Optimum decision making in asset management

Making in Asset Management María Carmen Carnero University of Castilla – La Mancha, Spain Vicente González-Prida University of Seville, Spain A volume in the Advances in Logistics, Opera

Making in Asset

Management

María Carmen Carnero

University of Castilla – La Mancha, Spain

Vicente González-Prida

University of Seville, Spain

A volume in the Advances in Logistics,

Operations, and Management Science (ALOMS)

Book Series

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Names: Carnero, Maria Carmen, 1970- editor | Gonzalez-Prida, Vicente, 1975-

editor

Title: Optimum decision making in asset management / Maria Carmen Carnero and

Vicente Gonzalez-Prida, editors

Description: Hershey, PA : Business Science Reference, [2017] | Series:

Advances in logistics, operations, and management science | Includes

bibliographical references and index

Identifiers: LCCN 2016023216| ISBN 9781522506515 (hardcover) | ISBN

9781522506522 (ebook)

Subjects: LCSH: Maintenance Decision making | Industrial

equipment Maintenance and repair Management | Public works Management

| Capital Management | Operations research

Classification: LCC TS192 O65 2017 | DDC 620/.0046 dc23 LC record available at https://lccn.loc.gov/2016023216

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Vicente González-Prida

JorgeMarcosAcevedo,University of Vigo, Spain

AitorArnaiz,IK4-Tekniker, Spain

AdolfoCrespoMárquez,University of Seville, Spain

FredyKristjanpoller,University Federico Santa María, Chile

CarmenMartin,Toulouse University, France

FrançoisPérès,Toulouse University, France

JavierSantos,Tecnun, University of Navarra, Spain

MiguelÁngelSanzBobi,Comillas Pontifical University, Spain

AntonioSola,Ingeman, Association for the Development of Maintenance Engineering, Spain

List of Reviewers

SamirAlSharif,Taibah University, Saudi Arabia

OlgaAleksenko,Sumy State University, Ukraine

DavidAlmorzaGomar,University of Cadiz, Spain

SyamsundarAnnamraju,Visakhapatnam Steel Plant, India

LuisBarberá,University of Seville, Spain

A.J.J.Braaksma,University of Twente, The Netherlands

JavierCárcelCarrasco,Universitat Politècnica de València, Spain

EduardoCastellano,IKERLAN, Spain

JoseLuisCenalmorFidalgo,Konica Minolta Business Solutions, Spain

JoseContreraMárquez,INGECON, Venezuela

PeterEecen,ECN, The Netherlands

MaríadeLourdesEgurenMartí,University of Barcelona, Spain

RafaelGonzález-Palma,University of Cadiz, Spain

AntonioJesusGuillénLopez,University of Seville, Spain

SamirKhan,Coventry University, UK

KhairyA.H.Kobbacy,Taibah University, Saudi Arabia

LeireLabaka,Tecnun, University of Navarra, Spain

CarlosLópez-EscobarBeares,ALCOA, Spain

PatriciaMaraña,Tecnun, University of Navarra, Spain

YuliiaParfeneko,Sumy State University, Ukraine

CarlosParra,University of Seville, Spain

ManuelRodríguezMendez,ESeyPro S.L., Spain

RichardRuitenburg,University of Twente, The Netherlands JoseMariaSarriegi,Tecnun, University of Navarra, Spain ViraShendryk,Sumy State University, Ukraine

WiegerTiddens,University of Twente, The Netherlands

TiedoTinga,University of Twente, The Netherlands

JasperVeldman,University of Groningen, The Netherlands PabloViverosGunckel,University Federico Santa Maria, Chile PatziXabierZubizarreta,IKERLAN, Spain

Foreword xxi Preface xxiii

Section 1 Chapter 1

CaseStudyonaMaintenanceandReliabilityManagementModelProposal:AThirdSetofLocksProjectinthePanamaCanal 1

Carlos Parra, University of Seville, Spain

Adolfo Crespo Márquez, University of Seville, Spain

Vicente González-Prida, University of Seville, Spain

Fredy Kristjanpoller, Universidad Técnica Federico Santa María, Chile

Pablo Viveros, Universidad Técnica Federico Santa María, Chile

Gabriel Llort, MWH Global, USA

Alfredo R Aguilar, MWH Global, Panama

Patricia Maraña, University of Navarra, Spain

Leire Labaka, University of Navarra, Spain

Jose Mari Sarriegi, University of Navarra, Spain

Chapter 4

GraphicalTechniquesandMethods:ValidatinghowtheyImproveCriticalAssetsManagement 83

Adolfo Crespo Márquez, University of Seville, Spain

Luis Barberá, University of Seville, Spain

Khairy A H Kobbacy, Taibah University, Saudi Arabia

Samir M Shariff, Taibah University, Saudi Arabia

Chapter 5

ImpactoftheKnowledgeManagementinMaintenanceEngineering:EffectsonIndustrial

Production 96

Javier Cárcel-Carrasco, Universitat Politècnica de València, Spain

Manuel Rodríguez-Méndez, ESeyPro S.L., Spain

María Carmen Carnero, University of Castilla – La Mancha, Spain & University of Lisbon, Portugal

Chapter 6

AssetManagementforBuildingswithintheFrameworkofBuildingInformationModeling

Development 121

Antonio Jesús Guillén López, University of Seville, Spain

Adolfo Crespo Márquez, University of Seville, Spain

Jose A Sanz, University of Seville, Spain

Khairy A H Kobbacy, Taibah University, Saudi Arabia

Samir M Shariff, Taibah University, Saudi Arabia

Etienne Le Page, École Centrale de Marseille, France

Vicente González-Prida, University of Seville, Spain

Chapter 7

Service4.0:TheReasonsandPurposesofIndustry4.0withintheAmbitofAfter-Sales

Maintenance 139

Eduardo Castellano, IK4-IKERLAN, Spain

Patxi X Zubizarreta, IK4-IKERLAN, Spain

Gerardo Pagalday, IK4-IKERLAN, Spain

Jone Uribetxebarria, IK4-IKERLAN, Spain

Adolfo Crespo Márquez, University of Sevilla, Spain

Chapter 8

CompatibilityWeldingParameterswiththeResultsObtainedinTestingofFractureMechanicsinHSLASteel 163

Rafael González-Palma, University of Cádiz, Spain

María Carmen Carnero, University of Castilla – La Mancha, Spain & University of Lisbon, Portugal

Carlos López-Escobar, Independent Researcher, Spain

David Almorza, University of Cádiz, Spain

Pedro Mayorga, EnerOcean S.L., Spain

Chapter 9

ModelofaPerformanceMeasurementSystemforMaintenanceManagement 194

José Contreras, INGECON, Venezuela

Carlos Parra, University of Seville, Spain

Adolfo Crespo Márquez, University of Seville, Spain

Vicente González-Prida, University of Seville, Spain

Fredy Kristjanpoller, Universidad Técnica Federico Santa María, Chile

Chapter 10

AIandStatisticalTechnologiesforManufacturingandMaintenanceStrategiesimprovement:

HealthMonitoringforElectromechanicalActuators 215

Susana Ferrerio Del Río, IK4-Tekniker, Spain

Santiago Fernández, IK4-Tekniker, Spain

Iñaki Bravo-Imaz, IK4-Tekniker, Spain

Egoitz Konde, IK4-Tekniker, Spain

Aitor Arnaiz Irigaray, IK4-TEKNIKER, Spain

Chapter 11

Sensor-BasedDecisionMakinginUncertainContext 234

Eric Villeneuve, Université de Toulouse, France

François Pérès, Université de Toulouse, France

Cedrik Beler, Université de Toulouse, France

Vicente González-Prida, University of Seville, Spain

Section 2 Chapter 12

AssetLifeCyclePlans:TwelveStepstoAssistStrategicDecision-MakinginAssetLifeCycle

Management 259

R J (Richard) Ruitenburg, University of Twente, The Netherlands & Liander N.V., The

Netherlands

A J J (Jan) Braaksma, University of Twente, The Netherlands

L A M (Leo) van Dongen, University of Twente, The Netherlands

Chapter 13

TowardsInformedMaintenanceDecisionMaking:GuidingtheApplicationofAdvanced

MaintenanceAnalyses 288

W W (Wieger) Tiddens, University of Twente, The Netherlands & Netherlands Defence

Academy, The Netherlands

A J J.(Jan) Braaksma, University of Twente, The Netherlands

T (Tiedo) Tinga, University of Twente, The Netherlands & Netherlands Defence Academy, The Netherlands

Chapter 14

InformationSupportingofDecisionMakingforEnergyManagementinDistrictHeating 310

Vira Shendryk, Sumy State University, Ukraine

Victor Nenia, Sumy State University, Ukraine

Olga Aleksenko, Sumy State University, Ukraine

Yuliia Parfenenko, Sumy State University, Ukraine

Chapter 15

RisksandUncertaintiesinthePlanningPhaseofOffshoreWindProjects 334

Jannes van der Wal, University of Groningen, The Netherlands

Peter Eecen, ECN, The Netherlands

Jasper Veldman, University of Groningen, The Netherlands

Chapter 16

TheSet-UpProcess 358

Manuel Rodríguez Méndez, ESeyPro S.L., Spain

Javier Cárcel-Carrasco, Universitat Politècnica de València, Spain

Foreword xxi Preface xxiii

Section 1 Chapter 1

CaseStudyonaMaintenanceandReliabilityManagementModelProposal:AThirdSetofLocksProjectinthePanamaCanal 1

