Loss Prevention in the Process Industries 24 (2011) 90e9794

type of the “channel” errormode. Through the relationship betweenerror mode and general antecedent, which is a starting point of theanalysis shown inTable 2, it is decided that easygoingness is the caseof this “channel” error mode. Furthermore, through the personalrelated antecedenteconsequent links fromTable 3, it is decided thatconceit is the reason and a specific antecedent. It is thereforededuced that conceit is the root cause in this case. This case studyillustrates the usefulness of the suggested analysis method.Although in this case the analysis method was applied to commu-nication errors in an NPP, all accidents related to communicationerror can be analyzed by the method.

3. Quantitative analysis methods

Amethod to predict the probability of speaking process errors isproposed in this section. The aim of this analysis is to evaluate theprobability of errors in the human cognitive function related tospeaking process. The process of the quantitative analysis is shownin Fig. 2. The assessment of CCs mentioned in the qualitativeanalysis is used for the quantification, because CCs also affectcognitive function failure.

3.1. Cognitive speaking process (CSP)

The CSP refers to the typical path from a planning process toa transmission process (Hollagel, 1998). The planning process is theprocess that creates the message. This process is divided into 3steps: macroplanning, microplanning, and grammatical encoding.In the macroplanning step, a sender determines the details ofa message by selecting which contents to express to realizecommunicative goals (Levelt, 1989). In other words, a senderdecides whether the intention of speaking is to give a question,command, or request for aid. The sender then decides who thereceiver is and the path for transmission. During this step, a speakerselects and molds the speaking content in such a way that theexpression of the content will be an appropriate means forconveying intention. In the microplanning step, a sender deter-mines the language which conveys the information (Levelt, 1989),i.e., one selects the relevant words, designations, and terminologyto implement a concrete message form. During this second step,a speaker brings all this speaking content into perspective,assigning topic and focus, and so on. In the grammatical encodingstep, a sender turns messages into audible speech (Levelt, 1989).Sentence structure is defined by arranging proper words gram-matically in this step. Through these three steps, a message isreadied for transmission to the receiver. This transmission process

builds the articulation plan for the utterance as a whole andconverts messages which are constructed in the planning processinto audible speech.

3.2. Errors in the cognitive speaking process (CSP) and nominalerror probability

In terms of the planning process, there are five error typeswhich are denoted in Table 6 as P1 through to P5, respectively.

These five error types occur when one or more steps of theplanning process have failed. For example, if a sender speaks to thewrong receiver, then this is considered as the sender misjudgingthe receiver: that is, the sender failed in the macroplanning step. Inthis case, the error type is P1- a message is sent to the wrong placeor person.

In terms of the message transmission process, there are threeerror types which are also denoted in Table 6 as T1, T2, and T3,respectively.

Each of the 8 types of errors occurs when the related CSP hasfailed. In order to quantify the probability of each error type,nominal probability values were evaluated by analyzing referencessuch as the Technique for Human Error Rate Prediction(THERP)(Swain & Guttman, 1983) and the Cognitive Reliability and ErrorAnalysis Method (Hollagel, 1998). The nominal probability values

Table 6CSP error types and nominal probability of CSP.

CSP Definition Cognitive speaking process error

Failure type Nominalvalue

Planning MacroplanningMicroplanningGrammaticalencoding

P1 Message is sent to thewrong place or person.

1.0E-3

P2 Message transmissionis inadequate.

1.0E-3

P3 Message productionis inadequate.

3.0E-3

P4 Message content is wrong. 5.0E-4P5 Message content is

inappropriate for thereceiver.

1.0E-3

Transmitting Articulation T1 Message is sent at thewrong time.

3.0E-3

T2 Message is not sent at all. 3.0E-2T3 Message content is

inconsistent contentwith other information.

3.0E-3

S.M. Lee et al. / Journal of Loss Prevention in the Process Industries 24 (2011) 90e97 95

have been defined in THERP as the Human Error Probability (HEP)when the effects of plant-specific performance shaping factors havenot been considered. In analogy with HEP, CREAM defined Cogni-tive Failure Probability (CFP) in order to assess the process ofcognitive failure they suggested.

