Warehouse in Today’s Business and Benefits of Simulation ...2 Warehouse In General 2.1 The...
Transcript of Warehouse in Today’s Business and Benefits of Simulation ...2 Warehouse In General 2.1 The...
WarehouseinToday’sBusinessandBenefitsofSimulationinWarehousingTuyetTranBachelor’sthesisFebruary2018Technology,communicationandtransportDegreeProgrammeinLogisticsEngineering
Description
Author(s)Tran,TuyetThi
TypeofpublicationBachelor’sthesis
DateFebruary2018
Languageofpublication:English
Numberofpages54
Permissionforwebpubli-cation:x
TitleofpublicationWarehouseinToday’sBusinessandBenefitsofSimulationinWarehousing
DegreeprogrammeLogisticsEngineering
Supervisor(s)Lähdevaara,HannuEnsAssignedbyLähdevaara,HannuEnsAbstract
Warehousingisanindispensablepartformostofbusinessorganizations,althoughitsexist-enceseemstobethreatenbymanymodernbusinessconcepts.Insteadofregardingware-housingasaredundantoperationthatcannotbeeliminated,moreeffortshouldbeputinadaptingthewarehouse-functiontofitintoorganization’sneed,aswellasimprovingitsperformance.
Theobjectivesofthethesisare(a)toprovideessentialknowledgeandusefulremarksre-latedtotoday’swarehousing;and(b)toattestthesignificanceofhowsimulationtechnol-ogycanbeusedtosupportimprovingthewarehouse’sperformance.
Thestudyofwarehouse’stopicswascarriedusingdeskresearchmethod.Informationwascollectedfromdifferentauthenticsources,subsequently,beevaluatedandfurtherex-plored.Intermofsimulation,amodelusedinsupportdesigningtheoptimalwarehouseforanimaginarycasewouldbeconstructedstep-by-step.Acomputer-basedsoftwarecalledEnterpriseDynamic9wasemployedasplatformtobuildthesimulationmodel.
Asaresult,thebenefits,reliabilityandsuitabilityofreplicatedmodelareclearlydemon-strated.Thegeneratedreportsfromsimulationrunsprovidedappreciablyusefulinfor-mationforthetaskofidentifyingproblemsassociatedwitheachactivitywithintheware-house.Naturally,themodelcancontinuetobeusedasverifyingtoolalongtheameliora-tionprocessforthewarehouseinillustrativecase,e.g.,totestanyintendedchangingorsolutioninpriortoimplementation.
Keywords/tags(subjects)warehousemanagement,optimalwarehouse,simulationmodel,improveperformanceMiscellaneous
1Contents
1 Introduction....................................................................................................4
1.1 StudyContext.............................................................................................4
1.2 StudyGoal..................................................................................................5
1.3 StudyMethod.............................................................................................5
1.3.1 EmployedMethods................................................................................5
1.3.2 DiscussionofMethods...........................................................................5
2 WarehouseInGeneral....................................................................................6
2.1 TheImportanceofWarehouse...................................................................6
2.2 Warehouse’sActivities...............................................................................8
2.2.1 ReceivingandUnloading.......................................................................9
2.2.2 Cross-docking.......................................................................................10
2.2.3 Put-away..............................................................................................10
2.2.4 Picking..................................................................................................12
2.2.5 Sortation..............................................................................................16
2.2.6 Packaging.............................................................................................18
2.2.7 LoadingandShipping...........................................................................19
2.2.8 CycleCounting.....................................................................................21
2.2.9 Replenishment.....................................................................................23
2.2.10 QualityConservationandLossPrevention..........................................24
2.2.11 HandlingReturns.................................................................................25
2.3 WarehousePerformanceMeasurement..................................................26
2.4 DesigningWarehouseLayout...................................................................28
2.5 SupportiveTechnologiesandAutomaticScale........................................30
3 TheoreticalBasesOfSimulation.....................................................................31
3.1 Simulation.................................................................................................31
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3.2 PoissonDistributionPois(𝜆)....................................................................32
3.3 ExponentialDistributionExp(𝜆)..............................................................33
3.4 QueuingTheory........................................................................................33
4 SimulationInWarehousing............................................................................34
4.1 MotivationofUsingSimulationinWarehousing......................................34
4.2 ComputerSoftwareforSimulation..........................................................35
4.3 AnIllustrativeCase...................................................................................36
4.3.1 Case-ScenarioandProgramme-Setup.................................................36
4.3.2 SimulationResultsandSuggestedActions..........................................38
4.4 Conclusion................................................................................................43
References............................................................................................................45
Appendices...........................................................................................................48
Appendix1. U-shapelayout(adaptedfromFrazelle2002,187)....................48
Appendix2. Straight-thrulayout(adaptedfromFrazelle2002,188).............48
Appendix3. Modular-spinelayout(adaptedfromFrazelle2002,189)..........49
Appendix4. Multistorylayout(adaptedfromFrazelle2002,190).................49
Appendix5. Actualconnectionsofobjectsintheprogramme.......................50
Appendix6. Capacityofwaitinglines.............................................................50
Appendix7. Data-setupforthearrivingofregularshipment.........................51
Appendix8. Data-setupforreceivingdocks’queue.......................................52
Appendix9. Data-setupforcross-dockingfunction........................................53
Appendix10. Truckonlydepartafterhaving40ordersloaded.....................54
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Figures
Figure1.Warehousetypesandtheirconnection(adaptedfromFrazelle2002,10)....8
Figure2.Initialsketchofwarehouselayout...............................................................36
Figure3.Simulationrecordedresult:utilizationlevelofindividualfunction.............39
Tables
Table1.KPIsusedinwarehousingassessment(adaptedfromFrazelle2002,57).....28
Table2.Probabilitythatkdevice(s)canbefixedin1hour........................................33
Table3.Probabilitiesthatxhour(s)isrequiredtorepairadevice.............................33
Table4.Performanceratecorrespondingtoinitialproposition.................................37
Table5.Simulationrecordedresult:processingofproducts(ororders)....................39
Table6.Simulationreportofqueues’status..............................................................40
Table7.Warehouse’sinitialproposition:ImperfectionsandSolutions.....................41
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1 Introduction
1.1 StudyContext
Thetoday’sbusinessisgettingobsessedwithoperationalefficiencyandresources
utilization.Underthatpressure,warehousing,alongwithotherlogisticalsegments,is
forcedtocontinuousimprovement:loweroperatingcost,shorterleadtimeand
higherreliability.Otherwise,itwillinevitablebecomingatargetofeliminationorat
leastminimization.Toabletosatisfythoseexpectations,managersnotonlybeobli-
gatedtoconstantlyupdatetheirwarehousing-knowledges,butalsoneedacom-
puter-basedapplicationthatcanassisttheminquicklydeterminingoptimalsolution
foreachwarehousingtask,aswellaseasilycopingwiththerapidchangeofopera-
tional-related-factors.
Fordecades,scientificexpertshaveregardedsimulationtechnologyasthemostout-
standinghigh-techtool,amarvellouskeyfornumerous“lockedbarriers”thatarise
duringtheoperationinvariousfields;fromhealthcare,media,business,tomilitary
industry.Nonetheless,plentyaspectsofsimulationarenotwellunderstoodbyma-
jorityofregularbusinessmen:itsefficiencyissuspected,itscostisover-estimated,
anditspathwayfrominitialapproachtofinalimplementationisstillamysteriousto
manyworkers.
Considertheaboveindicatedissues,inthisthesis,theauthorintendstointroduce
anddiscussabouttheusageofsimulationinwarehousingatentry-level.Suchthat
readerswithno-prior-knowledgeofsimulationcangettoknowaboutit.Inaddition,
allthewarehousing-related-concernwillbestudiedmeticulously:mainfactorsthat
affectperformanceofeachtask;theimportanceofharmoniouscooperationbe-
tweendifferentfunctionareas;howandinwhichwayoperationalefficiencyofindi-
vidualactivityimpactontheoverallwarehousingsystem;etc.
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1.2 StudyGoal
Thethesis’sprimeobjectivesaretoprovidereadersthemostessentialknowledges
andusefulremarksrelatedtowarehousing;andtoattestthesignificanceofhowsim-
ulationcanbeusedtosupportimprovingwarehouse’sperformance.Forafiner
demonstration,asupportivemodelusedintesting,correcting,andoptimizingthe
operationswithinawarehousewillbebuiltandanalysedstep-by-step.Certainly,the
warehousing’skeytopicswillbedeterminedandpresented.Withtheforthcoming
providedinformation,theauthorexpectsthisthesistobecomeausefulsourcefor
readers,whointerestinthewarehousingfield;aswellasworkers,whoareappealto
creatinganoptimaldistributioncentreorreconstructingtheexistingoneforbetter
productivity.
1.3 StudyMethod
1.3.1 EmployedMethods
Thestudyisconductedbyusingdeskresearch(secondaryresearch)andconstructive
method(designscienceresearch).Thewarehousefundamentalactivities;theirprin-
ciplesofoperation;thecontemporarystandardofmeasurements;aswellasother
relatedmatterswillbecollectedfromdifferentauthenticsourcesandsubsequently
beexaminedforfurtherexploration.
Intermofsimulation,anillustrativemodelwillbeconstructed,analysedandevalu-
atedusingassociatedorcorrelativemathematicalconcepts.Inadvance,thescientific
basesofsimulationwillbepresentedtosupportreadersincapturingthetechnology.
Naturally,attheend,thosekindsofcertifiedknowledgewillhelpprovingthevital
roleofsimulationinwarehousingwithoutlosinganycredibility.
1.3.2 DiscussionofMethods
Deskresearchisamethodfortheinsightstudyofasubjectorfield;carryingbyac-
cessandevaluatethepreviousfindingsofotherresearchers(Travis2016).The
methodallowsonetorapidlyapproachawiderangeofavailableinformation,freely
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comparingthembeforeselectthemostsignificant,applicableandtrustworthydis-
quisitions.Secondaryresearchisthebestchoicewhenthefieldorscaleofstudyis
large,suchthatitistootime-consuming,difficultorcostlytoconducttheactualex-
perimentstolearnaboutthesubject(i.e.,primaryresearch).Nonetheless,Prescott
(2008)warningthattheanteriorresearchcanbeoflowqualityoroutdated.There-
fore,itiscrucialtotakenecessarystepstoappraisethereliabilityandvalidityofoth-
ers’research-papersinpriortoreferring.(ibid.)
Designscienceresearchisamethodusedindesigninganddevelopingsolutionsfor
thetargetofimprovingperformanceofexistingsystems(Dreshch,Lacerda,&An-
tunes2015,56).Pasian(2015)claimsthatthemethodisaboutproducingasystem,
whichbottomofheartisbasingonacademictheories,tosolvepracticalproblems.
Thereby,thestudytechniquehelpsreducesignificantlythegapbetweenacademic
conceptsandreal-lifepractice.(ibid.,95-96.)
Themostinitialandfundamentalrequirementforonetosuccessfullycarryingacon-
structiveresearchismustfullycomprehendthesituationofproblems,aswellasthe
setofpertinenttheoreticalbasesthatcontributetobuildthesolution.Ingeneral,de-
signscienceresearchobeyingtheabductivelogicofreasoningthatinvolvingbothin-
ductiveanddeductiveargumentations.Whiledeductivelogicisemployedasaca-
demictheoriesbeingappliedtoacircumstantialeventorprocess;statingthegeneral
conclusionaboutapplicabilityofresultsfromexaminedsituationsrequirestheuseof
inductivelogic.(ibid.,97-98.)
