Modeling Approaches and Software for Predicting the Performance ofMilling Operations at MAL- UBC

Y. Altintas, Professor

CIRP Member, ASME Fellow

University of British Columbia (UBC)

Manufacturing Automation Laboratory (MAL), http://www.mech.ubc.ca/~mal

1 INTRODUCTION

The purpose of this article is to review the research doneat the author's laboratory, therefore the general review ofthe vast metal cutting literature is not covered in thearticle. The readers are referred to the recent reviewpresented in CIRP by van Luttervelt et al. [1] and inASME by Ehman et al. [2]

The metal cutting research should lead to improveddesign of cutting tools, machine tool structures, spindleand feed drives and the optimal planning of individualmachining operations based on physical constraints. Theamplitude and frequency of cutting forces, torque andpower are used in sizing machine tool structures, spindleand feed drive mechanisms, bearings, motors and drivesas well as the shank size of the tools and fixture rigidity.The stress and temperature field in the cutting tool edge,chip and finish work piece surface are used in designingcutting edge shape as well as in optimizing feed, speedand depth of cut to avoid residual stresses on the finishsurface. Modeling the interaction between the cuttingprocess and structural vibrations of machine tool, cuttingtool and fixture leads to the identification of weak links inthe machine structure and determination of chattervibration free spindle speeds and depth of cuts [3]. Thecomplete model of the machining process is thereforeused in both design of cutting tools and machine tools,as well as planning of machining operations formaximum productivity and quality.

The article summarizes the models developed andadopted in the author's laboratory. The modeling of metalcutting mechanics is presented in section 2. Thekinematics and mechanics of milling are presented insection 3, followed by chatter stability prediction insection 4. Several simulation and experimental resultsare presented for complex end mills and inserted cutters

in section 5. The article is concluded with the currentissues in machining research and technology transfer insection 6.

2 MECHANICS OF CUTTING

The first step is to model the cutting process as afunction of work material, tool geometry and material,chip load and cutting speed. The macro-mechanics ofcutting lead to the identification of cutting coefficients,which are used in predicting the cutting forces, torque,power and chatter stability limits. The cutting coefficientscan be modeled using either orthogonal cuttingmechanics or mechanistic models. The micro mechanicsof metal cutting is on the other hand, is used to predictthe stress, strain and temperature distribution in the chipand tool. It is primarily used for tool design, the analysisof material behavior under high strain and temperature,and optimal selection of chip load and speed to avoidtool chipping, tool wear, and residual stresses left on thefinish surface.

2.1 Macro - Mechanics of Metal Cutting

The diagram of orthogonal cutting, where the plasticdeformation is assumed to take place at a thin shearplane, is shown in Figure 1. The process is modeled byconducting orthogonal cutting tests, typically turningtubes with a wall thickness equal to the radial depth ofcut (a). The orthogonal tool must have a sharp cuttingedge with zero side cutting edge and inclination angles.The cutting force in the radial direction is zero inorthogonal cutting. The cutting forces in the tangential(Ft) and feed (Ff) directions are measured with adynamometer, and chips are collected during each test.The measured forces are separated into shear (Ftc,Ffc)

ABSTRACT

The author has been conducting research in the area of metal cutting mechanics, metal cuttingdynamics, machine tool vibrations, precision machining and machine tool control in his ManufacturingAutomation Laboratory, at The University of British Columbia, Canada since 1986. This articlesummarizes the research conducted in mechanics and dynamics of metal cutting in our laboratory.Modeling of mechanics of metal cutting is summarized first. The models include orthogonal to obliquecutting transformation, mechanistic modeling of cutting coefficients, slip line field and Finite Elementmodeling. The author mostly focused on milling. The kinematics of milling with and without structuralvibrations is modeled. The geometric model of end mills and inserted cutters with arbitrary geometry aremodeled. The prediction of forces, torque, power and dimensional surface finish is explained for millingoperations. The chatter stability for milling operations is presented. The metal cutting knowledge istransferred to manufacturing industry by combining all the models in shop friendly software.

and flank contact/ploughing (Fte,Ffe) edge componentsas:

Figure 1: Mechanics of orthogonal cutting process.

aKahKFFF tetctetct +=+=

aKahKFFF fefcfefcf +=+=(1)

The cutting forces are assumed to be linearlyproportional to uncut chip area (h), and edge forces canbe identified by extrapolating the measured forces at zerocut thickness (h = 0) intercept. The slopes of the linearforce plots correspond to the cutting force coefficients(Ktc,Kfc) in the tangential and feed directions. Thethickness of the collected chips is measured and anaverage value is considered. The chip thickness (hc) ismore accurately predicted by measuring its length andweight. The specific weight and width of the chip areknown, thus the chip thickness can be evaluated. Theshear angle (φc) of the primary deformation zone can beevaluated as:

