机械外文翻译中英文.docx
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机械外文翻译中英文.docx
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机械外文翻译中英文
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英文原文
Selectionofoptimumtoolgeometryandcuttingconditions
usingasurfaceroughnesspredictionmodelforendmilling
AbstractInfluenceoftoolgeometryonthequalityofsurfaceproducediswellknownandhenceanyattempttoassesstheperformanceofendmillingshouldincludethetoolgeometry.Inthepresentwork,experimentalstudieshavebeenconductedtoseetheeffectoftoolgeometry(radialrakeangleandnoseradius)andcuttingconditions(cuttingspeedandfeedrate)onthemachiningperformanceduringendmillingofmediumcarbonsteel.Thefirstandsecondordermathematicalmodels,intermsofmachiningparameters,weredevelopedforsurfaceroughnesspredictionusingresponsesurfacemethodology(RSM)onthebasisofexperimentalresults.ThemodelselectedforoptimizationhasbeenvalidatedwiththeChisquaretest.Thesignificanceoftheseparametersonsurfaceroughnesshasbeenestablishedwithanalysisofvariance.Anattempthasalsobeenmadetooptimizethesurfaceroughnesspredictionmodelusinggeneticalgorithms(GA).TheGAprogramgivesminimumvaluesofsurfaceroughnessandtheirrespectiveoptimalconditions.
1Introduction
Endmillingisoneofthemostcommonlyusedmetalremovaloperationsinindustrybecauseofitsabilitytoremovematerialfastergivingreasonablygoodsurfacequality.Itisusedinavarietyofmanufacturingindustriesincludingaerospaceandautomotivesectors,wherequalityisanimportantfactorintheproductionofslots,pockets,precisionmouldsanddies.Greaterattentionisgiventodimensionalaccuracyandsurfaceroughnessofproductsbytheindustrythesedays.Moreover,surfacefinishinfluencesmechanicalpropertiessuchasfatiguebehaviour,wear,corrosion,lubricationandelectricalconductivity.Thus,measuringandcharacterizingsurfacefinishcanbeconsideredforpredictingmachiningperformance.
Surfacefinishresultingfromturningoperationshastraditionallyreceivedconsiderableresearchattention,whereasthatofmachiningprocessesusingmultipointcutters,requiresattentionbyresearchers.Astheseprocessesinvolvelargenumberofparameters,itwouldbedifficulttocorrelatesurfacefinishwithotherparametersjustbyconductingexperiments.Modellinghelpstounderstandthiskindofprocessbetter.Thoughsomeamountofworkhasbeencarriedouttodevelopsurfacefinishpredictionmodelsinthepast,theeffectoftoolgeometryhasreceivedlittleattention.However,theradialrakeanglehasamajoraffectonthepowerconsumptionapartfromtangentialandradialforces.Italsoinfluenceschipcurlingandmodifieschipflowdirection.Inadditiontothis,researchers[1]havealsoobservedthatthenoseradiusplaysasignificantroleinaffectingthesurfacefinish.Thereforethedevelopmentofagoodmodelshouldinvolvetheradialrakeangleandnoseradiusalongwithotherrelevantfactors.
Establishmentofefficientmachiningparametershasbeenaproblemthathasconfrontedmanufacturingindustriesfornearlyacentury,andisstillthesubjectofmanystudies.Obtainingoptimummachiningparametersisofgreatconcerninmanufacturingindustries,wheretheeconomyofmachiningoperationplaysakeyroleinthecompetitivemarket.Inmaterialremovalprocesses,animproperselectionofcuttingconditionscausesurfaceswithhighroughnessanddimensionalerrors,anditisevenpossiblethatdynamicphenomenaduetoautoexcitedvibrationsmaysetin[2].Inviewofthesignificantrolethatthemillingoperationplaysintoday’smanufacturingworld,thereisaneedtooptimizethemachiningparametersforthisoperation.So,anefforthasbeenmadeinthispapertoseetheinfluenceoftoolgeometry(radialrakeangleandnoseradius)andcuttingconditions(cuttingspeedandfeedrate)onthesurfacefinishproducedduringendmillingofmediumcarbonsteel.Theexperimentalresultsofthisworkwillbeusedtorelatecuttingspeed,feedrate,radialrakeangleandnoseradiuswiththemachiningresponsei.e.surfaceroughnessbymodelling.Themathematicalmodelsthusdevelopedarefurtherutilizedtofindtheoptimumprocessparametersusinggeneticalgorithms.
2Review
Processmodellingandoptimizationaretwoimportantissuesinmanufacturing.Themanufacturingprocessesarecharacterizedbyamultiplicityofdynamicallyinteractingprocessvariables.Surfacefinishhasbeenanimportantfactorofmachininginpredictingperformanceofanymachiningoperation.Inordertodevelopandoptimizeasurfaceroughnessmodel,itisessentialtounderstandthecurrentstatusofworkinthisarea.