2 WarehouseInGeneral
2.1 TheImportanceofWarehouse
Althoughwarehouseoftenbeingunder-evaluatedasjustaplacetostoringgoods
anditsexistenceseemstobethreatenbymanymodernbusinessconcepts,suchas
integratedstrategy,just-in-timetechniqueorleanmethod.Frazelle(2002,9)stated
thatthesupplychaincollaboration,frominitialmanufacturingpointtofinalconsum-
ingmark,willneverreachtheoptimumlevel,wheretheusageofwarehousingbeen-
tirelyterminated.Asamatteroffact,warehousingprovidesaback-upsolutionto
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dealwithunexpectedproblemsariseinthebusinessworldthatfulloferrors:human
mistakes,machineryfaults,aswellasnaturaldisasters.Forinstance,thestockedma-
terialscanserveasquicklycompensationforunusualshortageoccuralongthepro-
ductionlines.
Basedonitsfunctionsorpurposes,Frazelle(2002)classifiedwarehousinginto7cate-
gories:
o Rawmaterialandcomponentinventory:materialsbeforth-preparedforfuture
requestsfrommanufacturingorassemblingchains.
o Work-in-process warehouse: temporary accommodate unfinished products
whentheyarewaitingfortheirturnoftransferringtodifferentstages.
o Finished-goodsrepository:isaimedtocoverforanypotentialshortagesorre-
solvecontradictionsbetweencustomerdemandandproductionschedule.
o Distributioncentre: isplacewhereproducts fromassociatedsourcespassed
by,optionallybesplitormixedbeforeshippingtocustomers.
o Fulfilmentcentre:providesdispensationservicetoindividualcustomerswith
smallerorders.
o Local warehouse: insures quickly-response to clients’ desire, as responsible
areaismoreconcentrated.
o Value-addedservicewarehouse:iswhereproductshavingcustomizedpackag-
ingorbeingappendedwithextradetails,suchaslabel,trademark,pricetag.
Usually,reversedordersarealsoprocessedhere.(ibid.,9-10.)
Thesebranchesconnectcloselywithoneanotherandformafull-setofwarehousing
network,whichisillustratedinthefigurebelow:
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Figure1.Warehousetypesandtheirconnection(adaptedfromFrazelle2002,10)
Comprehensibly,inextensivescale,warehousingbenefitstheorganizationbyvarious
means.Forexample,thestockingofmaterials(products)frommassorseasonalpur-
chasing(manufacturing)cansupportobtainingtheeconomiesofscale.Withthesim-
ilarmanner,theemployingoflocalstorageandvalue-addedwarehousecanrespec-
tivelyhelpreducetheprocessingtimeandimprovethecustomer-service-quality.Be-
sides,onsomeoccasion,foodandbeverageproductionsrequiretoholdunfinished
goodsatfermentationstageinnecessaryamountoftime;thismakeinventorybe
oneofthecompulsorysteps.Andassuredly,therearemanymoreutilitiestoname.
2.2 Warehouse’sActivities
Despiteofbeingregardedasoneofthemostcomplexworkingenvironmentsthatin-
cludesmultifariousconstituentfunctions,warehousingoperationcomplieswitha
certainsetoflogicalprinciples.Inmostcases,tasksmustbearrangedinatreepat-
ternandthefailureofanyactivitywillundoubtedlyaffecttheothers,throughdirect
orindirectmanner.Therefore,itiscrucialtohaveagoodoperationalplan,whichwill
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helpminimizethenumberoferrors,oratleastpreventmistakesfromfurtherex-
panding(e.g.,byearlierdetection).Thefollowingtextwillpresentthewarehouse’s
activitiesincorrespondingwithnormalmovementofgoodswithinadistributioncen-
tre;sothatreaderscaneasilyperceivetheirconnectionaswellastheirindividual
contribution.
2.2.1 ReceivingandUnloading
Priortothearrivingofanytruckatinboundarea,theassociatedcarriermustbooka
scheduleandinformwarehousemanageraboutallinformationrelatedtotheship-
ment.Baseonthevalue,property,andhandlingunitofgoods,themanagerwillde-
termineanappropriateinspectionprocedure,unloadingmethod,timerequiredfor
thejob.Andassignaplaceforitinasuitabledockthatresponsiblebycertainnum-
berofoperators,withspecifictypesofforkliftvehicleandequipment.Forexamples,
goodsofhighvaluewillbeallocatedtothemostsecuredspot;easydamagedprod-
uctsshouldbeinspectedthoroughly;dedicatedforklifttruckandextraequipmentof-
tenusedtosupporttheunloadingofheavyorpalletizedcommodity;andsoon.
Oncethetimeisset,itisessentialtoassurethattruckdriverssticktighttothetime-
tableandreachthestationontime,becausethenumberofdocksateachwarehouse
islimitedandtheyusuallyinreservedstate.Furthermore,thehandlingtasksmustbe
designedsothatitwillflowassmoothaspossible.
Ingeneral,theworkofinboundteamincludes:comparingthequalityandquantityof
arrivingitemsagainstinformationindicatedinpurchaseorders;unloading;andtag-
ginggoodsbyproperunit(ifapplicable).Alsoatthispoint,theteamleaderaddresses
allrelatedmatters,suchasdamagedormissingofproducts,incautiouscovering
methods,latedeliverytime,alongwithanyotherdiscoveredissues;andhaveitveri-
fiedbythecarriermen.Oncethereceivingprocessfinishedandshippingdocument
collected,anoperatorisassignedtoregisterallinvolveddatatothecompanyinter-
nalinformationsystem;sothat,otherconcerneddepartments(e.g.,purchasing,fi-
nanceorproduction)beimmediatelyinformedaboutthearrivingshipmentsaswell
asanyariseproblems.
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2.2.2 Cross-docking
Inwarehousingcontext,thetermcross-dockingreferstotheprocessofdirectly
pushingcommodityfrominboundentrancetooutboundarea;whereitoptionalbe
breakingintosmallerpieces,combiningwithothertypesofproduct,consolidating
andlabellingbeforebeingshippedaway.Asthispracticerarelyinvolvestheinspec-
tionprocedure,subjectedgoodsmustbeoriginatedfromtrustworthysources.Ac-
cordingtoDelBovo(2011),itisfavourableappliedtolow-touch,durablegoodswith
high-volumeandrestrictednumberofstock-keeping-units(SKUs),nevertheless,per-
ishableorconditionalcontrolledproductsarehavingmoreandmoredemandonthis
method.
Itiseasytorecognizethatcross-dockingbringsmanybenefitstotheoperationoflo-
gistics:shortenorder’sleadtime,eliminateinventorycost,reducetransportation
costaswellaslabourcostthroughintegrationandbetterresourceutilization.Yet,it
isquitechallengingtohavetheconceptsetupandoperateefficiently.Regardingto
theplanningphase,DelBovo(2011)havelisted2mainconcerns:designingthefacil-
ity,sothatthereisenoughreservedspaceforthemovementofgoodsandhandling
equipment;andestablishingacompetentmetrical-baseforthemerchandise-selec-
tion,sinceonlyseveralranksofproductareeconomicallyfitwith“crossing”function.
Usually,becausethecross-dockingareahasno“back-up”spaceforshipmentstolin-
geraround;itisnecessarytoobtainaneffectivecommunicationsystembetweendis-
tributioncentreandcustomer,carrier,aswellassupplier,tosecurethatmaterials
willarriveandshippingtruckswillbereadyattherightplace,intherighttime,with
therightamountandcategory.
2.2.3 Put-away
Shipmentthatnotplannedforcross-docking,afterundergoingthereceivingprocess,
issuggestedbyVitasek(2007)tobeput-awaytoitsstored-placeonthesameday,
otherwise,itcanleadtospacecongestion,productdamaging,aswellashindering
theflowofsubsequentprocesses.Sunol(2017)describeditsmainobjectiveasapro-
cessoftranslocatinggoodstothemostoptimumstoragespot,andlistedindetailits
coreresponsibilities:
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o Maximizingthespaceutilization.Startfromcollectingtheconsistentandaccu-
ratedataofproducts;whichincludethetype,size,height,weight,andtheir
receiving-shippingfrequencywithassociatedvolume.Itisrecommendedtoau-
tomateasmuchaspossible thegatheringwork, so that thecollected infor-
mationisreliableforlateranalysinganddecisionmaking.
o Quicklyandefficientlyinstoringgoods.Thisshouldbeguaranteedbyawell-
preparedandfocusing-on-detailsplan,withaclosely-monitoredimplementa-
tionstage.
o Stockingproductsareeasytotrack,findandretrieve.Thefavourablewayis
mixing the use of fixed and dynamic locating.When the first method help
speed-uptheprocessasoperatorsmemorizepositionofitems;thelatterone
offerflexibility,especiallyanadvantageinhandlingseasonalproducts.
o Minimizingtheoveralltraveldistanceby2means.Thefirstapproachisdeter-
miningtheshortestpathwayofproductsfrominboundareatotheirassigned
place;aswellasoptimizetheallocationofeachproducttype,basedonitsor-
derfrequencyandvolume,sothatthetotalmovementwithinthewarehouse
isas smallest.Thesecondone iseliminate theunnecessary-moving through
fullymonitoringtheavailabilityandcapacityofwarehousespace.Thiscanbe
obtainedbyusingradio-frequency-identification(RFID)fortheautomaticre-
cordingandreal-timedisseminationofspace’susagestatus.Or,byusingbar-
codescannerandbinlocationtocontroltheconditionofeveryindividualspot,
nonetheless,theefficiencyisheavyrelyonthecautiousofscanning-man.
o Securingthesafetyofgoodsaswellaswarehouseoperators.Thiscanbeat-
tained through the maintaining of logical-organized and clean warehouse.
(ibid.)
Theput-awayprocessthatfulfilabovequalitieswillnotonlyresultinbetterprofitbut
also happier employees. Without a doubt, a worker who must going around and
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aroundlookingfortherightitemtopick,willeasierfeelfrustratedthantheone,that
cancomfortablycollectitemsandfinishmanyordersinthesameamountoftime.
2.2.4 Picking
Pickingisthestageinwhichgoodsofproperamountarepulloutfromitsinventory
areatofitintodifferentorders,itisthemostlabour-consumedprocessandapproxi-
matelyaccountfor55%oftotalwarehousingcost(Murray2017a).Toexplainforthis
high-attention-requirementofpickingactivityandcomparetotheprocessingofin-
boundorders,whichareusuallyarriveinbulkquantity;Piasecki(n.d.)claimsthatitis
thenaturalofdistributionstructuretohavegreateramountofoutwardtransactions
withsmallerandlargernumberofitemstohandle;furthermore,theoutcomeof
pickingfunctionissignificantasitdirectlylinkedtocustomersatisfactionresult.
Therearemanymoderntechnologiesavailableforthepaperlessorder-fulfilment
processes,thatgreatlyassistinachievingamoreaccurateandhigherproductivityof
performance.Inwhich,light-directedpicking,voice-directedpicking,radiofrequency
(RF)mobilepickingandaugmentedreality(AR)pickingarethemostpopularand
widestappliedtechnologiesincontemporarywarehousingenvironments.
