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

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

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

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.

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

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

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:

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

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.

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:

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

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

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.)

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

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-

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:

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

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

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,

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

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.

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.)

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.)

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-

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-

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.

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:

Table1.KPIsusedinwarehousingassessment(adaptedfromFrazelle2002,57)

Financial Productivity Utilization Quality CycleTime

Receiving

costperre-

ceivingline

Receiptsper

man-hour

%Dockdoor

utilization

%Receipts

processed

accurately

Processingtime

perreceipt

Put-away

costperput-

awayline

Put-awayper

man-hour

%Utilization

ofput-away

labourand

equipment

%Perfect

put-away

Put-awaycycle

Storage

spacecost

peritem

Inventory

persquare

%Locations

andcubeoc-

cupied

%Locations

withoutin-

ventorydis-

crepancies

Inventorydays

onhand

picking

Pickingcost

perorder

Orderlines

pickedper

man-hour

%Utilization

ofpickingla-

bourand

equipment

%Perfect

pickinglines

Orderpicking

cycletime

Shipping

Shippingcost

percustomer

Orderspre-

paredfor

shipmentper

man-hour

%Utilization

ofshipping

%Perfect

shipments

Warehouseor-

dercycletime

Totalcost

perorder,

lineanditem

Totallines

shippedper

totalman-

%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,

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-

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-

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

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

anditsoperations;subsequently,promptanddetectnecessarychangesforperfor-

mance-improvements,suchasincreasingthroughput,reducingcosts,etc.(Lyman

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:

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

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.

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

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

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

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:

Figure3.Simulationrecordedresult:utilizationlevelofindividualfunction

Table5.Simulationrecordedresult:processingofproducts(ororders)

SummaryReport

ObjectCurrent Throughput

UnitProduct Input Output

RShipment 0 19 19

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

Picking 1 39 38

Sort 1 37 36

Packaging 1 19 18

ShippingDock2 18 18 0

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.

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

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).

Picking

Pickingisanotherfunctionthatneedmoresupport.Althoughitsre-

sourceshavebeenutilizedupto98.3%,onlyhalfuptheorders(38outof

76)werefullypickedfordelivery.Itisnotsurprisethatthepossiblemaxi-

mumnumberofordersmustendureinthequeueisnotlowerthan36.

Theseareclearimpellentsignsformanagertoconsiderengagingwith

thepaperless-pickingtechnologies(ifnotyet),besidefromincreasingthe

numberofworkersinthisarea.

(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.

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-

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.

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Appendices

Appendix1. U-shapelayout(adaptedfromFrazelle2002,187)

Appendix2. Straight-thrulayout(adaptedfromFrazelle2002,188)

Appendix3. Modular-spinelayout(adaptedfromFrazelle2002,189)

Appendix4. Multistorylayout(adaptedfromFrazelle2002,190)

Appendix5. Actualconnectionsofobjectsintheprogramme

Appendix6. Capacityofwaitinglines

Queue 1 2 3 4 5 6 7 A B

Capacity 30 60 30 150 50 50 50 15 15

Appendix7. Data-setupforthearrivingofregularshipment

Appendix8. Data-setupforreceivingdocks’queue

Appendix9. Data-setupforcross-dockingfunction

Appendix10. Truckonlydepartafterhaving40ordersloaded

warehouse in today’s business and benefits of simulation ...2 warehouse in general 2.1 the...

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