The definition of CSP and its steps, the identification of errortypes and nominal CSP error probability are shown in Table 6.

3.3. Weighting factors for CCs

The speaking process is affected by the context as mentionedabove. The degree of the impact that the CCs have on the CSP errorshould be considered. In this section, the coupling relation between

Table 7Coupling relation and weighting factors on the CCs.

Context condition

CC name Level

Organization Very efficientEfficientInefficientDeficient

Working conditions AdvantageousCompatibleIncompatible

Equipments SupportiveAdequateTolerableInappropriate

Procedures AppropriateAcceptableInappropriate

Workload Fewer than capacityMatching current capacityMore than capacity

Available time AdequateTemporarily inadequateContinuously adequate

Time of day AdjustedUnadjusted

Expertise level High experienceLow experienceInadequate

Crew collaboration quality Very efficientEfficientInefficientDeficient

PR: Performance reliability, I: Improved, N: No significant, R: Reduced, S: Strong, M: MeThe scale of weighting factors is adjusted from CREAM (Hollagel, 1998).

CCs and CSP is defined. The coupling relation is categorized intothree grades: strong, medium, and weak.

A strong coupling relation means that the CC would exerta strong influence on cognitive function. Similarly, a weak couplingrelation means that the CC would exert a weak influence oncognitive function, and performance reliability is only weaklyimproved or is reduced. The coupling relation is determined amongthe 9 CC categories and the 2 CSPs. For example, the adequacy of theorganization has a strong coupling relationship to the planningprocess and a medium coupling relation to the transmissionprocess. The total set of coupling relations are shown in Table 7.

To quantify the probability of the CSP error type, the couplingrelation between the CCs and CSPs is assessed with weightingfactors. The weighting factors assigned to the expected effects ofthe CCs on the performance reliability and to the coupling relationbetween the CCs and the CSP are determined based on theassignments shown in Table 7.

In the case that the effect on performance reliability is notsignificant, the weight is specified as 1, meaning that the nominalprobability will not change. If the expected effect is improved, thentheweighting factor is specified as less than 1 and the probability ofthe CSP error is decreased to less than the nominal probability.When the expected effect is reduced, then the weighting factor isspecified as larger than 1 and the probability of the CSP errorincreases to greater than the nominal probability.

If the coupling relation is deemed as weak, the weight is spec-ified as 1. Medium and strong effects are given different numericalweights, where the scale of this difference is determined in accor-dance with CREAM.

For example, the adequacy of organization (the first CC) hasa strong coupling relation to the planning process. The weightingfactor is determined to be 0.5 when the expected effect on perfor-mance reliability is improved, and theweighting is determined tobe

CSP

PR Planning Transmitting

I S 0.5 M 0.8N 1.0 1.0R 1.5 1.2R 5.0 2.0I W 1.0 M 0.8N 1.0 1.0R 1.0 2.0I W 1.0 S 0.5N 1.0 1.0N 1.0 1.5R 1.0 5.0I S 0.5 M 0.8N 1.0 1.0R 5.0 2.0N S 1.0 M 1.0N 1.0 1.0R 5.0 2.0I S 0.5 S 0.5N 1.0 1.0R 5.0 5.0N M 1.0 W 1.0R 1.2 1.0I S 0.5 M 0.8N 1.0 1.0R 5.0 2.0I S 0.5 M 0.8N 1.0 1.0N 1.0 1.0R 5.0 2.0

dium, W: Weak.

S.M. Lee et al. / Journal of Loss Prevention in the Process Industries 24 (2011) 90e9796

ranged between 1.5 and 5.0 when the expected performance reli-ability is reduced. The values for all of the weighting factors areshown in Table 8. The error probability in CSP is quantified byconsidering both the weighting factors and nominal probabilitysimultaneously. The result of predictive analysis helps reduce thepossibility of error occurrences (Kim & Jung, 2002). Cepin (2008a)mentioned that only few human failure events dominate in theHRA. If the quantitative analysis of CEAM is applied to more cases,we can sort out a couple of significant CSP errors. Thenwe canmoreeasily foresee the effects of given plant conditions on humancommunication errors.