Inbasicpick-to-lightsystem,alightpanelisattachedineachofthestoragebinor
rack.Whentheitemsbelongingtoaspecificcontainerinvolvedinanorder,con-
nectedlightwillbeilluminated,withthenecessarypickingquantitydisplayed.The
operatorresponsibleforthatorderjustsimplypicktheexactnumberofitemsand
pressconfirmbuttononthepanel.Oncethelightisnolongerbrightenup,itmeans
thatthepickingisdonewiththatbin,operatorcanmovetotheotheronesanddoing
similartasksuntiltheorderisfulfilled.Usingclientsreportedthatthistechnology
helpincreasesthepickingvelocityto10timesgreaterthanthetraditionpaper-
based.Moreover,itsupportsbestininternationalwarehousingaswellasseasonal-
employing-company,sincenoverbalcommunicationisrequiredduringthepicking
processandworkersalsocaneasilymanipulatethedevicewithoutmuchoftraining.
(Murray2016a.)
However,forthetechniquetofullybeeffective,warehousebuildingmusthave
enoughcontrastlightandharmonicvisibility.And,eachstoringregionmayneedthe
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minimumofoneon-duty-operatorbeingreadyforanyupcomingsignal.Thelastbut
nottheleast,physicalinstallationoflightpanelaroundrepositorycanbecostly.
Thepick-to-voicetechnologywasinitiallyadaptedfornon-barcodedproducts,
throughitsspeechrecognitionandsynthesisprogram,warehouseworkerscanusea
headsettointeractwithwarehousemanagementsystem(WMS).Ingeneral,opera-
torspicktherequesteditemsaccordingtovoicingcommand,thenreportbackfor
verificationbeforecontinuingwiththenextinstructions.Yet,extrarepetitionsof
commandmaysometimesberequired.Thisregulationhelpsreducefrom80to90
percentoftheordinarypickingerrors.Besides,itallowsworkerstooperatefreelyin
differentareawithoutmuchofconcernaboutothervisionsignsorcarryingaddi-
tionalhandhelddevice.(Murray2017b.)
WithRFmobilepicking,everyscanningactionisautomaticrecorded,enablesmanag-
ingdatabasetocaptureimmediatelyallinformationrelatedtoproducts,suchasre-
mainingquantity,currentlocationortransfer-statusofeachindividualitem.Thisnot
onlyhelppushingemployeestobeingmoreattentiveandresponsiblewiththeir
work,butalsomakeiteasierforlaterinventoryanalysistasks.(Melendez2013.)
AccordingtoKennedy(2017),thetechnologyiswidelysupportedbymanyWMSs
andappliedwellinallkindsofwarehousingforms,especiallyinbiggerandmore
complexsystem.Nevertheless,maintenanceandreplacementcostfortheequip-
mentcanbehighduetotherecklessinusingofemployees.Italsorequiresmorein-
tensivetrainingforoperatorstobeabletohandlethedeviceproperly.
ARpickingsystemassistwarehouselabourstooperatefasterandmoreefficientin
variousmeans.Firstly,itdisplayspickinglisttoworkersviathevisualfield.Next,asa
productispicked,anopticalreaderisusedtoscantheassociatedbarcode-tagfor
verification.Inthesubsequentpaces,itguidesoperatorstoanothermostrational
pickingplaceandregeneratethesameprecedingpattern.Inaddition,becauseallob-
servablescenesaheadtheAR-technology-equipped-employeesiscapturedand
savedautomatically,itisextremeconvenientforanylaterinvestigation,eitherre-
gardingtosafetyincidentsorerroneousshipments.Furthermore,workerscansimply
showthevideoofwhentheyencountertroubleordifficultytoaskforhelpaswellas
moreadvancedtrainingfromtheirsupervisor.(Montgomery2016.)
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Eventually,ARpickingcanberegardedastherefinedcombinationofthe3previous
discussedtechnologies.Itinheritedmostofthestrengthsandeliminatesmuchofthe
drawbacks.Thelittleremainingdownsideisthestrictlyrequirementofvisible
enoughworkingspace.
Theultimateobjectiveofpickingfunctionistocompleteasmuchaspossiblethe
numberofaccurateandon-timeorders,whileensuretheconditionsofgoodsare
preserved.Therefore,selectinganappropriatepickingmethodforeachtypeofware-
houseisquitecriticalandchallenge.AccordingtoPiasecki(n.d.),theaffectingfactors
include:propertiesofproducts,numberofpicksperorder,numberofitemsineach
pickaswellasthetotalamountoftransactionsandSKUs.
Often,thepickingworkisdividedintodifferentclasses,basedmainlyonthescaleof
ordersandonintegratinglevelineachpick.Withrespecttothefirstcriteria,there
are3groups,nameaspiece,caseandfull-palletpicking.Intermofthelatterstand-
ard,pickingisbindingwith4methods,whicharewave,zone,batchandbasicorder
picking.Piasecki(n.d.)havedoneagoodjobonclarifyingthesecategories:
o Piece(broken-case)pickingistypicalapplyforsystemthatpossesslargenum-
berofSKUswithshortcycle time,whereonly smallamountofgoodsbeing
pickedatatime.Postalofficeandsparepartsprovideraremainlyemploying
thiskindofoperation.
o Casepicking should fit distribution firmwith fewer sumof SKUsandhigher
number of picked items per SKU, compare to the broken-case picking. This
meanthattheproductsarehavingmoreconsistentfeatures.
o Full-pallet(unit-load)pickingisthemostconvenientandsimplepickingform,
whereoneorseveralpalletsofthesamecommodityarepickedatatime.
o Basicorderpickingoperatessothateveryindividualorderisprocessedsepa-
rately.Itisessentialtodesignagoodpickingflow,becausenormallywitheach
order,thereisonlyoneresponsibleoperator,whowillpickstep-by-stepallthe
requireditemsuntiltheorderisfulfilled.Besides,biggerandheavierproducts
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orfast-consumed-merchandisesarerecommendedtoallocatedclosetodepart
areaandmainaisles.
Thesizeandweightofgoodsareprimefactorsthataffecttheselectiononhan-
dling-equipment,suchaspickingcart,palletjack,turrettruck,forkliftvehicles;
anddecisionontheirstoragearea,whethertheyshouldbeplacedonstatic
shelf,palletrackoronthefloor.Fromtheexecutionalprinciple,candeduce
thatthismethodworksbestwithsmallnumberoforders,whichrequireagreat
numberofpickingtimes.Ifapplyforsystemhavinglargenumberoftransac-
tionsortakinglesserpicksineachorder,itmayresultinprocesscongestion
andexcessivetraveling.
o Batchpickingallowsvariousordersbeingintegratedandpickedtogetherinone
trip,meanwhileordersareseparatedbyusingdifferentbagsorboxeswithin
thepickingcart.Atypicalbatchsizevariesbetween4to12orders(whichhav-
ingsomeproportionofsameitems).Thispickingstrategyhelpsreducesignifi-
cantlytheoverallmovementsincesameproductsarepickedatatime.How-
ever,thedetainingoforderstoaccumulateenoughquotaforonebatchmay
over-prolongtheshippingtime.
o Inzonepicking,storageareaissplitintoseveralsections.Andeachonewillbe
responsiblebyapropernumberofworkers,suchthattheflowofpickingcarts
fromonezonetoanotherisconstantlymaintained.Differentmaterial-handling
technologiesmaybeinstalledforspecificzonesbasedontheirdistinctcharac-
teristicsof containingproducts. Systematically,operators ineachzoneafter
pickingalltherequireditemswithinthatregionwillpassthecontainertooth-
ers involved zone using conveyor belts. Thismake themethod become the
most favoured indispensation serviceswithhighnumberofSKUsand large
numberoflow-pickorders.
o Wavepickingisthemixedmethodofbatchandzonepicking.All itemsfrom
differentzonesaresimultaneouslypickedandcongregatedatoutboundarea,
wheretheyaresortedintoseparateshipments.Thispracticeissuitableforsys-
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temwithlargenumberofSKUswhenorderscompriseofmediumtohighpick-
ing-pieces.Butbeawarethat,althoughthemethodhelpsshortingsubstantially
theoverallpickingtime,itputsgreaterofworkonconsolidatingandsorting
activities.(ibid.)
Eachoftheabovepickingsystemhasitsownadvantagesanddisadvantagesforcertain
typeofgoods;imposingadifferentrangeofcostsinvarietyofscope,includepurchas-
ing,installation,operationandmaintenanceexpenses.Theonlycommontipthatbe-
ingsharedisplacethefrequentlyhandledandmassiveproductsclosetomainaisles
andstagingarea.Therefore,itisworthtobecautiousandwise-consideredwhense-
lectthepickingmethods,handlingequipmentaswellassupportingtechnologiesfor
eachstorageregion.
2.2.5 Sortation
Sortationisimportantfunctionforbothinbound-process,whencommoditiesbedi-
rectedtoproperstorageplaces,andoutgoing-operationthatarrangingitemsfordif-
ferentorders.AccordingtoCastaldi(2016),thereisawidevarietyofsortersthatcan
beusedtoorientgoodstoappropriatetracksforfurtherprocessing.Dependingon
theproducts’type,size,shape,weight,aswellashandlingspeedandmethod,noise
allowanceandlimitationofspendableenergy;onecanselectthesuitablesorters
frommanyavailableoptions,whichincludedifferenttypesofbelt,conveyor,pouch,
arm,paddle,andsoon.(ibid.)
Aneffectivemanagementinsortationisunquestionablyimprovethefulfilmentaccu-
racy,bringtimeandcostsaving,offerparceltraceabilityandvisibility.Andcanbeob-
tainedbythehelpoftechnology,forexample,inmeasuringdimensionalinformation
ofpackages,readingandtagginglabels,verifyingandmonitoringthemovementof
merchandises,etc.(Martins2017.)
SomeexamplesofbeingusedsortationsystemsintroducedbyCastaldi(2016)are
describedinthefollowingtext:
17
o Tilted-traysorters: Itemsmanuallyorautomaticallyenterenclosedconveyor
ontrays.Assoonastrayarrivesatthedestination,itshingeddoorsopenedso
thatcontainingparcelsbereleasedandglidedtothenextprocessingstage.For
thebetterproductivity,traysareplacedhorizontallyagainsttheinductionarea
andthenbetiltedforlatersortation.Thisconfigurationissuitedfororderswith
distinctiveunitsoflargevolume.
o Pouch sorters: Goods of various sizes and weights be hanging on separate
pouchesthatmovingontherollerswithpossible-maximum-velocityof10,000
pouchesperhour.Attachingitemstopouchescanbedonemanuallyorauto-
matically.EachpouchisidentifiedbyitsuniquebarcodeorRFIDtag,allowing
thesingle-controloneach individual item;consequently,make it feasible to
prioritizeproductsoractivities.
o “Slidingshoe”sorters:Thesystemisapplicableforawiderangeofgoods,re-
gardlessofsize,shape,weight;andespeciallydesignedforfragileproducts.It
gently and smoothly transferringpackages in rapid speed, aboutmore than
10,000parcelsperhour.Whenitemarrivingatitsassignedspot,theassociated
“slidingshoe”activatedtofreeitfromthecarryingchain.
o Paddlesorters:Thesedevicesareinstalledonsortationbeltstonavigatecom-
moditiesontopoweredornon-poweredconveyinglanes.Itperfectlyfitstofast
operationalmodel that process a large diversity of productswith individual
weightupto75pounds.Whencollaboratingwith450-feets-per-minute-con-
veyor,itcanattainthemaximumsortationspeedof60-cartons-per-minute.
o Pusher sorters:Thisappliance is setupandworks similaraspaddlesorters,
exceptitonlydivertproductsinperpendicularangle.Theoperationalvelocity
isalsolower,canhandleupto40cartonsperminutewhenbeusedinconjunc-
tionwith250-feets-per-minute-conveyor.Asexpected, it is suited forware-
housewith limited linearspaceandrequires theperformancespeedofme-
diumrate.
o Cross belt sorters: Processing goods are contained in separate belted trays.