Carlos Parra, University of Seville, Spain

Adolfo Crespo Márquez, University of Seville, Spain

Vicente González-Prida, University of Seville, Spain

Fredy Kristjanpoller, Universidad Técnica Federico Santa María, Chile

Pablo Viveros, Universidad Técnica Federico Santa María, Chile

Gabriel Llort, MWH Global, USA

Alfredo R Aguilar, MWH Global, Panama

Thepurposeofthischapter,istoprovideaMaintenanceandReliabilityManagementModelfortheproject:DesignandConstructionoftheThirdSetofLocksinthePanamaCanal,withtheapproachoftheprocessofassetmanagementoptimization.Apracticalvisionofthemaintenanceandreliabilitymanagementprocessandframeworkispresentedwiththeideaof:Structuringthemaintenancemanagementprocessbygroupingmanagementactivitieswithinaseriesofso-calledmanagementbuildingblocks;Structuringtheframeworkgroupingtechniquesthatcanbeusedtosupportdecisionstobetakenwithineachofthesebuildingblock.Thischapterpresentsnotonlyaprocessbutalsotheframeworkandtechniquestomanageandimprovemaintenanceandreliabilityeffectivenessandefficiency.Thisreportwillbeusedtoassistdifferentplantteamstoelaboratetheoptimalstrategiesformaintenanceandinspectionfortheassets,specifiedfortheproject:ThirdSetofLocksinthePanamaCanal

Chapter 3

MaintenanceinCriticalInfrastructures:TheNeedforPublic-PrivatePartnerships 62

Patricia Maraña, University of Navarra, Spain

Leire Labaka, University of Navarra, Spain

Jose Mari Sarriegi, University of Navarra, Spain

Theincreaseinthefrequencyofdisastrouseventsandsociety’sdependenceonCriticalInfrastructures(CIs)hasledtogreaterconcernabouttheneedtoincreaseresilienceinordertoimproveCriticalInfrastructureProtection.CIsarebasicserviceprovidersforsocietyandtheyneedtobeeffectivelyprotectedagainsthazards.Nowadays,CIscanbeownedbyprivateentities.However,althoughtheycanbeprivatelyownedormanaged,theyprovideapublicservicethatdirectlyaffectsthewholesociety.Consequently,thoseactivitiesthatincreasetheoverallresiliencelevelofCIsneedtobeunderthesupervisionofpublicentities.Increasingresiliencerequiresspecialattentionbepaidtocorrectinfrastructureandcrisisresponseequipmentmaintenance.ThischapterexplainswhyeffectivePublic-PrivatePartnerships(PPP)arevaluableforcorrectlymaintainingCIsandillustratesexamplesofrealsituationsthatdemonstratetheneedforeffectivePPPsinmaintenanceactivities

Chapter 4

GraphicalTechniquesandMethods:ValidatinghowtheyImproveCriticalAssetsManagement 83

Adolfo Crespo Márquez, University of Seville, Spain

Luis Barberá, University of Seville, Spain

Khairy A H Kobbacy, Taibah University, Saudi Arabia

Samir M Shariff, Taibah University, Saudi Arabia

GAMM(GraphicalAnalysisforMaintenanceManagement)isamethodthatsupportsdecision-makinginmaintenancemanagementthroughthevisualizationandgraphicalanalysisofdata.GAMMalsoallowstheidentificationofanomalousbehaviorinequipment,derivedfromitsownoperations,maintenanceactivities,improperuseofequipmentorevenasaresultofdesignerrors.Asabasisforanalysis,theGAMMmethodusesanonparametricestimatorofthereliabilityfunctionusinghistoricaldata,sometimesinverylimitedamounts.However,forsuccessfulresults,experienceandadvancedknowledgeinmaintenancemanagementarestrictlynecessary.InordertoeasetheinterpretationsoftheGAMMmethodresults,withtheintentionthatthemethodbecomesreallyamicableformanagers,asetofbasicruleshavebeendeveloped.ThissetofrulesleadstoaproperandobjectiveinterpretationofGAMMresults,improvingthedecisionmaking

Chapter 5

ImpactoftheKnowledgeManagementinMaintenanceEngineering:EffectsonIndustrial

Production 96

Javier Cárcel-Carrasco, Universitat Politècnica de València, Spain

Manuel Rodríguez-Méndez, ESeyPro S.L., Spain

María Carmen Carnero, University of Castilla – La Mancha, Spain & University of Lisbon, Portugal

Knowledgemanagementhasbeenanalyzedinnumerousareasoftheindustrialenterprise,especiallyintheareasofstrategicmanagement,innovation,trade,oradministration.Howeverinoperationalareaswithtechniciansworkingmainlyonthebasisofitsexperiencegainedovertheyears,suchasthedepartmentsofindustrialmaintenance,therearenodeepanalysisoftheincidenceoftheknowledgemanagementintheseareas.Thepeculiaritiesinthistypeofactivityontheinsideofthecompany,knowledgeofthesepeopleisstronglybasedonyourexperience(strongtacitcomponent),difficulttomeasureandarticulate,andhowever,onnumerousoccasions,thisknowledgenottransmitted,canbeahighcostforthecompany(manytimesassumedasinevitable)duetotheincreaseofproductionandservicesdowntime,lossofefficiency,ortimeofcouplingofnewpersonneltotheseareas

Chapter 6

AssetManagementforBuildingswithintheFrameworkofBuildingInformationModeling

Development 121

Antonio Jesús Guillén López, University of Seville, Spain

Adolfo Crespo Márquez, University of Seville, Spain

Jose A Sanz, University of Seville, Spain

Khairy A H Kobbacy, Taibah University, Saudi Arabia

Samir M Shariff, Taibah University, Saudi Arabia

Etienne Le Page, École Centrale de Marseille, France

Vicente González-Prida, University of Seville, Spain

Buildingslifecyclemanagementisanareaofgreatinterest.Duethis,theR&Disbeingpromotingworldwidelookingforneweffectivemaintenancetoolsandmethodologies.Inthisscenariotherearetwodevelopmentlineswhoseconvergencecanbringgreatadvancesinthisarea:AssetManagement(AM)andBuildingInformationModeling(BIM).BIMmodelsaretransformingthewaybuildingsareconceived,designed,constructedandmanaged.ButcurrentuseofBIMconcentratesonpreplanning,design,constructionandintegratedprojectdeliveryofbuildingsandfacilities,ratherthanmaintenanceandbuildingoperationmanagement.AssetManagementtools,includingFacilitiesManagement(FM),andapplicationframeworksprovidetheapproachandrequiredelementstogetmoreefficiencyandefficacyinthebuildinglifecyclemanagement.ThischapterintroducestheapplicationofAMforbuildingandhowthedevelopmentofBIMmodelsisthekeyelementtoallowitseffectiveimplementation

Chapter 7

Service4.0:TheReasonsandPurposesofIndustry4.0withintheAmbitofAfter-Sales

Maintenance 139

Eduardo Castellano, IK4-IKERLAN, Spain

Patxi X Zubizarreta, IK4-IKERLAN, Spain

Gerardo Pagalday, IK4-IKERLAN, Spain

Jone Uribetxebarria, IK4-IKERLAN, Spain

Adolfo Crespo Márquez, University of Sevilla, Spain

Inrecentyears,theconceptofIndustry4.0hasbeensignificantlyadvancedinindustrialcirclesasanaspectthatprovidesacompetitivedifferential.Throughthetechnologiesinvolved,machinescannowmonitorandrelayinformationontheiroperatingconditionsforanalysisanddecision-making,aswellasforpromptingaction.Thesenewfunctionsgenerallyinvolvethedevelopmentoftechnologicalprojectsandsignificantinvestments.Thisrendersitexpedienttoexplainwhycertainsystemsshouldbemonitored,butnotothers,aswellastheusetobegiventothedatagatheredasawayofgeneratingincomeforafirm.Thisapproachisespeciallyimportantincertaincorporateoperations,suchasafter-salesmaintenance.Thisarticleintroducesareferenceframeworkthatpermitstheeffectiveandefficientmanagementofafter-salesmaintenanceservices.Thisframeworkrelatesafter-salesservicetechnologieswithproducttechnologies(Industry4.0),andthereforecoversthereasonsandpurposesofIndustry4.0withintheambitofafter-salesservice

Chapter 8

CompatibilityWeldingParameterswiththeResultsObtainedinTestingofFractureMechanicsinHSLASteel 163

Rafael González-Palma, University of Cádiz, Spain

María Carmen Carnero, University of Castilla – La Mancha, Spain & University of Lisbon, Portugal

