[精选]美国的一个仓库管理系统（PPT 63页）20427.pptx

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1、 2002 Georgia TechInternet-basedData Envelopment Analysisfor Warehousing 2002 Georgia TechOutline The problem The current solution The need A new solution How it works Internet deployment and results to date Future directions 2002 Georgia TechPerformance Assessment How well are you performing?Do you

2、 have opportunities to improve?2002 Georgia TechWarehouse OperationsReceiving Function(inbound)Unload Inspect Put AwayStorageFunctionShipping Function(order fulfillment)Load Pack Order PickStorageFunctionStorageFunction 2002 Georgia TechSingle Factor Productivity MetricsProductivity=outputinput 2002

3、 Georgia TechTraditional Performance Metrics Fill rate Inventory turns Lines/hour Orders/hour$/line$/order 2002 Georgia TechWork ok when Requirements are not changing Technology is not changing Competition is not changingIts very hard to interpret a single factor productivity metric when the environ

4、ment is subject to rapid change in products,customer requirements,technology,or competition.2002 Georgia TechBut in a dynamic world Cant compare over time Cant compare across locations Cant compare to other companiesAt least not without a lot of additional explanatory data and information!2002 Georg

5、ia TechBenchmarkingRelative performance levelBest(effective)practices 2002 Georgia TechINPUTSOUTPUTSSystem-oriented Performance MeasureThe NeedResources ServicesActivities 2002 Georgia TechTotal Factor Productivity?Cant solve the pricing problem 2002 Georgia TechINPUTSOUTPUTSONEPERFORMANCE INDEXData

6、 Envelopment AnalysisResources ServicesActivities 2002 Georgia TechSystem-based assessment method Resources:capital,labor,overhead Activities:inbound,order fulfillment Services:lines/qty shipped,fill rate,etc 2002 Georgia TechCompare to other warehousesAll other warehousesAll other warehouses in you

7、r industryAll other warehouses in your companyYour warehouse in the past 2002 Georgia TechProduction Function Theoryfor one input,one outputResource/InputProduction/Output 2002 Georgia TechSystem Efficiency ConceptResource/InputProduction/OutputOBASystem efficiency of warehouse B is the ratioOAOB 20

8、02 Georgia TechDEA Model:Charnes,Cooper,and RhodesConstant Returns to Scale 2002 Georgia TechData Envelopment Analysis Allows us to consider multiple“inputs”Allows us to consider multiple“outputs”Determines the reference point on the production function by constructing a hypothetical“best practices”

9、warehouse using real warehouse data Best possible*not average*from data 2002 Georgia TechDEA Performance ScoreContribution to Profit 2002 Georgia TechInput/Output Specification(the Frazelle/Hackman model)EfficiencyWarehouseLines ShippedStorage FunctionAccumulationTotal StaffingEquipment“Replacement”

10、CostWarehouse area 2002 Georgia TechHtmldocumentsSolverDatabaseAt your siteGT ServerWeb-based ToolOver the internet 2002 Georgia TechOver 150 qualified users 2002 Georgia TechResults to Date 2002 Georgia TechExperience Existing database More than 150 warehouses Not segmented by industry(yet)No“descr

11、iptive”data to use for segmenting Can segment based on inputs and outputs 2002 Georgia Tech 2002 Georgia Tech 2002 Georgia Tech 2002 Georgia Tech 2002 Georgia Tech 2002 Georgia Tech 2002 Georgia Tech 2002 Georgia Tech 2002 Georgia Tech 2002 Georgia Tech 2002 Georgia Tech 2002 Georgia TechOutput Segm

12、entation broken case:49 full case:32 pallet:13 mix:65 total:159 2002 Georgia TechInput-oriented,all 159 together 2002 Georgia TechBroken Case,Input EfficiencyCompared Within(49/49)2002 Georgia TechPick Rate for Broken Case PickingAve=17SD=27 2002 Georgia TechFull case,Input Efficiency Compared Withi

13、n(32/32)2002 Georgia TechPick Rate for Case PickingAve=14SD=27.7 2002 Georgia TechPallet,Input Efficiency Compared within(13/13)2002 Georgia TechPick Rate for Pallet PickingLines/Labor hour(pallet)02468100.010.020.030.040.050.0100.0150.0200.0Morelines/labor hourFrequencyAve=25SD=27.7 2002 Georgia Te

14、chMixed,Input Efficiency Compared Within(65/65)2002 Georgia TechPick Rate for Mixed PickingLines/Labor Hour(mix)01020304050600.0020.0040.0060.0080.00100.00lines/labor hourFrequencyAve=10.6SD=23 2002 Georgia TechAggregate Pick Rate for All 159 2002 Georgia TechWhere do we go from here?2002 Georgia Te

15、chMany Opportunities to Improve the Benchmarking Tool Enhance the basic input/output model Enhance the ability to benchmark for technology,practice,&requirements 2002 Georgia TechSome Suggested MetricsInputs Space Capital Labor Inventory#of skus turnsOutputs Inbound receipt mix receipt variability r

16、eturns time to availability Fulfillment pick volume pick variability pick accuracy fill rate but Sorta 2002 Georgia Tech“Marker”Analysis 2002 Georgia TechPerformance“Marker”AttributeDEA Performance Score 2002 Georgia TechPerformance“Marker”PracticeDEA Performance Score 2002 Georgia TechResults Bigge

17、r is not always better,at least with regard to equipment and labor.There is,however,some evidence that more warehouse space leads to better system efficiency.Labor hours was not found to be a significant factor,by itself,in predicting system efficiency.However,the interaction of labor with investmen

18、t was found to be significant in the sense that labor hours mitigates the effect of investment(in other words,though high investment warehouses tended to be less efficient than low investment warehouses,the differences becomes less prominent the higher the labor hours).2002 Georgia TechMore Results

19、The interaction of investment and area was found to be significant.This means that high investment warehouses are even less efficient if they are also large.No matter how we segment the data,a very large proportion of warehouses are operating at or below 50%system efficiency.While this may reflect s

20、easonal fluctuations in customer orders,it still represents a very significant opportunity for improvement.2002 Georgia TechMore Results The opportunity for improvement seems largest for the segment of warehouses doing predominantly full case picking.In that segment,a smaller proportion of the wareh

21、ouses are efficient than in any other segment,and a larger proportion are operating below 50%efficiency.2002 Georgia TechOther Data Requirements Type(wholesale,retail,manufacturing)Industry(pharma,auto,electronics,)Order volume Sku spread Order size distribution Pallet/case/each distribution Plannin

22、g horizon Degree of automation Push vs Pull Picking strategy Sorta 2002 Georgia TechStill More Data Requirements Practices WMS?Compliant shipping?Space utilization?Velocity based slotting etc Diagnostics cost/carton shipped value added services inventory accuracy etc 2002 Georgia TechQuestions?2002 Georgia Tech演讲完毕，谢谢观看！