Davisetal.[3]haveinvestigatedthecuttingperformanceoffiveendmillshavingvarioushelixangles.CuttingtestswereperformedonaluminiumalloyL65forthreemillingprocesses(face,slotandside),inwhichcuttingforce,surfaceroughnessandconcavityofamachinedplanesurfaceweremeasured.Thecentralcompositedesignwasusedtodecideonthenumberofexperimentstobeconducted.Thecuttingperformanceoftheendmillswasassessedusingvarianceanalysis.Theaffectsofspindlespeed,depthofcutandfeedrateonthecuttingforceandsurfaceroughnesswerestudied.Theinvestigationshowedthatendmillswithlefthandhelixanglesaregenerallylesscosteffectivethanthosewithrighthandhelixangles.Thereisnosignificantdifferencebetweenupmillinganddownmillingwithregardtothecuttingforce,althoughthedifferencebetweenthemregardingthesurfaceroughnesswaslarge.Bayoumietal.[4]havestudiedtheaffectofthetoolrotationangle,feedrateandcuttingspeedonthemechanisticprocessparameters(pressure,frictionparameter)forendmillingoperationwiththreecommerciallyavailableworkpiecematerials,11L17freemachiningsteel,62-35-3freemachiningbrassand2024aluminiumusingasingleflutedHSSmillingcutter.Ithasbeenfoundthatpressureandfrictionactonthechip–toolinterfacedecreasewiththeincreaseoffeedrateandwiththedecreaseoftheflowangle,whilethecuttingspeedhasanegligibleeffectonsomeofthematerialdependentparameters.Processparametersaresummarizedintoempiricalequationsasfunctionsoffeedrateandtoolrotationangleforeachworkmaterial.However,researchershavenottakenintoaccounttheeffectsofcuttingconditionsandtoolgeometrysimultaneously;besidesthesestudieshavenotconsideredtheoptimizationofthecuttingprocess.
Asendmillingisaprocesswhichinvolvesalargenumberfparameters,combinedinfluenceofthesignificantparametersanonlybeobtainedbymodelling.MansourandAbdallaetal.[5]havedevelopedasurfaceroughnessmodelfortheendmillingofEN32M(asemi-freecuttingcarboncasehardeningsteelwithimprovedmerchantability).Themathematicalmodelhasbeendevelopedintermsofcuttingspeed,feedrateandaxialdepthofcut.Theaffectoftheseparametersonthesurfaceroughnesshasbeencarriedoutusingresponsesurfacemethodology(RSM).Afirstorderequationcoveringthespeedrangeof30–35m/minandasecondorderequationcoveringthespeedrangeof24–38m/minweredevelopedunderdrymachiningconditions.Alauddinetal.[6]developedasurfaceroughnessmodelusingRSMfortheendmillingof190BHNsteel.Firstandsecondordermodelswereconstructedalongwithcontourgraphsfortheselectionofthepropercombinationofcuttingspeedandfeedtoincreasethemetalremovalratewithoutsacrificingsurfacequality.Hasmietal.[7]alsousedtheRSMmodelforassessingtheinfluenceoftheworkpiecematerialonthesurfaceroughnessofthemachinedsurfaces.Themodelwasdevelopedformillingoperationbyconductingexperimentsonsteelspecimens.Theexpressionshows,therelationshipbetweenthesurfaceroughnessandthevariousparameters;namely,thecuttingspeed,feedanddepthofcut.Theabovemodelshavenotconsideredtheaffectoftoolgeometryonsurfaceroughness.
Sincetheturnofthecenturyquitealargenumberofattemptshavebeenmadetofindoptimumvaluesofmachiningparameters.Usesofmanymethodshavebeenreportedintheliteraturetosolveoptimizationproblemsformachiningparameters.JainandJain[8]haveusedneuralnetworksformodelingandoptimizingthemachiningconditions.Theresultshavebeenvalidatedbycomparingtheoptimizedmachiningconditionsobtainedusinggeneticalgorithms.Sureshetal.[9]havedevelopedasurfaceroughnesspredictionmodelforturningmildsteelusingaresponsesurfacemethodologytoproducethefactoraffectsoftheindividualprocessparameters.Theyhavealsooptimizedtheturningprocessusingthesurfaceroughnesspredictionmodelastheobjectivefunction.Consideringtheabove,anattempthasbeenmadeinthisworktodevelopasurfaceroughnessmodelwithtoolgeometryandcuttingconditionsonthebasisofexperimentalresultsandthenoptimizeitfortheselectionoftheseparameterswithinthegivenconstraintsintheendmillingoperation.
3Methodology
Inthiswork,mathematicalmodelshavebeendevelopedusingexperimentalresultswiththehelpofresponsesurfacemethodology.Thepurposeofdevelopingmathematicalmodelsrelatingthemachiningresponsesandtheirfactorsistofacilitatetheoptimizationofthemachiningprocess.Thismathematicalmodelhasbeenusedasanobjectivefunctionandtheoptimizationwascarriedoutwiththehelpofgeneticalgorithms.
3.1Mathematicalformulation
Responsesurfacemethodology(RSM)isacombinationofmathematicalandstatisticaltechniquesusefulformodellingandanalyzingtheproblemsinwhichseveralindependentvariablesinfluenceadependentvariableorresponse.Themathematicalmodelscommonlyusedarerepresentedby:
whereYisthemachiningresponse,ϕistherespons
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