Carlos López-Escobar, Independent Researcher, Spain

David Almorza, University of Cádiz, Spain

Pedro Mayorga, EnerOcean S.L., Spain

Manyinvestigationsledtoshowthatnocrackbeginstopropagatetoanincreaseofstressintensityfactor.Thelifeofthecomponentsofastructurecontainingprematurecracks,canbegovernedbythedegreeofsubcriticalcrackpropagation.Thus,knowledgeofcrackpropagationtodeterminethefatigueofthestructureisnecessary.OneproblemofsteelsofhighresilienceistheirlowtoughnessintheHAZ,whentheyareweldedwithahighheatinput.InthisworkwehavestudiedninespecimensthathavebeenweldedunderasubmergedarcweldingprocesscontrollingtheweldingparametersandcheckingintheHAZofsuchspecimens,criticaltensionsattheendsofthecracks,thecriticalcrackslengthsandstressintensityfactors.ItisintendedtocheckthattheparametersthatindicatethevaluesoffracturemechanicsintheHAZ,afterheatcycletowhichthesteelhasundergone,underaprocesswithamaximumheatinputof2.327kJ/mm,theyarestillvalid,withtheweldingparametersapplied.Itischeckedacorrelationbetweenthetheoreticalandexperimentalvalues

Chapter 9

ModelofaPerformanceMeasurementSystemforMaintenanceManagement 194

José Contreras, INGECON, Venezuela

Carlos Parra, University of Seville, Spain

Adolfo Crespo Márquez, University of Seville, Spain

Vicente González-Prida, University of Seville, Spain

Fredy Kristjanpoller, Universidad Técnica Federico Santa María, Chile

Pablo Viveros, Universidad Técnica Federico Santa María, Chile

Thischapterbookwillanalyzedifferentsystemsofindicatorsbywhichmaintenancemanagementisevaluated.Themodelsanalyzedare:1)TheBalancedScorecard.2)TheAlsyoufModel.3)TheMaintenanceScorecardModel.4)TheMetricsforMaintenanceofSMRP(SocietyofMaintenanceandReliabilityProfessionals).5)TheEN-15341-MaintenanceKeyPerformanceIndicators(EuropeanStandard).Thispaperpresentsamodelforindicatorsbasedonvarioushierarchicallevelsanddifferentfunctionsandprocessestakingplaceinamaintenancedepartment.Withthismodelacomprehensiveassessmentofthemostimportantaspectsatalllevelsoftheorganizationisachievedandshowstherelationshipbetweenthevariousindicatorstounderstandtheoverallperformanceofmaintenancemanagementandsoaligndepartmentalobjectiveswiththestrategicobjectives.AlsoisdevelopedtheC-KPI-Mmodel,whichisthedefinitionof18chainsofkeyindicatorsforviewingthecauseandeffectofthemaintenanceKPIthatcontributetoachievingthemaximumEconomicValueAdded(EVA)

Chapter 10

AIandStatisticalTechnologiesforManufacturingandMaintenanceStrategiesimprovement:

HealthMonitoringforElectromechanicalActuators 215

Susana Ferrerio Del Río, IK4-Tekniker, Spain

Santiago Fernández, IK4-Tekniker, Spain

Iñaki Bravo-Imaz, IK4-Tekniker, Spain

Egoitz Konde, IK4-Tekniker, Spain

Aitor Arnaiz Irigaray, IK4-TEKNIKER, Spain

Thedevelopmentandtheimplementationofadvancedactuationsystemshasincreasedinrecentyears,asmanyfactorsaredrivingthemigrationfromhydraulicactuatorstoelectromechanicalactuators(EMAs)inaeronautics.Butnotonlydowehavetoconsidertherightdesigntocustomizethesystemfromtherequirementsorientedtothefinalapplication,alsoadditionalfunctionsthatcanprovidethesystemwithadditionalvalue,tomakeitmorecompetitiveinthismarket.ThisisthecaseoftheHealthMonitoring(HM) systems. Thedevelopment,implementationandintegration of predictive algorithmsinto theenvironmentoftheEMAprovidethesystemwithanadditionalfunctionality,fromwhichitispossibletodetectfailuresatanearlystageinordertoavoidcatastrophicaccidentsandimprovemaintenanceactivities.ThisworkshowshowtodevelopHMalgorithmsbasedonAIandStatisticaltechnologiestodetectandpredictearlystagesoffailureinagearbox,whichcandirectlyaffecttothetransmissionofpowerinEMAs

Chapter 11

Sensor-BasedDecisionMakinginUncertainContext 234

Eric Villeneuve, Université de Toulouse, France

François Pérès, Université de Toulouse, France

Cedrik Beler, Université de Toulouse, France

Vicente González-Prida, University of Seville, Spain

Decisionmakers,whetherhumanorcomputer,usingsensornetworkstoinstrumentinformationcollectingnecessaryfordecision,oftenfacedifficultiesinassessingconfidencegrantedtosignalstransmittedandreceivedinthenetwork.Severalorganizational(networkarchitectureornature,distancebetweensensors ),internal(sensorreliabilityoraccuracy )orexternal(impactofenvironment )factorscanleadtomeasurementerrors(falsealarm,non-detectionbymisinterpretationoftheanalyzedsignals,false-negative…).Asystem-embeddedintelligenceisthennecessary,tocomparetheinformationreceivedforthepurposeofdecisionaidingbasedonmarginoferrorsconvertedinconfidenceintervals.Inthischapter,theauthorspresentfourcomplementaryapproachestoquantifytheinterpretationofsignalsexchangedinanetworkofsensorsinthepresenceofuncertainty

Section 2 Chapter 12

AssetLifeCyclePlans:TwelveStepstoAssistStrategicDecision-MakinginAssetLifeCycle

Management 259

R J (Richard) Ruitenburg, University of Twente, The Netherlands & Liander N.V., The

Netherlands

A J J (Jan) Braaksma, University of Twente, The Netherlands

L A M (Leo) van Dongen, University of Twente, The Netherlands

Effectivemanagementofphysicalassetsshoulddelivermaximumbusinessvalue.Therefore,AssetManagementstandardssuchasPAS55andISO55000askforalifecycleapproach.However,mostexistingmethodsfocusonlyontheshorttermoftheasset’slifeortheestimationofitsremaininglife.Thesemethodsdonotconsideralignmenttochangingcorporateobjectivesinavariablecontext,nordotheyadoptamultidisciplinaryperspective.Thischapterarguesthat,tocreatemaximumvalue,AssetManagementshouldbeamultidisciplinaryandstrategicpracticethatconsidersthecompletelifecycleoftheasset:AssetLifeCycleManagement.Apracticaltwelve-stepapproachispresentedtodevelopanAssetLifeCyclePlan(ALCP)inwhichexpertsessionsareusedtoidentifythemainlifetimeimpactsthatinfluencethecreationofbusinessvaluefromtheuseoftheasset.Thestepsareillustratedwithanexamplefrompractice.ThechapterconcludesthattheALCPsupportsassetmanagersinmakinglong-termstrategicdecisionsinatimelyandeffectivemanner

Chapter 13

TowardsInformedMaintenanceDecisionMaking:GuidingtheApplicationofAdvanced

MaintenanceAnalyses 288

W W (Wieger) Tiddens, University of Twente, The Netherlands & Netherlands Defence

Academy, The Netherlands

A J J.(Jan) Braaksma, University of Twente, The Netherlands

T (Tiedo) Tinga, University of Twente, The Netherlands & Netherlands Defence Academy, The Netherlands

informedmaintenancedecisions,suchasensuringjust-in-timemaintenance,corporatebusinessplanningorlifetimeextensionofphysicalassets.Thesetechniquestakethecurrent,butpreferablyalsothefuture,stateofassetsintoaccount.Althoughthereismuchliteratureonthedevelopmentofspecifictechniques,reportsontheiradoptionanduseshowthatonlyfewcompanieshavesuccessfullyappliedthesemethods.Guidanceisneededontheirselectionandapplication.Inthischapter,atypologyofcompanies–basedonanongoingmultiple-casestudy–thatapplythesemaintenancetechniquesisproposed.ThistypologyidentifiestypicaldifficultiespractitionersexperienceinapplyingAMTs.Finally,afour-stepprocedureisofferedwiththeaimofhelpingpractitionerstoovercomethediscusseddifficultiesintheapplicationofAMTs

Advancedmaintenancetechniques(AMTs)arepracticesthatcanhelppractitionerstomakebetter-Chapter 14

InformationSupportingofDecisionMakingforEnergyManagementinDistrictHeating 310

Vira Shendryk, Sumy State University, Ukraine

Victor Nenia, Sumy State University, Ukraine

Olga Aleksenko, Sumy State University, Ukraine

Yuliia Parfenenko, Sumy State University, Ukraine

Thechapterfocusesonimplementationofinformationtechnologiesinenergymanagementofdistrictheatingsystem.Itcapturesthecurrentstateofenergymanagementindistrictheating.Themainstandardsofenergymanagementaredescribed.Thespecificfeaturesofdistrictheatingsystemandtheexistingtoolsofenergymanagementindistrictheatingareexplored.Thechapterstudiestheexistingmodels,whichcanbeappliedinthedecisionsupportsystemforheatenergymanagement.Itdescribesthedecisionsupportsystem“HeatCAM”asatoolofenergymanagementindistrictheating

