Modelling of Technical, Human and Organisational Factors of Ship Grounding Accidents with the

112 Pages·2016·2.81 MB·English

by  Elisa Désiré Baumgärtner

Modelling of Technical, Human and
Organisational Factors of Ship Grounding
Accidents with the use of Bayesian Belief
Networks
Elisa Désiré Baumgärtner
Reliability, Availability, Maintainability and Safety (RAMS)
Submission date: May 2016
Supervisor: Stein Haugen, IPK
Norwegian University of Science and Technology
Department of Production and Quality Engineering

RAMS
Reliability, Availability,
Maintainability, and Safety
Modelling of Technical, Human and
Organisational Factors of Ship Grounding
Accidents with the use of
Bayesian Belief Networks
Elisa Désiré Baumgärtner
May2016
MASTERTHESIS
DepartmentofProductionandQualityEngineering
NorwegianUniversityofScienceandTechnology
Supervisor: ProfessorSteinHaugen

i
Preface
This Master Thesis is written in culmination of the 2-years International Master Programme
in Reliability, Availability, Maintainability and Safety (MSc RAMS) within the Production and
QualityEngineeringDepartment(IPK)attheNorwegianUniversityofScienceandTechnology
(NTNU),Trondheim, Norway. Thisworkhasbeenperformedduringthespringsemester2016
incontinuationoftheSpecialisationProjectwrittenduringautumnsemester2015.
ThisstudyispreparedincollaborationwiththeongoingresearchprojectNationalShipRisk
Model, which intends to develop a risk model for traffic in Norwegian waters. Partners of this
joinedprojectaretheNTNUSocialResearch’sdepartmentStudioApertura,NTNUDepartment
ofMarineTechnology,Safetec,theNorwegianMaritimeAuthority(Sjøfartsdirektoratet)andthe
NorwegianCostalAdministration(Kystverket).
Theintendedreaderforthisreportshouldhaveabackgroundinareasrelatedtoriskanalysis.
Inaddition,practicalexperiencewithinthemaritimeshippingindustryisanadvantagebutnot
aprerequisite.
Trondheim,2016-05-31
ElisaDésiréBaumgärtner

iii
Acknowledgement
There are several people I would like to thank for their comments, contributions and valuable
assistanceduringthewritingofthismasterthesis.
Firstly, my supervisor, Professor Stein Haugen from the Department of Marine Technology
forhistime,patienceandguidancewhichwasveryvitalintheexecutionofthisthesis.
IwouldfurtherliketoexpressmygratitudetotheNationalShipRiskModelteamforgiving
metheopportunitytocontributetothisproject. AspecialthanksgoestoMarieNilsenandPet-
terGryttenAlmklovfromStudioAperturaforsharingliteratureandcurrentinformationabout
theproject,aswellasansweringpatientlyallarisingquestions.
AspecialthankyoutothefacultyoftheRAMSEngineeringatNTNUforsupportandguid-
ancethroughoutthewhole2-yearsMasterprogramme.
Lastbutnottheleast,Ipersonallywouldliketothankmyfamilyandfriendsforsupporting
andmotivatingmethroughouttheyearsofstudyingatNTNUandlivingabroadinNorway.
E.D.B.

v
Summary and Conclusion
In recent years, the management of risk has developed towards a risk based approach. Thus,
industriesneedtohaveacomprehensiveunderstandingofwhyaccidentsoccurandhowthey
develop. In order to act successfully in the prevention of accidents, the areas in which risk re-
duction is most beneficial need to be identified. For this reason, quantitative risk analysis has
developedonwards. Onemethod,whichwillbeconsideredindetailtosupporttheseinvestiga-
tion,istheBayesianBeliefNetwork.
A Bayesian Belief Network (BBN) is a graphical model which visualises the causal relation-
ship between different factors and the final outcome. It represents a flexible approach which
canbeusedqualitativelyandquantitatively.
CurrentresearchonthequantificationofthesefactorsinBBNmodelsaremainlybasedon
statistical approaches evaluating incident and accident reports. This approach however com-
prisessomeproblemsrelatedtoalackofdata,dataoverloadandunderreporting.Thus,itneeds
to be decided on a correction factors, a safety margin or to rely on expert judgement. For that
reasonanotherapproachbasedonaframeworkofriskinfluencingfactors(RIFs)andriskindi-
catorscanbeusedtomeasuretheeffectonriskcoveringtheoverallsocio-technicalsystem.
ThismasterthesisfocussesontheidentificationofsuitableRIFsandindicatorsfortechni-
cal, human and organisational factors of a BBN ship grounding model. Based on a literature
reviewtheinfluenceofBBNnodesontheoccurrenceofgroundingaccidentsisinvestigated.
Theanalysesshowthat80%ofcausesarehumanandorganisationalrelated, whereasonly
20%representtechnicalcauses.Oftenarangeofcausesneedtobeconsideredinordertounder-
stand the whole complexity behind grounding accidents. The introduction of new technology
and automation does not always benefit marine navigation. It results in a polarised workload
structure,thereductionoftask-relatedcommunicationandadecreaseinsituationawareness.
Furthermore,theindividualriskperceptionwasfoundouttoinfluencepeoplesbehaviour.
vi
Thisexplainstheoccurrenceofgroundingsalsoingoodweatherandgoodtechnicalcondi-
tions of ships. For that reason, one should improve the human-machine interface rather than
adding new technology. One beneficial method could be user-centred design combined with
regularandbettertrainingsofpersonnel.
In summary, the identification of indicators represents a complex process that due to var-
ious approaches and context-specific understanding cannot give one ultimate outcome. The
implementationofriskindicatorsinanoperationalcontext,representsabeneficialtoolforper-
formancesurveillanceandriskcontrol.