3.4. Application

The quantitative analysis method was applied to the DiabloCanyon PWR unit 2 residual heat removal failure described earlier.Two relevant communication errors were reported in that case:

1. The control room operator tripped a pump prior to notifyingteam members of his intended action.

2. The informal communication route into and out of the controlroom was via a senior control room operator.

The first communication error is deemed a “transmissionprocess” error, and a “message is not sent at all” error type, whilethe second is deemed a “planning process” error and a “messagetransmission is inadequate” error type. To assess the relevant CSPerror probability, the CCs should be selected for determination ofweighting factors.

The 9 CCs are assumed and shown in Table 8. For the planningprocess, the availability of procedures has a weighting of 5.0, theexpertise level is 0.5, crew collaboration quality is 5.0, and theremaining factors are all set to 1.0 because the coupling relation isweak or their assumed effects on the CCs are not significant. For thetransmission process, the availability of procedures has aweightingof 2.0, the expertise level is 0.8, crew collaboration quality is 2.0,and the remainder are all set to 1.0.

The total influence of CCs is determined by multiplying all theweighting factors, which yields a total influence if 12.5 for theplanning process and 3.2 for the transmission process (Williams,1988). When the combined weighting factors and the nominalprobability are taken into account, the adjusted probability thatcorresponds to the specifically assumed CCs can be found.

In the case of the first CSP error, the adjusted probability isestimated as 9.6E-2 when it takes into account the combinedweighting factor for the transmission process of 3.2 and thenominal probability for T2 (message is not sent at all) of 3.0E-2. Inthe second case, the adjusted probability is estimated as 1.25E-2 bytaking into account the combined weighting factor for the planningprocess 12.5 and the nominal probability for P2 (message trans-mission is inadequate) of 1.0E-3.

Table 8Assessment of the effect on the CCs.

Context condition Level Planning Transmitting

Organization Efficient 1.0 1.0Working conditions Compatible 1.0 1.0Equipments Adequate 1.0 1.0Procedure Inappropriate 5.0 2.0Workload Matching current capacity 1.0 1.0Available time Temporarily inadequate 1.0 1.0Time of day Adjusted 1.0 1.0Expertise level High experience 0.5 0.8Crew collaboration

qualityDeficient 5.0 2.0

Total influence of context condition 12.5 3.2

According to CREAM, the probability results are categorized intofour types and we can speculate the meaning of results. The esti-mated probability of T2 is included in high tactical and mediumopportunistic modes and that of P2 is included in medium tacticaland low opportunistic modes. Tactical mode has probabilityinterval from 1.0E-3 to 1.0E-1. In this mode performance is based onplanning, hence more or less follows a known procedure or rule(rule-based behavior). Opportunistic mode has probability intervalfrom 1.0E-2 to 0.5E-0. In this mode the person does very littleplanning because the context is not clearly understood or time istoo constrained. The rest of modes in CREAM are strategic andscramblemode. Strategic mode has probability interval from 0.5E-5to 1.0E-2. This mode provides a more efficient and robust perfor-mance. Scramble mode has probability interval from 1.0E-1 to 1.0E-0. In this mode the choice of next action is unpredictable orhaphazard. The extreme case of this mode is the state of momen-tary panic (Hollagel, 1998).

4. Conclusion

To prevent accidents related to communication errors in NPPs,we have proposed a qualitative analysis method and a quantitativeanalysis method to serve as systematic analysis tools. CEAM targetsthe analysis of specific communication-related accidents so that ithelps understand and foresee the communication errors.

The qualitative analysis method for communication errorsaddresses the retrospective and predictive analysis of communi-cation failures. Root causes can be determined through the retro-spective analysis method for known accidents. Expected errors canbe found through the predictive analysis method when causes areprovided. As case studies, the qualitative analysis method wasapplied to two cases of communication error and the root causes ofeach case were found through retrospective analysis.

The quantitative analysis method provides for the evaluation ofthe nominal probability of communication error types which aredefined based on CSP. Expected error types can be predicted by thequalitative analysis method and then their nominal probability canbe evaluated by the means of quantitative analysis in terms ofa certain context condition. Both analysis methods are useful toanalyze communication errors, thereby forecasting communica-tion-related accidents and forewarning the possible occurrence ofsuch accidents.