Chapter 15

RisksandUncertaintiesinthePlanningPhaseofOffshoreWindProjects 334

Jannes van der Wal, University of Groningen, The Netherlands

Peter Eecen, ECN, The Netherlands

Jasper Veldman, University of Groningen, The Netherlands

Megaprojectsarelargeandcomplexprojectsthatentailmulti-actormanagement,non-standardtechnologyandprocesses.Thischapteraimstoexploreoffshorewindprojects(OWPs)asmegaprojects,particularintheplanningphase.Basedoninterviewswith26expertsfromavarietyofbackgroundsintheoffshorewindindustryinTheNetherlands,therisksanduncertaintiesintheplanningphaseofOWPsandkeyfactorsinthedecisionmakingprocessareexplored.AframeworkispresentedthatdepictstheplanningphaseofanOWP,aswellastenrisksandsevenuncertaintiesthataremostcommoninanOWP.Theroleofthegovernmentandtheprojectstructurearefurtherhighlighted.ThefindingsofthisresearchallowpractitionerstogainabetteroverviewoftheplanningprocessofanOWPandcanhelptoimprove

Chapter 16

TheSet-UpProcess 358

Manuel Rodríguez Méndez, ESeyPro S.L., Spain

Javier Cárcel-Carrasco, Universitat Politècnica de València, Spain

Topreparethemachinestomaketheproductthatclientneedsandtogivehimtheproductinthenecessarymomentistheobjectiveofallcompanies.Thismeanstohaveallmachinespreparedtomaketheproduct,itmeansthattheproductivesystemhasnotproblemstomaketheproductandthiscompliesthequalitystandards.Tohavepreparedthemachinestomakeaproductatsomepointitistheobjectiveofset-upprocess.Ifthisprocessiscorrectperformed,themachineswillmaketheproductwithoutproblems,butiftheset-upprocessisnotperformedincorrectway,thentheposteriorproductivestepwillhavemanyproblems.Perhaps,theset-upprocessisthemoreimportantproductivityactivity.Thetimenecessarytoperformtheset-upprocessistheparametertominimize,withtheprocesscost,andthistimesaystheflexibilityleveloftheproductiveprocessofthefactory

Chapter 17

AssetsManagementandRiskControl 374

María de Lourdes Eguren Martí, Universitat de Barcelona, Spain

Riskmanagementandinternalcontrolisasubjectthathasincreaseditsrelevanceduetotherecentfinancial scandals on companies like Enron and Worldcom, and the increment of fraud cases andfinancialmisstatementsaroundtheglobe.Inlinewiththis,severalinitiativeshavebeendefinedorrequiredinordertocontroltheriskexposureinthecompanyprocesses,includingthedevelopmentofinternalcontrolstandardslikeSarbanes-Oxley(SOX).Oneofthefactorstobeconsideredwhentakingoptimumdecisionsisrisk.Duetothis,inthischapterthekeyconceptsoverriskassetsmanagementwillbeexposed,includingapracticalexampleunderSOXframeworkaswellasasystem’sapproachandvaluemanagementperspective

Chapter 18

ReliabilityBasedMaintenanceofIndustrialAssets 399

A Syamsundar, Visakhapatnam Steel Plant, India

Mostindustrialassetstodayarecomplexrepairablesystems.Maintenancedecisionsonthesesystems/assetsarestillmadeonanempiricalbasisbasedontheexperienceandunderstandingofthemaintenanceengineers/managers.Thisleadstosub-optimaldecisionsandwillleadtoinefficientandineffectivemaintenance.Reliabilityisakeyattributeofsuchassets.Reliabilitycentredmaintenanceasamaintenancephilosophy and reliability engineering as an engineering discipline have been well developed overthepastseveraldecades.However,theseareyettofindaplaceinmaintenancedecisionsofindustrialassetsonaregularbasis.Thischapterdealswithhowreliabilitycentredmaintenanceandreliabilityofrepairablesystemscanbecombinedtogethertodevelopreliabilitybasedmaintenanceofindustrialassetsinanobjectivewaytoimprovetheefficiencyandeffectivenessofindustrialassetmaintenance.Themethodologyisillustratedwithasimplecasestudy

Chapter 20

NoFaultFoundProblemsinAssetManagement 448

Samir Khan, Coventry University, UK

Withinaerospaceanddefencesectors,maintainingassetavailabilityduringoperationalservicehasbecomemoreimportantthanqualityofservicethroughoutthesystemlifecycle.Thisrequiresorganisationstoestablishcosteffectivestrategiestomanageuncertaintieswithintheirvalueledservicese.g.maintenanceactivities.Inlargeorganizations,itisnotalwaysapparentwhosedecisionaffectstheoutcomethemost.Often,accountabilitymovesawayfromthedesignatedorganizationpersonnelinunforeseenways,anddependingonthedecisionsofindividualdecisionmakers,thestructureoftheorganization,orunregulatedoperatingproceduresmaychange.Thiscanhavefarmoreeffectontheoverallreliabilityleadingtoinadequate troubleshooting, repeated down-time and reduced availability. This chapter focuses ondiscussingtheNoFaultFoundproblemsinaviationandhighlightsthedriversthatinfluenceitsdecisionmakingprocess.Itfurtherarticulatesthecontentsoftacitknowledgeanddiscussestheknowledgegapswithcurrentmanagementpolicies

Compilation of References 468 About the Contributors 509 Index 520

IampleasedandhonouredattheopportunitytowriteashortForewordtoOptimumDecisionMakinginAssetManagement.Thebook’seditors,VicenteGonzález-PridaDíazandMaríaCarmenCarneroMoya,bringawealthofexperiencetobearontheirtopic,theyaregoodfriendsandwellrecognizedauthorsofresearchpapersandmanuscriptswithinthefieldofassetsmanagement,andmoreprecisely,assets’warrantyandpredictivemaintenancetechnologiesmanagement

VicenteGonzález-PridaDíazisamemberoftheSIMResearchGroup(Sistemas Inteligentes de

Man-tenimiento)oftheUniversityofSeville.Hehasmanagedwarrantyandtechnicalservicesdepartments

invariousmultinationalcompaniesinthemilitaryandintheutilitiessectors.MaríaCarmenCarneroMoyaisAssociateProfessor(withtenure)attheHigherTechnicalSchoolofIndustrialEngineeringoftheUniversityofCastilla-LaManchainCiudadReal,intheDepartmentofBusinessAdministration.Hehaspublishedextensivelyintheareaofpredictivemaintenancemanagementandhasbeeninvolvedinmanymaintenanceprojects,especiallywithintheHealthsector

Manyofthecontributorsofthisbook,includedthetwoEditors,aremembersoftheNetworkof

ExcellenceonAssetsManagement(DPI2014-56547-REDT),PromotedinSpainbythePlan Estatal

de Investigación Científica y Técnica y de Innovación

2013-2016,releasedbytheEconomyandCom-petitivenessMinistryoftheGovernmentofSpain.Becauseofmyresponsibilityasthecoordinatorofthisnetwork,Iamgladtoseethisworkasanotherinterestingoutcomeofouracademicandresearchcommunity(Section1ofthebookcontainspapersinwhichatleastoneoftheauthorsisamemberofournetwork),dealingwiththetopicofassetsmanagement

ThefieldofPhysicalAssetsManagementisanemergingfieldofactioninindustryandinothersectors,whichhasgivenrenewedattentiontothemaintenanceofindustrialequipment,buildingsandinfrastructureingeneral.Themainconcernofassetsmanagementistoensuretheintegrityandsustain-abilityoftheassets,payingatthesametimespecialattentiontotheireco-efficiencyovertheirlifecycle.Thisbookisagoodexampleofhowtheindustrialmaintenanceconcepthasevolvedovertimewiththeadventofnewtechnicalandorganizationalcapabilitiestotheindustry.Conceptslikeriskanduncer-taintymanagement,orlifecyclecostanalysisandmanagementarebecomingamustformodernassetsandmaintenancemanagers.GoodexamplesofthisrealityarealsopresentedinSection2ofthebook,fromverydiverseandenrichingperspectives

ingnewchallengesespeciallyforindustrialorganizations.Theopennatureofthestandard,besidesthenumberofdifferentareasitdealswith,makesessentialthesearchforcollaborationbetweencompaniesandresearchinstitutioninterestedinthisfield

Adolfo Crespo Márquez

University of Seville, Spain

Adolfo Crespo Márquez is currently Full Professor at the School of Engineering of the University of Seville, and Head of the

Department of Industrial Management He holds a PhD in Industrial Engineering from this same University His research works have been published in journals such as the International Journal of Production Research, International Journal of Production Economics, European Journal of Operations Research, Journal of Purchasing and Supply Management, International Journal

of Agile Manufacturing, Omega, Journal of Quality in Maintenance Engineering, Decision Support Systems, Computers in Industry, Reliability Engineering and System Safety and International Journal of Simulation and Process Modeling, among oth- ers Prof Crespo is the author of 7 books, the last four with Springer-Verlag in 2007, 2010, 2012 and 2014 about maintenance, warranty and supply chain management Prof Crespo leads the Spanish Research Network on Dependability Management and the Spanish Committee for Maintenance Standardization (1995-2003) He also leads a research team related to maintenance and dependability management currently with 5 PhD students and 4 researchers He has extensively participated in many en- gineering and consulting projects for different companies, for the Spanish Departments of Defense, Science and Education as well as for the European Commission (IPTS) He is the President of INGEMAN (a National Association for the Development

of Maintenance Engineering in Spain) since 2002.