Their induction or removal only initiate when the transferring chain being
18
stopped.Thishelpincreasetheaccuracyinproduct’snavigationandmonitor-
ing,makingthesystemperfectforsmall,fragileorhighfrictionitems.Moreo-
ver,itisdesignedtobeabletoperformrapidlythetransportationtask.
o Narrowbeltsorters:Merchandisesareconveyedbyvariousnarrowbeltsand
divertedperpendicularlytoeithersidesofthesorters,whenthehighfriction
rollersthatattachedbetweenbeltspoppingup.Thistypeofmechanismiscre-
atedforhigh-throughput-warehouseofsmalltomediumsizedpackages,with
restrictedoperationalspace.
o Pop-upwheelsorters:Thepoweredpop-upwheelsare inadvancebeing in-
stalledonthebottommostofconveyorchains.Whenproductsarriveattheir
destination,thesewheelsareraisedupandhavingphysicalcontactwiththe
basalsurfaceofthecontainers, forcingthemtogetofffromthechains.Alt-
houghthetechnologyisquiteoldandslow,itisemployedduetothelowex-
pense.Itshighestproductivityisaround130casesperminute.(ibid.)
Regardlessofthechoiceonsortationmodel,Rogers(2011)noticedthatthesorters
mustcontainsbarcodescannersorsensors,whichwilldetectthepresenceofpackages
oneachstage,andtransferthatinformationtothewarehousecontrolsystem.Inad-
dition, connectedmonitor program should have a prior-design on how,when and
wheretheflowing-goodsbedivertedwithintheconveyornetworks.(ibid.)
2.2.6 Packaging
Whiletheimposingofwrappersongoodsatmanufacturingfactoryismeanttoat-
tractcustomers’attentionandalwaysbecarriedfollowingaspecificdecorativede-
sign;thepackagingforproductsthatabouttoenterorinbetweendistributionpoints
isaimedtoprotectthemfromdamageduringthetransference.Themerchandises
canbecoveredinseparatedorconsolidatedmanner,withlayerdimensionincreas-
ingfromsmallpackageormediumcasetolargecardboardboxandentirepallet,de-
pendingonthesizeofeachindividualitem.
Theoverlayingformandmaterialmustbecarefullydeterminedsothatitcandefend
19
productsfromenvironmentalhazards,suchasharmfultemperature,waterlog,con-
taminationorstaticfriction,whilstneitherexpandsmuchinweightnorproportion.
Forexample,paperboard,aluminiumandplasticarepopularlyusedmaterialsbe-
causeoftheirlightweightandrecyclablefeatures.Inaddition,sincepalletsandvehi-
cle-containershavefixeddimensions,maximizetheutilizationoftheirholdingcapac-
ityrequiresthecompatibleinsizingofsmallerparcel,caseandbox.(Murray2016b.)
Justasothernormaloperations,packagingalsodemandcertainleveloftechnologi-
calsupporttoperformfasterandbetter,therebycansatisfytherequiredqualityand
efficiency.Hobkirk(2016)categorizesthefunctioninto4scalesofautomaticimple-
mentations,nameasmanual,specialized,semi-automatedandfullyautomated
packaging.Thefirstexecutionalmannerexpectsworkerstohaveagreatspreadin
ability,canhandleallinvolvedstepsthroughoutthepackagingprocess.Includeskil-
ful-desiredtaskssuchascartonerection,dunnageandsealing,orderchecking,mani-
festingandlabeltagging.Thisinevitableleadtotheinefficientperformance.Further-
more,themethodrequiresthepurchasingandmaintainingofahugebunchofsup-
portiveequipment,fromweightingscale,labelprinter,barcodescannertodunnage
machine,sealingdevice,etc.(ibid.)
Specializedpackagingisa-bit-upgradedversionofthemanualone,itgainsabetter
productivity,becauseworkersaredesignatedtodifferentrolesbasedontheirspecial
skills.Insemi-automatedpackaging,someofthetediousrepetitivefunctionsarear-
rangedtobehandledbymachines,forinstances,labeltaggingandcartonerection.
Ontheotherhand,someofprocessesarepreparedbeforehandorintegratedinto
otherfunctionsforthesmootherflowofparcels.Forexample,appropriateholding
boxesaremadetobereadyfortheaccommodatingofitemsrightinthepicking
stage.Finally,inthemostmodernizedpackagingsystem,allpiecesofworkarecar-
riedoutautomaticallyusingaseriesofequipmentthatwiselyconnectedwithone
another.(ibid.)
2.2.7 LoadingandShipping
Similarwiththepreciserequirementonrunningscheduleatinboundports,out-
bounddocksshouldonlyabletoservetrucksthatarriveontime.Bythatway,ship-
ments-backlog,whichisespeciallytroublesomeforwarehousewithlimitedspace,
20
canbeavoided.Therefore,itisextremelycrucialtodetermineaproperandreliable
carrier-partnersforeachtypeofdeliveryoperation.
Inmostcases,cost,qualityandtimearethedominantinfluences;thesefactorsal-
wayscomeasaset.Highercost-chargingcarriersnormallyprovidefasterservices
withbetterqualityandviceversa.Besides,aseachtransportagencyhasitsownbusi-
nessarea,offersdifferentkindsofserviceandcapacity;multiple-operationsware-
housingfirmmayresultincooperatingwithvariouscarriers.Theotherimportantel-
ementsmustbetakenintoconsiderationarethereliability,stabilityandsustainabil-
ityofthehaulagecompany.
Inadditiontoselecttherightpartnerstocollaborate,forthesuccessofoutbound
function,loadingprocessshouldbewellyarrangedsothatitoperatesasefficientas
possible.Stone(2017)suggestedtousetelescopicconveyortomoveproductsfrom
storageplace,allthewaytotruck-container.Then,anin-chargedwarehouseopera-
torjuststaysinsidethetrailerandfinishtheloadingworkrightthere.Withthissys-
tem,notonlyperformancebesignificantlyimproved,butmajornumberoflabours
andforkliftsneededforthefinalhandlingstageofgoodstolorriesalsobeelimi-
nated.(ibid.)
Forthesameconcern,Woollard(2015)proposetoinstalldockbumperstohelpdriv-
erseasierparkingtruckinreversemanner;andtoplacethelightsalongwaysideas
wellasdockstomakethepathwayclearer.Healsointroducesthenewdockingtech-
nology,whichdimensioncanberetractingandextendingtofitdifferentsizeof
transportvehicles.Thereby,terminatingtheneedofdiversity,consequentlyreducing
thequantityofrequiredports.
Aboveofallothermatters,safetyisthebiggestprobleminloadingactivity.About
25%ofwarehouseaccidenthappenhere;itcanbeforkliftcollision,loadfalling,
trailerslippingandsoon.Thesemisadventurescanbepreventedorreducedbyem-
ployingseveralsolutions.Themostessentialoneisapplyingmotion-basedwarning
systemwithsupportingcameras,flashinglightsoraudiblealertstohelpandguide
workersalongtheprocess.Thesecondadviceisdesigninganergonomicworkinglay-
outthathasminimumnumberofbendingcornerandreachingpoint,sinceaccidents
21
usuallytookplaceatthesespots.Thenextrecommendationishavingpalletsun-
dergostretch-wrappingstagetoincreasetheirstabilityandsecurity.Thisprocess
substantiallyprotectsproductsfromdamage;yet,itissuggestedtocarriedoutauto-
maticallyoratleastinsemi-automaticmanner,becauseofitslabour-intensityre-
quirement.Inaddition,besuretoplacegoodsorpalletfirmlyonforkliftvehicleand
securetruck-containertoafixedpositionduringtheoperation.Finally,sealthedoor
andusingfoldinggatestorestrictaccess,thisisespeciallyimportantinextreme-tem-
perature-days.Meanwhile,utilizehigh-volume-low-speedfansandventilationpanels
togetridofengine’sexhaustfumesandpurifythearea’satmosphere.(Stone2017.)
2.2.8 CycleCounting
Cyclecountingisaninventorymanagementtechnique,usingwhenacertainpropor-
tionofitemsinstorageiscounted,andthatresultwillrepresentfortheaccurate-
levelofentirewarehouse,bothinqualitativeandquantitativemean.Thereare2in-
ferencesmustbeclarifiedandagreedupontheexecution.Theprimaryoneistaking
theitemaccuracyincyclecountanduseitasthewholeinventory’saccuracy.These-
condinferenceisacceptingthat:otheritemsinthewarehousemayhavethesame
errorwiththeonethatisfoundduringcyclecountperformance.
Murray(2017c)introduced3associatedmethodsofcyclecounting,asdescribedin
thefollowingtext:
o Controlgroupcount:usedwhenstartimplementingcyclecountingforthefirst
time,totestwhetherthetechniqueiseffective.Themethodfocusesandre-
peatsthecountingonasmallgroupofgoodsateachshort-periodoftime,by
that,errorsareeasierdetectedandfixed.Theprocessisdoneonceitsaccuracy
andefficiencyisassuredlyconfirmed.
o Random sample count: suitable forwarehousewith large storageof similar
products.At every short-durationof time, suchasdaily basis, itemsare se-
lectedrandomlyforcounting.Thisapproachguaranteesthatlargeproportion
ofgoodsarecountedinacceptableinterval.Thecontingentselectionthatsub-
jectedtoallcontemporaryholdingitemsiscalledconstant-population-count.
22
Whilediminished-population-countexcludesalready-counteditemsfromran-
domsampling.
o ABCcount:basedonParetoprinciple,whichstatethatformostofevents,80%
ofproblemiscausedby20%ofthegroup’smember.Priortothecountingper-
formance,everyiteminwarehouseiscategorizedasA,BorC.Theentirein-
ventorybedividedto20%,30%and50%segments;thesegrouprespectively
accountfor80%,15%,5%ofthetotalsales,namedasA,BandCclass.Atthe
nextstep,thecountingfrequencyforeachcategoryisdetermined.Naturally,
AitemsshouldbecheckedandcountedmoreoftenthantheBandCones.Yet,
thiscanleadtoinaccuracy-storage-controlforCitems,sincetheymaynotbe
checkedinenough-regular.Theotherissuemayariseatwarehousewithlarge
numberofSKUs,wheregoodsbeingassignedforthecountinmanytimesand
therearenotenoughhuman-resourcesavailabletocompletethework.(ibid.)
AccordingtoFain(2014),cyclecountingbringmanybenefitstowarehousemanage-
ment.Whilethetraditionalinventorycountingoftenrequiretheentirewarehouse
operationtostopduringitsprocessing,asaresult,causingmajordisruptionstothe
system;thecyclecountingtechniqueexecutedinpartialbasisandallowotherareas
tocontinuewiththeiractivities.Inaddition,theongoing-cycle-counthelpforcing
workerstocontinuouslyassesstheinventory.Thereby,increasingthechancetode-
tecterrorsbeforetheybringtoomuchtroubles.Thecheckinginsmallersegmentata
timenotonlyreducingworkstressforoperators,butalsosupportthemtobeableto
focusoneachinventorysubset;andconsequently,createbetterreportsforbuyer-
group.(ibid.)