If the antecedenteconsequent links are understood in greaterdetail, the qualitative analysis can be more concrete and detailed. Ifmore exact nominal probability and weighting factors are set, thequantitative analysis can be more exact. In addition, if the depen-dencies between human factors are considered, the qualitativeanalysis can be more realistic (Cepin, 2008b). This study will notonly be useful for analyzing communication-related events butmayalso be a basis for research into the development of communicationsupport procedures and communication support tools in NPPs.

References

Berlo, D. K. (1960). The process of communication: An introduction to theory andpractice. , New York: Holt, Rinehart and Winston.

Berman, J., & Gibson, H. (1994). Communication failure in the operation of nuclearpower plants. Sandia National Laboratories. Sandia Report No. SAND-942364.

Boring, R. L., Hendrickson, S. M. L., Forester, J. A., Tran, T. Q., & Lois, E. (2010). Issuesin benchmarking human reliability analysis methods: a literature review. Reli-ability Engineering and System Safety, 95, 591e605.

Cepin, M. (2008a). Importance of human contribution within the human reliabilityanalysis (IJS-HRA). Journal of Loss Prevention in the Process Industries, 21, 268e276.

Cepin, M. (2008b). DEPEND-HRAda method for consideration of dependency inhuman reliability analysis. Reliability Engineering and System Safety, 93,1452e1460.

Chung, Y. H. (2007). Communication analysis of emergency operations in nuclearpower plant based on humanehumanesystem framework. Doctoral thesis. KAIST.

S.M. Lee et al. / Journal of Loss Prevention in the Process Industries 24 (2011) 90e97 97

Carvalho, P. V. R., Santos, I. L., Gomes, J. O., Silva Borges, M. R., Huber, G. J. (2006).The role of nuclear power plant operators0 communications in providingresilience and stability in system operation. Proceedings of 2nd Symposium onResilience Engineering.

Hirotsu, Y., Suzuki, K., Kojima, M., & Takano, K. (2001). Multivariate analysis ofhuman error incidents occurring at nuclear power plants: several occurrencepatterns of observed human errors. Cognition, Technology, & Work, 3, 82e91.

Hollagel, E. (1998). Cognitive reliability and error analysis method. Amsterdam:Elsevier Science Ltd.

Kim, D. H., Lee, Y. H., & Lee, J. W. (2006). An assessment of job-related stress factorsin nuclear power plant. Proceedings of Ergonomics Society of Korea, 10, 489e495.

Kim, J. W., & Jung, W. D. (2002). An integrated framework to the predictive erroranalysis in emergency situation. Journal of Loss Prevention in the ProcessIndustries, 15, 97e104.

Kim, M. C., Park, J. K., & Jung, W. D. (2008). Sentence completeness analysis forimproving team communications of safety-critical system operators. Journal ofLoss Prevention in the Process Industries, 21, 255e259.

Lee, Y. H. (2007). The casebook on human error in nuclear power plant. Korea AtomicEnergy Research Institute. (in Korean).

Levelt, W. (1989). Speaking: From intention to articulation. Cambridge, MA: The MITPress.

Min, D. H., Chung, Y. H., Yoon, W. C. (2004). Comparative analysis of communicationat main control rooms of nuclear power plant. Proceedings of IFAC/IFIP/IFORS/IEASymposium.

Nadler, D. A., & Tushman, M. L. (1980). A Model for diagnosing organizationalbehavior. Organizational Dynamics, 9, 35e51.

Richmond, P. V., & McCroskey, J. C. (2009). Organizational communication forsurvival: Making work, work. Boston: Pearson/Allyn & Bacon.

Swain, A. D., & Guttman, H. E. (1983). Handbook of human-reliability analysis withemphasis on nuclear power plant application (NUREG/CR-1278). Washington DC:NRC.

Williams, J. C. (1988). A data-based method for assessing and reducing human errorto improve operational performance. Proceedings of IEEE 4th Conference onHuman Factors in Power Plants. Monterey, CA.