OVERVIEW

Assetmanagement,onceconsideredatacticalarea,isnowamatterofstrategy,giventheimplicationsithasforavailabilityoffacilitiesandequipment,deliverytime,productquality,costs,safetyandtheenvironment.Inaddition,theintroductionofadvancedmanufacturingtechniquesandnewproductionmanagementsystems,whichleadtoincreasedautomationandreduceddeliverytimes,hasgivengreatimportancetoassetmanagement

Inmanufacturing,production,finance,etc.,decisionsareincreasinglytakenbasedonmodelsortechniqueswhichprovidesatisfactory,objectivedecisionmaking,whichguaranteesimprovedcompeti-tiveness,reducingriskanduncertainty,andthatcanbejustifiedtomanagement.However,maintenancemanagershavetakendecisionsbasedonlyontheirexperienceorsupportedbytheadviceofsystemsalesstafforconsultants.Thislackofmodelsandtechniquesintheareaofassetmanagementleadstounderperformingmaintenancedepartmentscharacterizedbyareactiveapproach,underutilizedmainte-nanceinformationsystems,inaccuratelymanagedcosts,noscheduledmaintenancehours,feedbackonworkqualitynotbeingprovided,etc

Thisbooklookstopromoteandaddresstheapplicationofobjectiveandeffectivedecisionmakinginassetmanagementbasedonmathematicalmodelsandpracticaltechniquesthatcanbeeasilyimple-mentedinorganizations.Thiscomprehensiveandtimelypublicationaimstobeanessentialreferencesource,buildingontheavailableliteratureinthefieldofassetmanagementwhileprovidingforfurtherresearchbreakthroughsinthisfield.Thistextprovidesthenecessaryresourcesformanagers,technol-ogydevelopers,scientistsandengineerstoadoptandimplementoptimumdecisionmakingbasedonmodelsandtechniquesthatcontributetorecognizingrisksanduncertaintiesand,ingeneralterms,totheimportantroleofassetmanagementtoincreasecompetitivenessinorganizations

SUMMARY OF TOPICS

Therelevanceofmaintenanceinorganizationshasincreasedconsiderablyoverthelasttwodecades;thisimportanceislinkedtotheintroductionofagrowingnumberoffactorswithaninfluenceonefficientassetmanagement.Theexistenceofincreasinglycomplexequipmentandprocesses,theincreaseinthenumberofassets,thespeedoftechnologicalchange,theneedtoreducecostsinthemodernworld,togetherwithincreasesinthelevelofexcellenceofcommercialgoalssuchasqualityanddeliverytime,andconcernforthesafetyofworkersandtheenvironment,makeassetmanagementanimportantsource

casespracticalapplicationinbusiness.Optimum Decision Making in Asset Managementisaimedatthe

above-mentionedtargetaudienceworldwideandbecauseofthenumberofchaptersitcontainsandthevarietyofthesubjectsanalysed,itprovidesanin-depthlookatcurrentglobalconcerns

IMPORTANCE OF EACH CHAPTER

Thebookisstructuredintwoparts.Thefirstpartconsistsof11chapterswhichincludecontributionsbyresearchersfromtheSpanishNetworkofExcellenceinthemanagementofPhysicalAssets,whichbringstogethermostofthebestSpanishresearchersinthefieldofassetmanagement.Thesecondpartconsistsof9chapterswithcontributionsbyauthorsfromdifferentcountriesincluding:TheUK,France,theNetherlands,Portugal,theUkraine,SaudiArabia,Chile,Venezuela,Panama,theUnitedStatesandIndia.Thisgivesamorecompleteviewofthestateofassetmanagementaroundtheworld

Ofthe57membersoftheeditorialboardandauthorswhohaveparticipatedinthisbook,atleast20havecarriedoutactivitiesrelatedtoassetmanagementindifferentcommercialorganizations,bring-ingpracticalvision,butalsomotivatingimprovements,advancesandnewtechniquestobeappliedtocompanies.Thisfavoursorientationofresearchtowardsrealapplicationinorganizations,whichispartofthevalueaddedbythisbook.Thereisalsoasignificantflowofideasandexperiencethroughcol-laborationasreviewerswithanumberofauthorswhohavecontributedtothebook.Thesuggestions,commentsandideastheyprovidetheircolleagueshavebeenenrichingforallofus,seedingmeaningfuldevelopmentsinknowledge.Forallthesereasons,wewishtothankeachofthem

Abriefdescriptionofthetwentychapters,withregardtotheirresearchmaterialandtheconclusionsreached,arecollectedandsummarizedasfollows:

Chapter1describesamaintenanceandreliabilitymanagementmodelfortheproject:DesignandConstructionoftheThirdSetofLocksinthePanamaCanal.Thismodelconsistsofeightsequentialmanagementbuildingblocks.Thefirstthreebuildingblocksareconcernedwithconditionmaintenanceeffectiveness,thefourthandfifthensuremaintenanceefficiency;blockssixandsevendealwithmain-tenanceandassetlife-cyclecostassessment,andfinallyblocknumbereightensurescontinuousmainte-nancemanagementimprovement.Thischaptercouldbeusedtoassistdifferentplantteamsindesigningtheoptimalstrategiesformaintenanceandinspectionoftheassets;additionally,recommendationsforoptimizingtheprocessesintheareasofmaintenanceandreliabilitymanagementarealsoincluded.Chapter2presentsamulticriteriamodelconstructedbymeansofMeasuringAttractivenessbyaCategoricalBasedEvaluationTechnique(MACBETH)toselectthemostsuitablecombinationofmain-tenancepoliciesinthedifferentsubsystemsthatmakeupanoperatingtheatre.Adecision-makinggroupincludingtheHospital’stechnicalservices,environmentalandoccupationalriskpreventionmanagers,healthcaremanagers(operatingtheatresandhealthactivityprogramming),healthcarestaff,technicians,purchasingservicesmanagersandHospitalexecutiveswasusedtodeterminetherelevantdecisioncriteriaandtheirweightings.Markovchainswereusedtocalculatethemeanavailabilityforrepairablesystems.Thisisaimedatincreasingtheavailabilityoftheoperatingtheatre,therebyincreasingphysicalsafetyduringpatientoperationsandreducingthenumberofdelayedoperationsduetotechnicalmalfunctions.Chapter3focusesoncriticalinfrastructureswhicharebasicserviceprovidersforsocietyandsoneedtobeeffectivelyprotectedagainsthazards.Currenteconomicandpoliticaltrendsmeanthatprivatecompaniesarenowadaystheownersoroperatorsofmostcriticalinfrastructure.Thepreventionactivitiesrequiredtoanticipateorreducetheimpactofcriticaleventsaffectingcriticalinfrastructuresareanalysed.Additionally,thischapterexplainsthemainreasonswhypublic-privatepartnershipsaresometimesvalu-ableforensuringthatcriticalinfrastructuresarecorrectlymaintained.Theaimistopromotethesharingofresourcesandinformationbetweenpartnersinvolvedtoenhancetheoverallresiliencelevelofcriticalinfrastructuresandachievebetterdecisionsbycriticalinfrastructuresmanagers

edge,andtheimpactthiscanhaveontheorganization.Maintenanceworkersessentiallyworkbasedontheirexperienceortacitknowledge,whichisdifficulttomeasureorexpress,butneverthelessthisuntransmittedknowledgecanleadtohighcostsforthecompanybecauseofincreasedstoppagetimesforproductionandservices,lossofenergyefficiency,oranincreaseinadaptationtimeofnewstaff.Thischapterdescribesthefactorswhichinfluenceknowledgemanagementinmaintenanceengineering,andtheireffectonindustrialproduction,aswellasidentifyinghowknowledgemanagementinassetmanagementworks,andhowitmaybeimpededormademoreefficient