Withsimilaropinion,Gray(n.d.)believesthatcyclecountingtechniquecangenerate
amoreaccurateandupdatedinventorydata.Thishelpsreducestock-outsituations,
evenwhenlowerlevelofsafetystockbeingused.Furthermore,asthecurrentloca-
tionsofholdingitemsbecloselymanaged,ittooksmalleramountoftimeforopera-
tortofindandpicktherequesteditems;bythat,reducingtheshippingleadtimeand
cost.(ibid.)
23
2.2.9 Replenishment
Replenishmentisallabouttheactoftimingandbalancing.Whilecarryinganexces-
siveamountofstockwouldnegativelyaffecttheprofitabilityandfinance-abilityof
company;ashortageinreservinggoodscanleadtosalesdropandcustomers-dissat-
isfying.These2inversingissuesmakereplenishmentbeingoneofthemostcrucial
activityinwarehousing.
Theresponsiblemanagerforrestocking-operationmustdeeplycomprehendand
closelycapturethelifecycleofeachindividualproductwithinthewarehouse.And
thereby,determinetheoptimumamountofgoodstopurchaseforthere-fulfilment
intherighttime.Sothat,neworderonlyarrivesafteroldstockhavebeenusedup,
consideredallpotentialhindrancesalongthesupplychain.Typically,managerisad-
visedtoutilizehistoricaldataaswellasconductingappropriateclassification
method,suchasABCanalysistoprioritizeitemsanddecidethesuitableorderquanti-
ties.Inaddition,assuppliersoftenprovidedifferentkindsofdiscountbaseonthe
purchasingvolume,replenishmentmanagerneedtobeconscioustobalancebe-
tweentheseoffers,associatedcostsandactualdemandtoobtainthemostbenefit.
AccordingtoCurley(2017),thereare3replenishmenttacticsthatcanbeused,de-
pendingonthenatureofeachspecificwarehousingsystem,concerningitsstaffing
andspacingscaleaswellasoperatingprinciple.Firstly,designedforwarehouse
wherefirst-in-first-outrotationisnecessaryandtheusageofrepositorymustbeop-
timizedduetothelimitedofspace,on-demandreplenishmentoperatedsothat
productonlybeacquiredortransferredtoaspecificlocationataroundthetimeitis
needed.Withtheoppositestrategy,top-offmethodiscreatedtohelpmaximizeutil-
ityduringpotentialdowntimes.Generally,therewillbeareplenishment-teamwork-
ingaroundthewarehousetoensurethatinventorygoodsarealwaysmaintainedat
certainquantitativelevels.Withthesimilarmanner,routinereplenishmentalso
pulledbyorder.Suchthat,theminimumthresholds,whichactasthetriggerforre-
fill-functioniscarefullydeterminedinpriortotheimplementation.Nonetheless,
boththetop-offandroutinetacticsmayonlybeusedinwarehouseoflargespace.
(ibid.)
24
2.2.10 QualityConservationandLossPrevention
Inventory’svaluecanaccountforalargeproportionofcompany’sasset.Therefore,
figuringoutapropersecuringproceduretoprotectstorage-goodsfromtheftaswell
asmaintainitsoriginalqualityishighlyimportant.Inmostcases,theinventorylossis
foundoutaswarehousestaffscarrythephysicalcounting,andrealizedifferences
whencomparingtheresultwithinformationrecordedinmanagingdatabase.Theat-
rophyofquality,ontheotherhand,detectedafterrawmaterialshavebeendeliv-
eredtodesignatedmanufacturingplants,andnotqualifiedenoughtobefurtherpro-
cessed.Or,whencustomersclaimforthereturnbecauseofthepoorqualityofre-
ceivingproducts.Exceptionally,defectedgoodscanberecognizedatearlierstageif
warehouseoperatorsproperlychecktheminpriortotheshipping.
Marfo(n.d.)believesthestock-shrinkagecanberesultedfromsingleorcombination
ofseveralfactors;includesinternalandexternalburglary,stockmisplacing,errorin
productshippingandreceiving,etc.Thesuggestedsolutionisinstallingsurveillance
camerasaroundthewarehouse,andhiringsecurityserviceifthieveryfrequentlyoc-
curredinthearea.Inaddition,entrustonlyacertainnumberofemployeesforthe
tasksrelatedtoshipments’verification.Theseworkersnotonlyresponsibleforthe
receiving,inspectingandmonitoringthemovementofgoods,butalsotakingcareof
involveddocuments,receiptsandinvoices;ensurethatallthefilesareproperlyup-
datedandsavedtocompany’smanagingdatabase.Besides,eachemployeeshould
beprovidedwithauniquelogin-accountfortheelectronicregisterofprocessed
transactionsorworkhistory.Thereafter,itiseasiertoidentifytheoperator,who
causingtrouble,andwhetherthemistakeismadeintentionallyoraccidentally.(ibid.)
Carryingnecessarybackgroundcheckonphysicalandmentalhealthaswellascrimi-
nalrecordofcandidatesinrecruitingphaseisgreatlyrecommended.Thelastbutnot
theleast,limittheaccessofstaffsintoareas,wheregoodsofhighvaluearestored.
Bythisway,thestealingattemptofemployeesmaybeterminatedrightinthefirst
place.
Intermofqualitycontrol,aspecializedexpertshouldbehiredtoestablishproper
processesusedintransferringmaterialswithinthewarehouse.Afterward,communi-
25
catethoseprocedurestoworkersandtrainthemtohandlegoodswithcare.Further-
more,aseachinventoryitemoftendemandcertaindifferentstoring-conditions,be
assurethatproductsareplacedintherightroom,wheretheirrequirementsfully
provided.
2.2.11 HandlingReturns
Fromclient’spointofview,acompanywithgoodafter-sale-supportmustabletoof-
feritscustomersthesimpleandrapidreturningserviceofhighequality.Toreach
thatlevel,theforemostimportanttaskforthefirmstocareisdevelopandclearly
publishtheirreturningpolicies,basedonthenatureoftheirbusinessandcharacter-
isticsoftradingproducts.Incaseofcommercialdealsbetweenbusinesses,allissues
relatedtotransactions,suchaswhenandhowshipmentsberejectedforrefundor
alternativeexchange,mustbediscussed,agreeduponandplainlystatedincontracts.
Oncethepolicyisestablished,amanagershouldbeassignedtomonitorthereturn-
ing-related-activities,whichincludegrantingpermission;routingtheflowofinvolved
shipment;determiningwhatprocessshoulditundertakeafterward;calculatingthe
incurredcosts;andfinallyinformtoallconcerneddepartmentsaboutthereturn.
Fortheconvenienceofclients,ordersaresuggestedtodeliveredwithdetailedin-
structionofhowtheycanbereturned,iffailtomeetcustomers’expectation.Itis
popularthatthepostaladdresswherereturned-parcelsshouldheadto,alongwith
othernecessarylabelsanddocuments,alsobeattached.Obviously,customersare
requiredtosubmittheirreturning-requestviaaweb-basedform,emailorphone-
call;andonlysendthepackagesafterreceivingapprovals.Sincetheapplicationsare
collectedandhandledinpaperlessmanner,theprocessingtimeisconsiderable
shortened.Thisnotonlyhelpgratifycustomers,butalsomaintainasmuchaspossi-
blethevalueofreturned-goods,astheysoonerbefixedorsentbacktooriginal
sources.
Themostcrucialconcerninthiswarehousingstageismeticulouslyevaluatingreturn-
ing-claimswithanobjectiveattitude,sothatcustomersfeelcontentevenwhentheir
requestisrejected.Althoughthedecisionmustbemadefollowthefirm’spublished
policy,someextentofflexibilityisalsorecommended.Ontheotherhand,allinfor-
26
mationregardingtothereturnsshouldbeintegratedandstoredincompany’sinter-
nalsystem.Bythatway,employeesfromrelateddepartmentswillbenotifiedto
trackthearisingissuesdownataheadoftimeandcorrectthemrightaway.Forex-
ample,materialpurchaser,productionengineerandinventorycontrollerareobliged
tofindifthereisanyhiddenproblemintheirwork,whenproductsareclaimedof
poorquality.Or,accountantsmustmodifyandupdatetheirfinancialreportswhen
productsbereturnedfortherefund.
2.3 WarehousePerformanceMeasurement
Toefficientlymanagingtheoperationofanybusiness-activity,onemustfirststart
withtheperformancemeasurement.Withacloselymonitoringbasedonthelistof
establishedkey-performance-indicators(KPIs),managercanknowwhetherataskis
properlyexecuted,orbealertedassoonasproblemariseinanywork-chain.Particu-
larlyinthewarehousingfield,Frazelle(2002,55)suggeststhatanorganization
shouldcompareitsownwarehouseperformancemeasurementswiththethird-party
providers.Then,ifapplicable,executenecessaryimprovementorevenreconsider
theoptionofoutsource.(ibid.)
Normally,besidefromthetotal-operational-assessmentofthewholewarehouse,its
belongingdominantfunctionsalsobeevaluatedindetailtogainbetterobservation
andcontrol.Frazelle(2002)classifiedthemeasurementsinto5key-groups:
o Financial:Theincurredcostforeachactivityisestimated,thecost-listwillthen
beregardedasabasis for laterbudgeting,servicepricingorcompareware-
housingproposalsfromthird-partycompanies.
o Productivity: The most tradition and desired performance measurement is
productivity,whichisdefinedasratiooftheoutputtorequiredinputtoobtain
thatoutcome.Forexample, labour-productivity isequaltotheunits,orders,
linesorweightsofshipped-out-commercialdividedbynumberofhoursthat
operatorsspentforthetasks.
27
o Utilization:Toavoidmisleading,productivity-assessmentisrecommendedto
carryinconjunctionwithutilization-measurement;andinvolveseveralbelong-
ing-key-assets,suchaslabour,space,materialhandlingsystemandwarehouse
managementsystem.Itisnotusualbutsometimes,atoohighofutilization-
indicatorcanbeabadsign.Forinstance,ahighvalueofstoragedensity,which
iscalculatedastheamountofholding-inventorydividedbythesquarefootage
ofwarehousespace,maysignifythestatusofovercrowded.
o Quality:Put-away,inventory,pickingandshippingare4majorfunctionsthat
theiroutcome’squalityisextremelyimportantforanywarehousingoperation.
Theperformanceaccuracyismeasuredbythepercentageofitemororderbe-
ingprocessedwithouterror.
o Cycle-time:Dock-to-stock-timeandwarehouse-order-cycle-timeare2popular
unitsusedinevaluatingperformance-speedofawarehouse.Thefirstindicator
refers to thedurationbetween the arriving of a product atwarehouse and
whenitcompletelyavailableforpicking.Thesecondtermismeantforelapsed
timefromthepointwhenorderisplacedatawarehouseuntilitisreadyfor
shipping.(ibid.,55-57.)
