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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
2
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
3
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
4
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.
5
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
6
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
7
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:
8
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
9
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.
10
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:
11
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
12
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
13
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.)
14
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
15
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-
16
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