Chapter5analyseshowmaintenancedepartmentsofcompaniesgenerate,transferanduseknowl-Chapter6showshowmaintenancemanagementforbuildingshasbecomearesearchareaofgreatinterestbecausetheyarerequiredtooperateefficiently.However,whiletraditionallybuildinginformationmodelshavemainlyaddressedtheconstructionsector,recentlytheresearchfocushasshiftedfromearlylife-cyclestagestomaintenance,refurbishment,deconstructionandend-of-lifeconsiderations,especiallyofcomplexstructures.Assetmanagementtoolssuchasfacilitiesmanagementprovidetheapproachandrequiredelementstoachievegreaterefficiencyandeffectivenessinbuildinglife-cyclemanagement.Thischapterintroducestheapplicationofassetmanagementinbuildingsandhowthedevelopmentofbuildinginformationmodellingisthekeyelementinallowingeffectiveimplementation

mationabouttheiroperatingconditions,bothtointernalcontrolmechanismsandtoothermachinesorexternalsystemsforanalysis,decisionmakingormaintenanceactivity.Thischaptershowsareferencemodeldevelopedfromanumberofcasestudies(sheet-metalprocessingmachines,toolmachines,specialmachinery,aerogenerators,compressors,etc.),whichallowsefficientmanagementoftheafter-salesser-vice.Thismodelrelatesafter-salesservicetechnologywithproducttechnologies(Industry4.0)intheareaofafter-salesmaintenance.Threelevelshavebeenidentifiedatwhichcompaniesinthemachinegoodssectormaybeclassified,dependingonthelevelofexcellenceoftheafter-salesmaintenanceservice.Chapter8performsexperimentalanalysisofcrackpropagationbyfatigueinhighresiliencesteels.Thelifeofthecomponentsofastructurecontainingprematurecrackscanbedeterminedbythedegreeofsubcriticalcrackpropagation.OneproblemofhighresiliencesteelsistheirlowtoughnessintheHAZ,whentheyareweldedwithahighheatinput.Thischapteranalysesninespecimensthathavebeenweldedbyasubmergedarcweldingprocesstocheckthattheparametersthatindicatethevaluesoffrac-turemechanicsintheHAZ,aftertheheatcyclesteelhasundergone,inaprocesswithamaximumheatinputof2,327kJ/mm,arestillvalid.Acorrelationbetweenthetheoreticalandexperimentalvaluesisconfirmed.Theexperimentalworkcarriedoutensuresthattheparametersregulatingthemechanismoffractureremainvalidundertherulescompatiblewiththedesignofthebasematerialandthatasfaraspossibleacorrelationisestablishedbetweenweldingparametersandthoseobtainedinfracturetests,sothatiftheresultsofthetestsarenotsatisfactory,theappropriatesolutionmaybeappliedtotheweldingfortheparametersgoverningfractureteststobeacceptable

Thedevelopmentandtheimplementationofadvancedactuationsystemssuchaselectromechanicalactuatorshasincreasedbecausetheyintensifytheeaseofcontrolofthesystem,provideoptionsforre-configuration,maintainfunctionalityduringfaults,andmakeitpossibletocarryoutadvanceddiag-nosticsandprognosticsforamoreintelligentmaintenance,leadingtoanincreaseofaircraftavailabilitywithlong-termplanningformaintenanceactivities.Chapter10showshowtodevelophealth-monitoringalgorithmsbasedonAIandstatisticaltechnologiestodetectandpredictearlystagesoffailureinagearbox,takingintoaccountvibrationsignalsobtainedfromtheelectromechanicalactuatorsbymeansoftri-axialaccelerometersinon-groundtesting.Thetestingisexperimental,involvingdatacollectionofhealthyandfaultygearsandextractionofasetoffeatureswithdifferentpre-processingtechniques.Chapter11presentsfourcomplementaryapproachestoquantifytheinterpretationofsignalsexchangedinanetworkofsensorsinthepresenceofuncertainty.Theaimistobeabletoassessmeasurementerrorandthecorrespondingriskinordertoreduceoversizingofthemonitoringarchitecturesandbet-terdefinethelevelofconfidenceplacedintheinformationreceivedfromthenetwork.Acomparativeanalysisispresented,accordingtodifferentcriteriaofquality,quantityand/ortypeofdatacollectedbythesensornetworkbetweenBayesiannetworks,TransferableBeliefModel(TBM),DirectedEvidentialNetworks(DEN)andDeepBeliefNetworks(DBN).Thisincludestheresourcesnecessarytoimplementeachmethodinordertounderstandmeasurementortoreduceerrorsrelatedtouncertaintyinasensornetwork.Thisanalysiswillassistinidentifyingthemostsuitablemethodforeachproblemdetectedbyasensornetwork

Chapter12setsoutanumberofimplicationsforpractitionersofassetmanagement,suchasthatisamultidisciplinaryandstrategicpracticewhichshouldlookatthecompletelifetimeofassets,andwherebestpracticeistoclosetheloopofobjectives,performance,interventions,expectedperformance,andnewperformancefigures,takingaccountoftheknowledgeofexperts.Itpresentsapracticaltwelve-stepapproachanddevelopsanassetlife-cycleplaninwhichsessionswithexpertsareusedtoidentifythemainlifetimeimpactsthatmaybeusefulinguaranteeingorincreasingthevalueoftheassettothecompany.Chapter13providesinsightsintoreal-lifeapplicationsofadvancedmaintenancetechniques,inordertosupportcompaniesandpractitionersinmovingtowardsbetter-informedmaintenancedecisionmak-ing.Threecasestudiesareintroduced,correspondingtocompanieswithdifferentmaturitylevelsintheusageofadvancedmaintenancetechniques,tohighlighttypicalproblemsbusinessesexperienceintheapplicationofprognostictechniques.Afour-stepprocedureisdescribedthatguidespractitionersintheapplicationofadvancedmaintenancetechniques,therebyovercomingthedifficultiesofapplication.Chapter14focusesonimprovingenergyefficiencyindistrictheatingbyimplementationofinfor-

Chapter15exploresoffshorewindprojectsconsideredtobemegaprojects,thatis,withahighlevelofcomplexity,especiallyatthebeginning,whichaccumulatehighrisksresultinginahigherlikelihoodoffailure.Thecurrentliteratureregardingoffshorewindprojectsfailstoaddresstheplanningaspect,inparticulartherisksanduncertaintiesoccurringinthisphase.Inthischapter,aDelphistudyisdescribed,involvinginterviewswith26expertsfromavarietyofbackgroundsintheoffshorewindindustryinTheNetherlands.Aframeworkispresentedthatdepictstheplanningphaseofanoffshorewindproject,alongwithtenrisksandsevenuncertaintiesthatarecommonlyfoundinoffshorewindprojects.Thestructureoftheprojectandtheroleofgovernmentisalsoanalysed

Chapter16analysestheprocessbywhichthemachineryisprepared,sothattheproductisavailableinthequantityandatthemomentrequiredbythecustomer.Theseset-upactivitieshavetraditionallybeenconsideredawastefuloperation,asareotherlogisticaloperationsincompanies;however,itisinfactofgreatimportanceinthemoderncompetitiveworld.Thischapteranalysesthevariablesthatcanaffectthedevelopmentofset-upprocess,thetypologyofoperationsintheset-upprocess,thetimesinvolved,amethodologyforanalysisandimprovementoftheset-upprocessandacontrolsystemfortheimprovementsgained

Chapter17describesanamenablemanagementofrisk,consideringallthetypesofriskthatcanbeapplicabletoassetmanagementthroughaholisticapproach,whichisakeyelementintakingoptimaldecisions.Itanalysesdifferentfactorsthatdeterminewhetherriskassessmenthasbeendoneeffectively,suchasprocessinformationavailability,understandingofrisks,internalcontrol,changemanagementandpersonnelmanagement.Itpresents,inaddition,apracticalapproachusingaSarbanes-Oxley(SOX)frameworkinordertoimplementaproperinternalcontrolframework,whichissustainableandadapt-abletoeachcompanyorcase

Chapter18introducesthereliability-basedmaintenancephilosophywiththegoalofenhancingthereliabilityoftheassetunderconsiderationatoptimalcost.Thismostlyqualitativemethodologycandeterminemaintenanceintervalsbasedonpastexperienceandage-explorationmethods.Themethodprovidesaquantitativewayofdeterminingmaintenanceintervalsusingtheprinciplesofreliabilityengi-neeringforrepairablesystems.Thisisdata-based,relyingonfailureandotherdatageneratedbyassets.Itcomplementsthereliability-centredmaintenancephilosophywhilehelpingtoimprovetheefficiencyandeffectivenessofindustrialassetmaintenance

sumedinMozambique.Thesesystemsrequiredesigntoolstosupportthestrategicandoptimisedusedofavailablesocio-ecologicalresources/assets,andwhichalsoincludethevariousagentsinvolvedinthedecision.Thischapterthereforedevelopsanoveltoolforthestrategicdesignofwood-fuelenergysys-tems,called2MBio.2MBioisaparticipatoryconceptualdesigntoolthatprovides:aformalizedcommonspacefordialogue,allowingparticipantstoexpresstheirknowledgeandexperienceonthequestionof

Chapter19analysesthewood-fuelenergysystemswhichrepresentaround70%oftheenergycon-“why”and“how”toaddressproblemsandsolutions,andfacilitatesparticipatoryconceptualdesignofcomprehensiveandintegratedstrategies,policies,projectsandsolutionsforwood-fuelenergysystems.Chapter20focusesondiscussingtheoccurrenceoffaultswheretherootcausecannotbedetermined,usuallycalledno-fault-foundproblems.Intheaerospaceindustrythisisanimportanttopic.Whenfaced