Thesystematizedcatalogueofindicatorsforwarehouseperformancemeasurement
ismeticulouslydescribedinthetablebelow:
28
Table1.KPIsusedinwarehousingassessment(adaptedfromFrazelle2002,57)
Financial Productivity Utilization Quality CycleTime
Receiving
Receiving
costperre-
ceivingline
Receiptsper
man-hour
%Dockdoor
utilization
%Receipts
processed
accurately
Processingtime
perreceipt
Put-away
Put-away
costperput-
awayline
Put-awayper
man-hour
%Utilization
ofput-away
labourand
equipment
%Perfect
put-away
Put-awaycycle
time
Storage
Storage
spacecost
peritem
Inventory
persquare
foot
%Locations
andcubeoc-
cupied
%Locations
withoutin-
ventorydis-
crepancies
Inventorydays
onhand
Order
picking
Pickingcost
perorder
line
Orderlines
pickedper
man-hour
%Utilization
ofpickingla-
bourand
equipment
%Perfect
pickinglines
Orderpicking
cycletime
Shipping
Shippingcost
percustomer
order
Orderspre-
paredfor
shipmentper
man-hour
%Utilization
ofshipping
docks
%Perfect
shipments
Warehouseor-
dercycletime
TOTAL
Totalcost
perorder,
lineanditem
Totallines
shippedper
totalman-
hour
%Utilization
oftotal
throughput
andstorage
capacity
%Perfect
warehouse
orders
Totalware-
housecycle
time(Dock-to-
stocktime+
Warehouseor-
dercycletime)
2.4 DesigningWarehouseLayout
Itisnaturalthatthedeepertheroot,thestrongerthetreecangrow.Andjustashow
thetreedependingonitsroot,warehouseoperationcannotbesuccesswithoutan
effective-designedlayout.AccentuatedbyMurray(2017d),toefficientlysupportthe
overallwork-flow,thesystem’sconstituentfunctionsshouldadaptivelybearranged,
29
contingentonspecificobjectiveofeachwarehouse.Itcanbetominimizeinvolved
resourceandwaste,tomaximizespace-utilizationandperformance-productivity,or
toprovidethehighestcustomerserviceandoperationalflexibility.(ibid.)
Themaintaskindesigningphaseiscollectandanalyseallrelatedinformation:busi-
nesspurposes;architecturaldrawingsofwarehousespace;includedactivitieswith
theirconnection,priority,requirementsandconcerns,aswellasneededvehicle,
equipment,andsoon.Thegoalofthisanalysingtaskistodetermineanappropriate
allocationandspaceformainoffice,restrooms,constituentfunctions,intersect
aisles;andestablishoptimalpathwaysfortheflowofworks.
Frazelle(2002)introduced4popularpatternsthatsuitablyusedinmostofcontem-
porarywarehousing,whichareU-shape,straight-thru,modular-spineandmulti-
story.IntheU-shape,receivingandshippingareaareadjacentlocatedinthefront
sideofwarehousebuilding.Productsarriveinatoneedge,storedattheback,and
shippedoutattheotheredge.Thisarrangingpatternnotonlysupportgreatlycross-
dockingfunction,butalsohelpmaximizeresourcesutilization,asthe3processescan
sharetheusage.Moreover,becausetheentranceandexitgatesareinthesameside,
security-executionresultsinmorefocusandefficient.Next,thestraight-thrulayout
shouldonlybeemployedinoperationthatdedicatedforcross-dockingactivity,
wherepeakreceivingandshippingoccuralmost-simultaneously.Incaseoflarge-
scalewarehousethateverysinglebelongingactivityisbigenoughtooccupyanown
building,modular-spineconfigurationisthemostsuitableoption.Finally,themulti-
storymodelisbeneficial-designedforwarehouse,whichlandisverylimited.Yet,itis
unavoidabletoencountersomedifficultiesandbottlenecksduringtheoperation,
whenmaterialsbetransferredbetweendifferentfloors.(ibid.,186-190.)(Thevisual
appearanceoftheselayoutsisdemonstratedinappendices1-4.)
Althoughthedesigningoflayoutneedtobecarriedbaseupononcurrentbusiness
objectivesaswellasothercontemporarywarehousing-related-information,itis
highlyrecommendedtoinvolvetheplansoffuturegrowthandexpansioninthispro-
cess.Forinstance,ifthewarehouseisexpectedtoabletoaccommodatemore
goods,thepurchasingofhigher-capacity-facilitiesrightinthefirstplacewillhelp
avoidunnecessaryreplacinginthefuture;consequently,resultineconomicalsav-
ings.
30
2.5 SupportiveTechnologiesandAutomaticScale
Innowadays’extremecompetitiveandfast-pacebusiness,organizationsmustem-
ploythehelpofautomationtechnologyinmanyoperationstooutstandtheirposi-
tioninthefield.Warehousingisnotanexception,butincontrary,hasthemostpo-
tentialofgainingsavingsfromefficientautomatizing.Ingeneral,warehouseagencies
canfreelychoosethenecessaryactivitiestoautomatizeinappropriatescales,de-
pendingontheirbusinesses’focusingareas.Theavailabletechnologiessupporta
widerangeoffunctions,includematerialhandling,storage,retrieving,conveying,
sortation,order-fulfilment,manifestingorpackaging.
Inthepreviouschapters,theauthorhasdiscussedabouthowautomatedsortation,
packagingandmaterialhandlingsystems,RFID,paperlessorder-fulfilment,andtele-
scopicconveyorcanhelpreducetheamountofrequiredworkforce;productdamag-
ing;employeeinjury;aswellasincreasetheperformance’sproductivityandeffi-
ciency.Tofullycompleteonthistopic,inthefollowingtext,theadvantagesanddis-
advantagesofusingautomatedstorageandretrievalsystem(AS&RS)andautomated
guidedvehicles(AGVs)willbepresented.Typically,thesetwosystemsarecausing
themostheadacheformanager,whenmakingdecisiononthetechnology-invest-
ment.
Firstly,withtheAS&RS,therearevarioustypesofsystemthatspecificallydesigned
fordifferentstoring-unit,load-weight,operationalspeed,storage-condition,oreven
theamountofavailablewarehousespace.Forexamples,theUnitLoadAS&RSissuit-
ableforhandlingproductinunitsofpalletortote;VerticalLifeModuleAS&RSoffers
thegreatutilizationofverticalspaceandsupportswellforpickingoperationofhigh
speed;CarouselAS&RSisusedforgoodsthatcanbestoredonshelvesorinbins(Au-
tomatedStorageandRetrievalSystemsn.d.).
TheAS&RSoftenbeconstructedtomaximizetheutilizationofstoragespace,conse-
quentlysavingupusageenergyforlightandtemperature-control.Theoperation
manneralsobeoptimized,sothatitiseasier,fasterandmorediscretetoaccessfor
productstorageandretrieval.Inmostcases,thesystemcanbedistantlymonitored
byusingaconnectedcomputersoftware;andthebuilt-inequipmentwillbeguided
torapidlyhandlealltheheavyandrepetitivetasks.Thisnotonlyhelpincrease
31
productivityandefficiency,butalsopreventemployeesfrominjury.Furthermore,
AS&RScanallowreal-timetrackingandcontrolofstoringgoods,whilelimitingthe
unnecessaryaccessofwarehouseworkers.
AlthoughtheAS&RSpromisingmanybenefits,warehousemanagerfeelhesitates
whendecidingonthepurchasingbecauseofitshighinitial-investmentcosts.Inaddi-
tion,oncethesystemisinstalled,itisveryhardtomakeanychangesaroundthe
area.Theimproperusingmanneralsoeasilyleadtolargepayingcostsforrepairing.
Andthemostinconvenienceisthatduringthemaintenancetime,operationmustbe
stoppedifitisnotpossibletoswitchtomanualmode.
Forthesimilarpurposeofreplacinghumanmanualworkbyafasterandsaferauto-
maticengine,AGVisbuiltwithnecessarynumberofsupportivecamerasandsensors,
accompaniedbyagreatly-designedexecutional-programme,allowittooperatein-
cessantly,evenintheextremeconditions.Althoughitmaynotabletohandlethe
tasksasflexibleashumandoes,ithelpseliminatesignificantlyaccidentaleventsand
inaccurateperformance.
Insummary,automatizingwarehousingfunctionsbringsinbothgoodandbadef-
fects.Tocomeupwiththerightdecisions,anddetermineanappropriatelevelofau-
tomationforeachactivity,onesmustfirstcomprehendthoroughlythenatureof
theirbusiness.Next,identify,prioritizeandbalancebetweenthegainsandlosses
thatpotentiallyresultin,ifanautomaticsystembeemployed.Onlythen,theright
answermaybedetected.Theonlyassuredrecommendationisthatautomatictech-
nologyisobviouslybenefitforlong-term-orientationwarehouseoflarge-operation-
scale,wheretheworkstendtobefixedinrepetitivepatterns.
3 TheoreticalBasesOfSimulation
3.1 Simulation
Simulationistheactsofexecutingandobservingacomputer-basedprocessmodel,
whichisareplicaofreal-worldsystemorprocess.Thetechnologymaybeusedfor
carryingvirtualexperimentsorgenerating“what-if”analysesinamuchmorecon-
venientandcheapermanner.Bythat,onescanunderstandbetteraboutthesystem
32
anditsoperations;subsequently,promptanddetectnecessarychangesforperfor-
mance-improvements,suchasincreasingthroughput,reducingcosts,etc.(Lyman
n.d.)
Withthesameopinion,Lahdevaara(2016,5)believesthatsimulationcanbeusedto
experimentanewdesignorpolicies;toverifyanalyticsolutionsinpriortoimplemen-
tation;orfortheinsightstudyofcomplexsystems.Nevertheless,heemphasisesthat
appropriateandapplicabledataisextremelyessentialinbuildingausefulmodel.
(ibid.)
3.2 PoissonDistributionPois(𝜆)
Inthecontextthatcertaineventsaregoingtooccuratrandomtimesandindepend-
entofeachother.Whereas,theaveragenumberofspontaneouseventsinaninter-
valoftime,whichismeasuredasintensity𝜆,is(approximatelytobe)constant.Then,
thenumberofspontaneouseventsXinanyspecifictimeintervalisPoissondistrib-
uted.Xiscalleddiscreterandomvariableanditsvaluebelongingtotheset{0,1,2,3,
4,5,…}.(Brink2010,35.)
SomeexamplesofPoissondistributedevents:thenumberofcustomersarriveata
storeineach2-hours-period;thenumberofordersplacedatanonlineshopeach
day;thenumberofdefectedshipmentsdetecteddailyatawarehouseinboundarea;
andsoon.Foreachk∈{0,1,2,3,4,5,…},accordingtoBrink(2010,35),thepoint
probabilitiesinaPois(𝜆)distributionarecalculatedas:
𝑃 𝑋 = 𝑘 =𝜆)
𝑘!𝑒,-
noticethat0!=1,byconvention.
Forexample,arepairshopcanfixonaverage2devicesperhour(eachtypeoffault,
whichisariserandomlyandindependently,demandsacertainamountofeffortin
repairing).Then,thenumberofcorrecteddevicesinevery1-hour-periodfollowthe
Pois(2)distribution,andthepointprobabilitiescaneasilybedeterminedaslistedin
thetablebelow:
33
Table2.Probabilitythatkdevice(s)canbefixedin1hour
k 0 1 2 3 4 5 6 ≥7
P(X=k) 13.53% 27.07% 27.07% 18.04% 9.02% 3.61% 1.2% 0.45%
3.3 ExponentialDistributionExp(𝜆)
Stayinginthesamescenario,whereeventsoccurspontaneouslywithintensity𝜆,and
thenumberofeventsinacertaintime-periodisPois(𝜆)distributed.Itfollowsthat,
thewaitingtimeTbetween2successiveeventsisexponentiallydistributed.AndTis
calledcontinuousrandomvariable,takingvaluefromtheinterval[0,∞).Mathemati-
cally,theexpectedvalueofwaitingtimeTis𝐸 𝑇 = 5-,andthedensityfunctionof
Exponentialdistributionisformedas𝑓 𝑥 = 𝜆𝑒,-9.(Brink2010,45-46.)