CONCLUSION

Atthecurrenttimemakingbetter-informedmaintenancedecisionsisofkeyimportancefororganizations.Thus,theprocessofdatacollection,treatmentandmanagementisincreasinglyimportantoverthelife-cycleofassets,inaccordancewithassetmanagementstandardssuchasPAS55andISO55000.Thiscanbeseeninthecontributionsinthisbook,whichanalyseareasrangingfromtheinterpretationofsignalsprovidedbyanetworkofsensors,throughalgorithmstodeterminethefatigueofthestructureandtodetectandpredictearlystagesoffailure,todifferentapproachestostrategicdecisionmakinginassetlifecyclemanagement.Thisbookanalysesfromspecificoperationaldecisionsrelatingfailuremechanismsanddetection,tostrategicdecisionsinvolvingthewholelife-cycleofindustrialplants.Thisisalldonewithoutlosingsightoftherisksanduncertaintiesinvolvedinanyreal-lifedecision-makingprocess.Thisbook,therefore,willstimulatetheideathatdecisionsrelatedtothemanagementofphysicalassetsshouldceasetobebasedpurelyonempiricalevidencefromexperienceandunderstandingofmaintenanceengineersandmanagers,andshouldbegintoincorporatetechniques,toolsandmodelsusingintegratedmathematicaltechniques,togetherwithbetterdataandanalyticalandclarificationtechniques,thejudgementsofexperts,andcommonsense.Thisshouldleadnotonlytosatisfactoryorgooddeci-sions,asoptimaldecisionsdonotgenerallyexist,duetofrequentlyconflictingcriteria,butitwillalsoleadtoefficientandeffectivemaintenancesystemswhichseparateworldclasscompaniesfromtherest.Theinterplayoftechniquesrequiredtoachievethis,theapplicationtoevermorecomplexandex-clusiveareas,andtheinclusionofriskanduncertaintyindecisionmakingarequestionswhoseanalysisthisbookattemptstoaddress,andtheyrepresentachallengeforfutureresearchinassetmanagement

María Carmen Carnero

University of Castilla – La Mancha, Spain

Vicente González-Prida

University of Seville, Spain

Case Study on a Maintenance and Reliability Management

Model Proposal:

A Third Set of Locks Project

in the Panama Canal

Carlos Parra

University of Seville, Spain

Adolfo Crespo Márquez

University of Seville, Spain

1 MAINTENANCE MANAGEMENT MODEL PROPOSED FOR THE PROJECT: THIRD SET OF LOCKS IN THE ACP (AUTORIDAD DEL CANAL DE PANAMÁ) 1.1 Introduction to Maintenance Management Model

The Maintenance Management Models are frequently associated with a wide range of difficulties Why

is this function, at least in appearance, so difficult to manage? We have carried out a review of literature

to find out some of the reasons:

• Lack of maintenance management models (Parra and Crespo, 2012) There is a lack of models that could improve the understanding of the underlying dimensions of maintenance Maintenance is somewhat “under-developed” with a lack of effective prevention methodologies and the integra-tion of said methods in manufacturing companies in most continents;

• Wide diversification in the maintenance problems Maintenance is composed of a set of activities for which it is very difficult to find procedures and information support systems in one place to ease the improvement process Normally, there is a very wide diversification in the problems that maintenance encounters, sometimes a very high level of variety in the technology used to manu-facture the product, even in businesses within the same productive sector; therefore, it has been difficult to design an operative methodology of general applicability;

• Lack of plant/process knowledge and data Managers, supervisors and operators typically find that the lack of plant and process knowledge is the main constraint, followed by the lack of historical data, to implement suitable maintenance policies;

• Lack of time to complete the analysis required Many managers indicate how they do not have the required time to carry out suitable maintenance problems analysis Day to day actions and deci-sion making activities distract them from these fundamental activities to improve maintenance;

• Lack of top management support Lack of leadership to foster maintenance improvement grams, fear of an increase in production disruptions, etc., are other common causes of mainte-nance underdevelopment in organizations;

pro-• Exigent safety and environmental factors In addition to process and technology related issues mentioned above, new and more exigent safety and environmental factors such as emerging regu-lations put pressure on a maintenance manager and add complexity to this function

Some authors (Parra & Crespo, 2012) have worked on the characterization of the complexity found

in managing the maintenance function in a production environment, creating tools where we are able

to value each one of previously reviewed factors for a certain organization (with a degree of fulfilment – DFi), and evaluate them according to environmental aspects (with a relevance factor – RFi) The maintenance management complexity index can be helpful as one way of comparing across different production environments to help decide the relative effort and resources required to maintain them

1.2 Proposal for a Generic Model of Maintenance Management

for the Project: Third Set of Locks in the ACP

The generic model proposed for maintenance management that will now be proposed and defined tegrates other models found in the literature for built and in-use assets, and consists of eight sequential

in-management building blocks (Parra and Crespo, 2012) Each block is, in fact, a key decision area for asset maintenance and life cycle management Within each of these decision areas we can find methods

and models that may be used to order and facilitate the decision-making processes (this model is being

used in the ACP since 2012).

The maintenance management process can be divided into two parts: the definition of the strategy, and the strategy implementation The first part, definition of the maintenance strategy, requires the definition of the maintenance objectives as an input, which will be derived directly from the business plan This initial part of the maintenance management process conditions the success of maintenance in

an organization, and determines the effectiveness of the subsequent implementation of the maintenance plans, schedules, controls and improvements Effectiveness shows how well a department or function meets its goals or company needs, and is often discussed in terms of the quality of the service provided, viewed from the customer’s perspective Effectiveness concentrates then on the correctness of the process and whether the process produces the required result (Vagliasindi, 1989; Wireman, 1998; Palmer, 1999).The second part of the process, the implementation of the selected strategy has a different significance level Our ability to deal with the maintenance management implementation problem (for instance, our ability to ensure proper skill levels, proper work preparation, suitable tools and schedule fulfilment), will allow us to minimize the maintenance direct cost (labour and other maintenance required resources) In this part of the process, we deal with the efficiency of our management, which should be less important Efficiency is acting or producing with minimum waste, expense, or unnecessary effort Efficiency is then understood as providing the same or better maintenance for the same cost

In this report, we present a generic model proposed for maintenance management integrates other models found in the literature (Pintelon & Gelders, 1992; Vanneste & van Wassenhove, 1995) for built and in-use assets, and consists of eight sequential management building blocks, as shown in Figure 1 (Parra & Crespo, 2012) The first three building blocks condition maintenance effectiveness, the fourth and fifth ensure maintenance efficiency, blocks six and seven are devoted to maintenance and assets life cycle cost assessment, finally block number eight ensures continuous maintenance management improve-ment The maintenance management model proposed to the project: Third Set of Locks in the ACP, is

presented below (model is based on the Asset Management Standards ISO 55000, 55001 and 55002).

In this section, we will briefly introduce each block and discuss methods that may be used to improve each building block decision-making process (Figure 2) (Parra & Crespo 2012)

1.2.1 Definition of Maintenance Objectives and Strategy

Regarding the definition of maintenance objectives and key performance indicators – KPI’s (Phase 1), it

is common the operational objectives and strategy, as well as the performance measures, are inconsistent with the declared overall business strategy (Gelders et al., 1994) This unsatisfactory situation can indeed

be avoided by introducing the balanced scorecard – BSC (Kaplan & Norton, 1992) The BSC is specific for the organization for which it is developed and allows the creation of KPIs for measuring maintenance management performance which are aligned to the organization’s strategic objectives

1.2.2 Asset Priority and Maintenance Strategy Definition

Once the maintenance objectives and strategy are defined, there are a large number of quantitative and

Figure 1 Maintenance Management Model

Source: Crespo Marquez, A (2007), The Maintenance Management Framework, Models and Methods for Complex Systems Maintenance, Springer, London

Figure 2 Sample of techniques within the maintenance management framework

Source: Crespo Marquez, A (2007), The Maintenance Management Framework, Models and Methods for Complex Systems Maintenance, Springer, London

priority within a maintenance management process (Phase 2), a decision that should be taken in cordance with the existing maintenance strategy Most of the quantitative techniques use a variation of

ac-a concept known ac-as the “probac-ability/risk number” – PRN (Moubrac-ay, 1997)

Assets with the higher PRN will be analysed first Often, the number of assets potentially at risk outweighs the resources available to manage them It is therefore extremely important to know where

to apply available resources to mitigate risk in a cost-effective and efficient manner Risk assessment is the part of the ongoing risk management process that assigns relative priorities for mitigation plans and implementation In professional risk assessments, risk combines the probability of an event occurring with the impact that event would cause The usual measure of risk for a class of events is then R = P

x C, where P is probability and C is consequence The total risk is therefore the sum of the individual class-risks (Parra and Crespo, 2012) The procedure to follow in order to carry out an assets criticality analysis following risk assessment techniques could be then depicted as follows:

1 Define the purpose and scope of the analysis;

2 Establish the risk factors to take into account and their relative importance;

3 Decide on the number of asset risk criticality levels to establish; and

4 Establish the overall procedure for the identification and priorization of the critical assets

Notice that assessing criticality will be specific to each individual system, plant or business unit For instance, criticality of two similar plants in the same industry may be different since risk factors for both plants may vary or have different relative importance

1.2.3 Immediate Intervention on High Impact Weak Points

Once the assets have been prioritized and the maintenance strategy to follow defined, the next step would

be to develop the corresponding maintenance actions associated with each category of assets Before doing so, we may focus on certain repetitive – or chronic – failures that take place in high-priority items (Phase 3)

Finding and eliminating, if possible, the causes of those failures could be an immediate intervention providing a fast and important initial payback of our maintenance management strategy The entire and detailed equipment maintenance analysis and design could be accomplished, reaping the benefits of this intervention if successful

There are different methods developed to carry out this weak point analysis, one of the most well known being RCFA (Root Cause Failure Analysis) This method consists of a series of actions taken to find out why a particular failure or problem exists and to correct those causes Causes can be classified as physical, human or latent The physical cause is the reason why the asset failed, the technical explanation

on why things broke or failed The human cause includes the human errors (omission or commission) resulting in physical roots Finally, the latent cause includes the deficiencies in the management sys-tems that allow the human errors to continue unchecked (flaws in the systems and procedures) Latent failure causes will be our main concern at this point of the process Note that although informal RCFA techniques are usually used by individual or groups to determine corrective actions for a problem, they have limitations that can make the development of long-term solutions difficult

1.2.4 Design of the Preventive Maintenance Plans and Resources

Designing the preventive maintenance (PM) plan for a certain system (Phase 4) requires identifying its functions, the way these functions may fail and then establish a set of applicable and effective PM tasks, based on considerations of system safety and economy A formal method to do this is the RCM (Parra and Crespo, 2012) RCM methodology allows the identification of real maintenance needs starting from the analysis of the 7 questions:

• What are the functions and associated performance standards of the asset in its present operating context?

• In what ways does it fail to fulfil its functions?

• What causes each functional failure?

• What happens when each failure occurs?

• In what way does each failure matter?

• What can be done to prevent each failure?

• What should be done if a suitable preventive task cannot be found?

1.2.5 Preventive Plan, Schedule, and Resources Optimization

Optimization of maintenance planning and scheduling (Phase 5) can be carried out to enhance the tiveness and efficiency of the maintenance policies resulting from an initial PM plan and program design.Models to optimize maintenance plan and schedules will vary depending on the time horizon of the analysis Long-term models address maintenance capacity planning, spare parts provisioning and the maintenance/replacement interval determination problems, mid-term models may address, for instance, the scheduling of the maintenance activities in a long plant shut down, while short-term models focus on resources allocation and control (Duffuaa, 2000) Modelling approaches, analytical and empirical, are very diverse The complexity of the problem is often very high and forces the consideration of certain assumptions in order to simplify the analytical resolution of the models, or sometimes to reduce the computational needs

effec-For example, the use of Monte-Carlo simulation modelling can improve PM scheduling, allowing the assessment of alternative scheduling policies that could be implemented dynamically on the plant/shop floor (Parra and Crespo, 2012)

1.2.6 Maintenance Execution Assessment and Control

The execution of the maintenance activities, once designed planned and scheduled using techniques described for previous building blocks have to be evaluated and deviations controlled to continuously pursue business targets and approach stretch values for key maintenance performance indicators as se-lected by the organization (Phase 6) Many of the high-level maintenance KPIs, are built or composed using other basic level technical and economical indicators Therefore, it is very important to make sure that the organization captures suitable data and that data are properly aggregated/disaggregated accord-ing to the required level of maintenance performance analysis

1.2.7 Asset Life Cycle Analysis and Replacement Optimization

A life cycle cost analysis (Phase 7) calculates the cost of an asset for its entire life span (Figure 4) (Parra and Crespo, 2012) The analysis of a typical asset could include costs for planning, research and devel-opment (R&D), production, operation, maintenance and disposal Costs such as up-front acquisition (research, design, test, production and construction) are usually obvious, but life cycle cost analysis crucially depends on values calculated from reliability analyses such us failure rate, cost of spares, repair times, and component costs A life cycle cost analysis is important when making decisions about capital equipment (replacement or new acquisition) (Campbell and Jardine, 2001), it reinforces the importance

of locked in costs, such as R&D, and it offers three important benefits:

1 All costs associated with an asset become visible Especially: upstream; R&D, downstream; maintenance

2 Allows an analysis of business function interrelationships Low R&D costs may lead to maintenance costs in the future

high-3 Differences in early stage expenditure are highlighted, enabling managers to develop accurate revenue predictions

1.2.8 Continuous Improvement and New Techniques Utilization

Continuous improvement of maintenance management (Phase 8) will be possible due to the utilization

of emerging techniques and technologies in areas that are considered to be of higher impact as a result of the previous steps of our management process Regarding the application of new technologies to main-tenance, the “e-maintenance” concept (Parra and Crespo, 2012) is put forward as a component of the e-manufacturing concept (Lee, 2003), which profits from the emerging information and communication technologies (ICTs) to implement a cooperative and distributed multi-user environment e-Maintenance can be defined (Tsang et al., 1999) as a maintenance support which includes the resources, services and management necessary to enable proactive decision process execution

Figure 3 Life cycle cost analysis

Source: Parra, C and Crespo, A, (2012), Ingeniería de Mantenimiento y Fiabilidad Aplicada en la Gestión de Activos rollo y aplicación práctica de un Modelo de Gestión del Mantenimiento (MGM), Primera Edición Editado por INGEMAN, Escuela Superior de Ingenieros Industriales, Universidad de Sevilla, España

Desar-This section summarizes the process (the course of action and the series of stages or steps to low) and the framework (the essential supporting structure and the basic system) needed to manage and optimize the maintenance strategies in theThird Set of Locks of the ACP.

fol-1.3 Proposal of a Reliability Team to Implement the Activities

within the Maintenance Management Model

With the aim to cover different activities to be developed within each block of the maintenance ment model proposed for the Third Set of Locks of the ACP, it is necessary to create a support group

manage-in Mamanage-intenance and Reliability Engmanage-ineermanage-ing, to promote and run a set of activities at different stages of the maintenance model presented in Figure 1 Initially, this group will implement the MAXIMO system and subsequently, shall control and manage the MAXIMO and develop an optimization process from Maintenance and Reliability techniques

1.3.1 Minimum Requirements of Knowledge for Expert

in Reliability and Maintenance Management

This section contains the minimum requirements of the theoretical knowledge for a maintenance and reliability manager in general However, this document aims to fulfil the intention to be comprehensive enough and include the essential and fundamental knowledge that any expert in maintenance management

Figure 4 RCM implementation process

Source: Crespo Marquez, A (2007), The Maintenance Management Framework, Models and Methods for Complex Systems Maintenance, Springer, London

needs to have, regardless of which company or in which country he or she is working The requirements

cover the following areas (EFNMS publication of June 19th 2006 The requirements of Competencies

and Responsibilities for an European Expert in Maintenance and Realibility):

1.3.1.1 Management and Organization

Within this area, it is essential to have a very good knowledge about the importance of maintenance for the economy in the company, for achieving production goals and for the quality of the product, and so

on It is important to have good knowledge of how maintenance activities are organized Therefore, the following knowledge is necessary:

• How to set up a company management policy to be able to participate in its definition as far as

maintenance is concerned to:

◦ Describe why a policy has to be set up and what the requirements are for that policy;

◦ Give examples on in which way the maintenance aspects are in a company management policy

• How to formulate the maintenance policy within a company to:

◦ Give an example of a maintenance policy;

◦ Describe the requirements for a maintenance policy;

◦ Describe the process of the development of a maintenance policy

• How to formulate the maintenance goals to:

◦ Describe the general requirements for maintenance goals;

◦ Describe the process of the development of maintenance goals;

◦ Give examples of maintenance goals;

◦ Describe the relationship between goals and policy

• Different maintenance strategies and how to choose the right strategy to:

◦ Formulate different maintenance strategies;

◦ Describe the reasons behind the choice of a certain strategy

• How to specify the requirements for the maintenance activities to:

◦ Describe the different maintenance activities;

◦ Describe different requirements for the maintenance activities;

◦ Describe the process of the identification, the formulation and the communication of the requirements

• How to organize the maintenance activities, how to choose a suitable organization and assure the

right competence within the organization to:

◦ Describe different types of maintenance organizations (e.g centralized, decentralized, operation with the equipment supplier and/or servicing companies and integration with the production);

◦ Describe the advantages and the disadvantages with the different types of organizations and the combination of them;

◦ Describe how to develop the competence in all the different types of organizations

• How to determine the human and material resources in order to implement the organization to:

◦ State the different types of maintenance resources (e.g tools, material, personnel,