Continuewiththerepair-shop-example,theservicetime(thetimeneededtofixa
device)isexponentiallydistributed.Althoughtheexpectedservicetimecanbecom-
putedas𝐸 𝑇 = 5:= 0.5hours,thetimerequiredtorepairadeviceisdifferentfrom
casetocase.Usingthedensityfunction,onecancalculatetheprobabilityofanyser-
vice-durationwithintheinterval[0,∞).Thetablebelowcontainssomeexampleof
service-time-valueswithassociatedprobabilities:
Table3.Probabilitiesthatxhour(s)isrequiredtorepairadevice
X 0.2 0.4 0.5 0.8 1.4 4 ≥6
f(x) 45.24% 40.94% 38.94% 33.52% 24.83 6.77% 7.47%
3.4 QueuingTheory
Queuingtheoryisabranchofoperations-research,regardingtomathematicalstudy
ofwaitinglines.Itsresultsareusedinsupportplanningschedule;determiningappro-
priateinputresourcesforeachservice-activity;improvingcustomersatisfaction;and
soon.Inthemostbasicformation,queuingmanagementregulates3majormatters:
howcustomersorproductsarrive,howtheyareservicedandconditionsofthem
34
leavingthesystem.(Shermann.d.)
Thearrivingofcustomersatastore,ofunfinished-goodsatamanufacturingline,of
defectiveproductsatarepairshopandsoonisvaryingfromtimetotime,butcanbe
approximatelyestimatedbyanacceptableconstantrate(CR).Asdiscussedearlier,in
CRmodel,thenumberofarrivalspertime-unitandthetimebetweensuccessivearri-
valsrespectivelyfollowthePoissonandExponentialdistributions.
Toefficientlydirectemployeesinservingcustomersorhandlingproducts,asuitable
queue-ruleshouldbeselectedandapprisedinadvance.Lahdevaara(2016,65)di-
videdtheavailableoptionsinto2mainclasses,fornot-interruptedandinterrupted
services.Thefirstgroupcontainsprinciplescalled:firstcomefirstserved(FCFS),last
comefirstserved,shortestprocessingtimefirst,serviceinrandomorder,triage-pri-
orityandnon-pre-emptivepriorities.Whereas,thesecondoneincludesdisciplines
namedas:shortestremainingservicetime,roundRobinandpre-emptivepriorities.
(ibid.)
4 SimulationInWarehousing
4.1 MotivationofUsingSimulationinWarehousing
Theworkofawarehousemanagerisallaboutmakingtherightdecisions,whetherit
istohireandallocatestaffsforeachoperation;todrawplanonoperatingschedules
andemployees’shifts;todetermineappropriatepurchasesofequipmentandforklift
vehicles;toselectpropertypesofdock,rack,AS&RS,conveyorbelt,sortationsystem
andsoonforinstallation;toinitiateanewexecutionalprincipleandpolicy;todesign
anewoperationallayoutorbetterpathsfortheflowingofworkandmaterials;etc.
Inanyofthementionedcasesabove,simulationcanplayagreatsupportiverole
alongdecision-makingprocess.
Byhavingthewarehousesystemvirtuallyreplicatedinacomputerprogramme,man-
agercaneasilymakechangetoinputelements,runthemodelindesiredtimeframes
andgetthecorrespondingresults(indifferentlevelsofconfidence)immediately.Af-
terward,he(orshe)cancomparetheproposedalternativesintermsofassociated
costs,gainsandlost,beforechoosingthemostoptimaloptionforimplementation.
35
Thisprocedureassistsmanagergreatlyinanticipatingposteriordifficulties,aswellas
evadingrisksandlossresultedfromthewrongdecisions.
Becausesimulationmodelisconstructedandexecutedpurelybaseonmathematical
concepts,thecalculatedoutcomesiscompletelyassured(ifinputdataispertinent
andreliable).Furthermore,ascomputersoftwarecanrunanddisplayinstantlythe
resultsofemulatedcases,managershouldabletomakedecisionsfaster.Ultimately,
helpwarehousingfirmtocatchupwiththecurrentbusinesstrends.
4.2 ComputerSoftwareforSimulation
Sincethepowerofsimulationisgettingmorerecognition,manytechnologycompa-
niesbecomeengagingincreatingamoreintelligentandsophisticatedsimulationsys-
tem.Thisleadtotheconfusingmarketofsimulationsoftwarewithhundredsofin-
ventedprogrammes,thatgreatlyvaryinqualityaswellasprice.Besides,aseach
companyoftenhasitsowntargetedgroupsofcustomers,whoareworkingorstudy-
inginaspecificprofessionalarea;thecompany’ssoftwaretendstobegenerated
withcertainuniquefeatures,thatmainlysupportthesimulatingandoptimizingfor
operationsinthatfield.Hence,oneshouldbecircumspectwhenselectingthesimu-
lationprogrammetoworkwith.
Fortunately,manycompaniesofferfreetrialversionoftheirsoftwareforcustomers
totestandexplore,beforedecidingonthefinalpurchasing.Thedurationoffree-pe-
riodisvaryingfrom1to4months,whichislongenoughforuserstounderstand(in
anadequateamount)aprogramme.Itisalsorecommendedtoseekinformation
fromexperts;fromarticleswritingaboutsimulationandtheannualbest-ranking
software;fromotherusers’reviews;andsoon,beforespendingtimeonanytrial
version.
Inthenextchapter,asoftwarecalledEnterpriseDynamics(version9)willbeusedto
constructtheexamplemodel.Sinceitsfirstreleasein1997,theprogrammehasbeen
improvedandexpandedapplicationstovariousareas.Warehousingisoneofthe
mainsupportedfieldandthereisevenawarehouse-specific-libraryintegratedinthe
system.Fromauthor’spointofview,thisisthemostuser-friendlyprogramme,such
36
thatitshouldonlytakeafewweeksforanynewbietogetalongwiththesoftwareas
wellasitsevent-and-object-oriented-platform.
4.3 AnIllustrativeCase
4.3.1 Case-ScenarioandProgramme-Setup
Inthisexamplecase,amanager(simplynamedasS)isassignedtoconstructaware-
house,whichmainactivitiesincludereceiving,cross-docking,registering,sortation,
put-away,storage,picking,packagingandshipping.Splanstoarrangetheoperation
intheU-shapelayout;andhavecollectedthenecessaryinformation,regardingto
amountofworkrequiredineachtask,qualificationofemployees,productivityof
machines,capabilityofsupportivetechnologiesandequipment,aswellasotherin-
volvedissuesandlimitations.Now,Swantstodeterminethemostoptimalnumber
ofworkers,machines,equipment,forkliftvehicles,etc.toemployandpurchase,so
thatoperating-resourcesneverinthesituationofeitherredundancyorshortage;or
atleast,itonlyoccurinanacceptableextend.
Theinitialsketchofthelayoutispresentedinthefigurebelow;thereare3pathways
fortheflowingofmaterials:regularshipmentsmoveinasguidedbyblackarrows,
cross-dockingshipmentsfollowgreenarrowsandfinally,outboundordersarepro-
cessedinthedirectionofredarrows.
Figure2.Initialsketchofwarehouselayout
37
Thesimulatedmodelcontains27objects.Outboundorders,regularshipmentsand
cross-dockingshipmentsaresymbolizedbythe3smallsquares.Pine-greenrectan-
glesactasaplacewhereordersandshipmentsenter,stay(atstoragearea)andexit
thewarehouse.Eachorangerectanglerepresentsforawarehousingfunction.Ex-
cept,theworkinreceivingandshippingdocksisdividedbyteam.Thebluerectan-
glessignifyforqueuesassociatedwithactivities.(Appendix5exposeshowtheseob-
jectsreallybeconnectedintheprogramme.)
Basedonhistoricaldata,onaverage,2batchesofregularshipmentand1batchof
cross-dockingshipmentareestimatedtoarriveatinboundareainevery1-hour-pe-
riod.Thismakesinter-arrivaltime(waitingtimeforashipmenttoarrive)ofthemto
respectivelybe0.5hoursand1hour,followingtheExponentialdistribution.Inthe
sameduration,anaverageof10ordersaredemandedbycustomers,meaningthat
orders’inter-arrivaltimeis0.1hoursandexponentiallydistributed.
Aftercollectingtherelatedinformationfromhuman-resourcesdepartmentandsup-
ply-partners,Shascomeupwiththefirstproposition.Suchthat,withanappropriate
executionalprincipleandpolicy,accompaniedbycertainnumbersandtypesofwork-
ers,machines,equipment,vehiclesandtechnologies,theperformance-rateofeach
activityobtainsaspecificlevelasdeclaredinthefollowingtable:
Table4.Performanceratecorrespondingtoinitialproposition
Operation(Rule:FCFS) CycleTime(Hour(s))
Receivingdock1 1
Receivingdock2 1
RegisteringandSortation 2
Put-away 0,5
Picking 0,2
Sortation 0,1
Packaging 0,3
Cross-docking 1
38
Therateisevaluatedusingindicatorcalledcycletime,andinthiscase,itismeasured
asthelengthoftimerequiredtohandleabatchofinboundshipmentoranout-
boundorder.Theaveragenumberofbatches(ororders)processedareapproxi-
matelyconstant(Poissondistributed),impellingtheratetofollowExponentialdistri-
bution.Exceptionally,forthereductionintransportationcosts,delivery-truckonly
leavingthewarehousewhenfullyloadedwithabout4batchesofcross-dockingship-
ment(atshippingdock1)or40orders(atshippingdock2).However,itnotmeans
that4batchesofshipmenthavethesameload-dimensionswith40outboundorders,
buttrucksofdifferentsizesarebeingusedforthe2docks.
Anappropriatequeue-capacityispresumablyassignedforeachobject(queueimita-
tion),toemulatetheallocationofreservedspacefordifferentwarehousefunctions.
Thisassigningissubjectiveandshouldbechangedeasilyinaccordancetotheup-
comingsimulationresult.(Thedetailofcapacity-settingissummarizedinappendix6.
Andtheprogramme-setupofsomerepresentativeobjectsaredisplayedinappen-
dices7-10.Notethattheunitoftimeisinsecond.)
4.3.2 SimulationResultsandSuggestedActions
Afterhavingthemodelruninatimeframeof8hours–1dayworkinghours(inreal
time,itonlytookafewminutes)forseveraltimes,themostfrequently-occurresult
isrecordedasshowninthefigureandtablebelow:
39
Figure3.Simulationrecordedresult:utilizationlevelofindividualfunction
Table5.Simulationrecordedresult:processingofproducts(ororders)
SummaryReport
ObjectCurrent Throughput
UnitProduct Input Output
RShipment 0 19 19
Batch
ReceivingDock1 1 9 8
ReceivingDock2 1 10 9
Register&Sort 1 4 3
Put-away 0 3 3
CDShipment 0 10 10
CrossDocking 0 10 10
ShippingDock1 4 8 4
OrderNotice 0 76 76
Order
Picking 1 39 38
Sort 1 37 36
Packaging 1 19 18
ShippingDock2 18 18 0
40
Toexaminethestatusatwaitinglines,aseriesof20-days-simulationislaunchedand
themaximumnumberofproductsateachqueueineachruniscaptured.Subse-
quently,thestatisticsusedinlimit-control(average–centralline,lowerbound,up-
perbound)arecomputedwith95%ofconfidence.Thecorrespondingresultistabu-
latedasbelow:
Table6.Simulationreportofqueues’status
Observation-period: 576000 Warmup-period: 0
Numberofobservations: 20 Simulationmethod: Separateruns Object Average L-bound(95%) U-bound(95%) Unit
Queue1 4 2 5
BatchQueue2 8 7 10
Queue3 1 1 1
Queue4 40 36 45
OrderQueue5 3 3 4
Queue6 15 12 17
Queue7 1 1 1
QueueA 3 2 4Batch
QueueB 2 2 3
Takingasanexampletoexplainforthemeaningofthesestatistics,regardingtothe
Queue1(queueforReceivingfunction),onecanbe95%confidentthatthemaxi-
mumnumberofproductsinthisqueuewithin1-day-periodisgreaterthanorequal
to2(batches)andlessthanorequalto5,andonaverageitshouldequalto4.Byfit-
tingthedataintoNormaldistributionandusingtherelatedformulas,thesestatistics
caneasilybeevaluated.Conveniently,thereisabuilt-instatisticaltoolinthesoft-
warethatautomaticallyhandlethiscalculationwhenusersplacethedemand.Thisis
thereasonwhytheauthoromitsNormaldistributionconceptinthechapteroftheo-
reticalbases.
41
Thesimulationresultsplainlysignifythatthedesignedwarehousingsystemcontains
variousproblems.Foraclearandsystematicreporting,issuesassociatedwitheach
activitywillbeidentifiedanddiscussedcase-by-caseinthefollowingtable:
Table7.Warehouse’sinitialproposition:ImperfectionsandSolutions
Activity DiscussionandRecommendedActions
Receiving
Utilizationratesatreceivingareaarequitegood(88.8%and95.5%).In
therecordedday,17outof19batches(ofproduct)weresuccessfullyfor-
wardedtothenextpace.Nonetheless,with2batchesleftbehinduntil
thenextday,andanaverageofmaximumcontentsmustlingerinthe
queueisconfidentlyestimatedtobe4,alittleimprovementisneeded.
Register
&
Sort
Thisistheactivitythatcausedangerousblockageatinboundarea.There
wereonly3outof17batchesbeprocessedtothenextstage.According
tothisoperationalspeed,theremaininglargeproportionofproducts
mustbestackingupfordays.Despiteso,thefunction’sutilizationalmost
reached77%.Meaningthat,eithertheareaisdeservedtobeassigned
moreresources(operator,machine,vehicle,equipment),orabetterreg-
isteringandsortationsystemshouldbeemployed,forthefunctiontobe
abletofullyaccomplishitsduty.
Put-away
Becausethepreviousprocesshadhinderedsubstantiallytheflowofma-
terials,therewasnotmuchofthemavailabletobeput-awayinthis
phase(extremelylowutilizationrateof8.7%).Hence,itisessentialtore-
allocateorintegrateresourcesforthe2adjacentareas(Resister&Sort
andPut-away),sothatamorebalanceofutilizationratesandagreater
amountofthroughputcanbeattained.
Cross-docking
Theoperationofcross-dockinghasbeendesignedwell.Intherecorded
result,itsutilizationratereached95.3%andalldemandedworkloadwas
completelyhandledbytheendoftheday.Confidently,managercannow
decidethefinalamountofreservedspacefortheactivity’sconnected-
queue,whichaverageofmaximumcontentsisexpectedtobe3batches
(95%assurance).
42
Picking
Pickingisanotherfunctionthatneedmoresupport.Althoughitsre-
sourceshavebeenutilizedupto98.3%,onlyhalfuptheorders(38outof
76)werefullypickedfordelivery.Itisnotsurprisethatthepossiblemaxi-
mumnumberofordersmustendureinthequeueisnotlowerthan36.
Theseareclearimpellentsignsformanagertoconsiderengagingwith
thepaperless-pickingtechnologies(ifnotyet),besidefromincreasingthe
numberofworkersinthisarea.
Sort
(Outbound)
Onlyused38.8%oftheassignedresources,butrapidlysortedoutthein-
putordersforthenextstageofpackaging.Therefore,acertainpropor-
tionofoperatorsshouldbetranslocatedtoworkinotherareas,suchas
pickingorpackaging.
Packaging
Fromthefactthatpackagingareacouldonlyprocessouthalfofthein-
puts(18outof36),eventhough96.5%ofitscapacityhasemployedin
theoperation.Itcanenrolinthelistoffunctions,whichnotgettingas
muchsupportasdesired.Amongtheorders-handling-queues,packag-
ing’squeueplacesasthesecond,intermofnumberofmaximumcon-
tentsrecordedattheline(15ordersonaverage).
Shipping
Asmentionedearlier,theworkatshippingareaisarrangedsothatthere
willbeonetruckparkingateachdock,waitingforcross-dockingproducts
toreach4batches(docknumber1),oroutboundorderstoaccumulate
to40packages(docknumber2).Thisprincipleexplainsforthelowutili-
zationratesatthe2docks.Theproblemisthat,bytheendofrecorded
day,therewasonly1-timetruckleavingtheshippingareafromdock
number1.Theother4availablebatchesmustwaituntiltheearliestof
thefollowingday.Regardingtothedocknumber2,only18orderswere
successfullygatheredafter1workingday,22moreordersstillneededfor
thetrucktoleave.Thisexecutionalmannercausesmajordelayindeliver-
ingproductstocustomers.Therefore,itisbettertooutsourcethisactiv-
ityandcooperatingwithathird-partycarrier,thatcancomeandpickthe
productsinmorefrequenttimes.Otherwise,thecurrentusingtrucks
shouldbereplacedbysmallervehicles,which,forexamplebefully
loadedwith2batchesofcross-dockingproducts,or6outboundorders.
However,thismayresultinhighertransportationcosts.
43
Althoughtheinitialpropositionseemstobefineatafirstsight,manydrawbacksbe-
comevisibleafterhavingthesimulatedmodelrunandconsequentresultsgener-
ated.Whilesomefunctionareasbeassignedwithtoomuchofresources,theother
operationshavetosufferwiththeheavyworkload,comparetotheirequippedcapa-
bility.Theinappropriateexecutionalprincipleatshippingdocksalsopreventedabout
two-thirdsofshipmentsfromdepartingfordelivery,intherecordedday.Andover-
all,thewarehouseonlyshippedout4batchesofproductsfromtherequestof76or-
dersplus10batchesofcross-dockingshipments–anextremelylowproductivity.
Bynow,themanagermustrealizethattheestablishedplanisseriouslybad.Moreef-
fortsshouldbeputtinginrefiningtheperformanceprinciples;balancingthere-
sourcesforinvolvedactivities;andprovidinggreatersupportforfunctionswith
heavyworkload.Alongtheprocess,simulationshouldalsobeusedasaverifyingtool
foranychangethatmanagerintendsto,evenaverysmallone.Thisway,themodel
canbeimprovedinamorereliableandsteadymanner.
Intermofspaceallocationforthequeuesaswellasareaforeachactivity,decision
shouldbemadebasedonsimulationresultsofmodel,whichemulatedthefinalver-
sionofwarehousedesign.However,fromauthor’spointofview,theidealnumberof
productslingerateachqueueshouldnotlargerthan3batchesor10orders.
4.4 Conclusion
Sincetheexamplemodelisbuiltbasedonpertinentandverifiedmathematicalcon-
cepts,belongingobjectsalsobeconnectedtointeractwitheachotherexactlyinac-
cordancetotheestablishedperformanceprinciples,thesimulationmodelaswellas
itsgeneratedresultsaretotallyreliable,providedthatthecollecteddata(arrivalpat-
ternandinter-arrivaltimeofinboundandoutboundorders,cycletimeoffunctions)
isupdated,relevantandaccurate.Itisworthtoalertonceagainthatamodelfailing
toguaranteeanyoftheabove-mentionedstandardsduringtheconstructionphaseis
useless.Andemployingawronglybuiltsimulationmodel(withoutawareness)asa
lodestaralongdecision-makingprocessmayleadtoterribleconsequences.Hence,it
iscrucialtoexamineandverifythequalityandreliabilityofamodelbeforetheus-
age.
44
Thecurrentsimulationtechnologyhasgreatlydevelopedsuchthatitispossibleto
replicateexactlyanyreal-worldeventorprocessintoa3-dimensions(3D)computer-
basedmodel.Forinstance,differenttypesofautomaticconveying,sortation,packag-
ingsystemcanbeemulatedas3Dsimulationmodels;andvirtuallybeimplemented
toexamineandidentifythemostsuitableonesforacertainrangeofproducts.
Infact,thepreviouslyusedprogramme(EnterpriseDynamics9)alsooffers3Dsimu-
lationfeatures.Buttoabletobuildthatkindofcomplexmodel,acertainlarger
amountoftimeandeffortmustbespendingongatherthenecessaryinformation.
Andthistime,theaccuracyrequirementoncollecteddatashouldbestrictertoavoid
anyprobabledominoeffects.Modeldesigneralsoexpectedtopossessasolid
enoughmathematicalbase,accompaniedbyaskilfullevelinsoftwaremanipulation.
Nonetheless,ifwarehousemanagerdoesnotwanttobearthelearningofadvanced
mathematicsandsimulationsoftware,thenjustsimplyhireasimulationspecialist,
whocaneasilycreateanydemandedmodel,providespecializedadvicesandassist
him(orher)alongthepainfuldecision-makingprocess.Thetotalcostisnotmore
thanaperiodicsubscriptionfeeofsimulationsoftwareandmonthlysalaryforavalu-
ableexpert.
Althoughthemodelcreatedintheillustrativecaseisquitesimple,thatbasingonly
onacouplepiecesofdataandmathematicalconcepts,withsomeutilitiesofasimu-
lationsoftwareinvolved,itworksbestforwarehousingfirm,whichoperationsare
pureandplainlyconnectedwithoneanother.Inthesituationthatasupportive
modelisinurgentneedandwherethereisnotmuchofaccurateandreliabledata
availableatthetime,thiskindoffocusandsolidmodelismorepreferredthana
largeandcomplexone,withvariouspotentialerrorsassociated.Besides,thelevelof
simulationknowledgeofgeneralwarehousemanagersshouldalsobetakinginto
considerationwhendecidingonthecomplexityscaleofamodel.Astheextentof
benefitsthatasimulationmodelcanbringindependingonhowmuchitcanbeuti-
lizedbytheuser.
45
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Appendices
Appendix1. U-shapelayout(adaptedfromFrazelle2002,187)
Appendix2. Straight-thrulayout(adaptedfromFrazelle2002,188)
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Appendix3. Modular-spinelayout(adaptedfromFrazelle2002,189)
Appendix4. Multistorylayout(adaptedfromFrazelle2002,190)
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Appendix5. Actualconnectionsofobjectsintheprogramme
Appendix6. Capacityofwaitinglines
Queue 1 2 3 4 5 6 7 A B
Capacity 30 60 30 150 50 50 50 15 15
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Appendix7. Data-setupforthearrivingofregularshipment
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Appendix8. Data-setupforreceivingdocks’queue
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Appendix9. Data-setupforcross-dockingfunction
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Appendix10. Truckonlydepartafterhaving40ordersloaded