,c

c h

hr =

rc

rcc r

r

α−α

=φ −

cos1

costan 1 (2)

where (rc, rα ) are the chip compression ratio and rake

angle of the orthogonal tool, respectively. The shear

force (Fs) and average shear stress ( sτ ) on the primary

deformation zone can be evaluated as:

,sincos cfcctcs FFF φφ −= )sin/( c

ss ah

F

φ=τ (3)

Depending on the lubrication, cutting speed and materialtype, the chip may first stick than slide on the rake face.In macro-mechanics, and average Coulomb friction angle( aβ ) and friction coefficient ( aµ ) are considered, and

evaluated from the cutting force measurements as:

,arctantc

fcra F

F+= αβ aa βµ tan= (4)

The resultant cutting force ( cF ) can be expressed as a

function of shear force as:

)cos(sin)cos( racc

s

rac

sc

ahFF

αβφφτ

αβφ −+=

−+= (5)

The tangential and feed forces can be expressed as afunction of resultant cutting force, which leads to thefollowing:

])cos(sin

)cos([)cos(

racc

rasractc ahFF

αβφφαβ

ταβ−+

−=−=

)cos(sin

)sin([)sin(

racc

rasracfc ahFF

αβφφαβ

ταβ−+

−=−=

(6)

From equations (5),(6) the cutting coefficients can beexpressed directly as a function of average shear stress,shear angle, average friction angle and rake angle of thetool :

[ ][ ]

)cos(sin

)sin(/

)cos(sin

)cos(/

racc

ras

2fc

racc

ras

2tc

mmNK

mmNK

αβφφαβ

τ

αβφφαβ

τ

−+−

=

−+−

=

(7)

Once the cutting coefficients are identified, cutting forcesfor any depth of cut (a) and cut thickness (h) can beevaluated in an orthogonal cutting operation. When thecutting coefficients are found from the slope or trend ofthe force measurements, the method is calledmechanistic modeling. When the cutting forcecoefficients are evaluated from the shear stress, shearangle and friction angle, the method is based on themacro-mechanics of orthogonal cutting. The mechanicsapproach relates the basic material property, friction andtool geometry directly to the magnitudes of cuttingforces. Depending on the material behavior duringmachining, the three orthogonal cutting parameters( acs µφτ ,, ) may vary with the cut thickness (h), cutting

speed (V) and rake angle ( rα ). In order to cover wide

range of cutting conditions, the orthogonal cutting testsmust be conducted at a range of cutting speeds, feedsand rake angles. The orthogonal parameters can becurve fitted to empirical expressions to cover the range ofcutting conditions used in experiments.

Mechanistic approach has been popular in predicting thecutting forces, torque and power very quickly for a set oftool geometry and work material. In early 1950s, Kienzlereported specific cutting coefficient tables, which werecalibrated from extensive machining tests conducted onmost common alloys by using different rake anglesspeeds, feeds [4]. Metcut also prepared an extensiveMachining Data Handbook which contains cutting

coefficients and machinability conditions for commonlyused alloys [5].

Most practical tools used in industry have obliquegeometry, where the tools may have side cutting edgeangle, nose radius or helix angle. There are cutting forcesin all three directions, which have to be evaluated (Figure2). In mechanistic approach, the slopes or trend of themeasured cutting forces in all three directions areevaluated as in orthogonal cutting, see Eq. (5). Hence,each tool with a specific geometry must be calibrated inmachining tests in order to find the cutting coefficients inmechanistic modeling. However, using macro-metalcutting mechanics approach, or unified approach asArmarego calls it [6], the cutting coefficients for anyoblique tool can be predicted as follows:

Figure 2: Mechanics of oblique cutting process.

n22

nnn2

nnn

n

sac

n22

nnn2

nn

n

sfc

n22

nnn2

nnn

n

stc

iK

iK

iK

βηαβφ

βηαβφ

τ

βηαβφ

αβφτ

βηαβφ

βηαβφ

τ

sintan)(cos

sintantan)cos(

sin

sintan)(cos

)sin(

cossin

sintan)(cos

sintantan)cos(

sin

+−+

−−=

+−+

−=

+−+

+−=

(8)

where acK is the axial cutting coefficient for the force

perpendicular to the cutting speed and uncut chip plane.Stabler assumed that the chip flow angle ( η ) isapproximately equal to oblique angle (i), which can beused for practical force calculations, but not for tooldesign. The combined influence of rake and inclinationangles must be considered for more accurate predictionof chip flow direction that is important for the evacuation

of chip [1]. The normal shear angle ( nφ ), friction angle

( nβ ) and shear stress ( sτ ) in oblique cutting can be

assumed to be identical to the values obtained from theorthogonal cutting tests described above. The normalrake angle of the oblique tool must be evaluated from thevarious angles of the oblique tool [6],[7].

2.2 Micro-Mechanics of Metal Cutting

The prediction of stress, strain, strain rate andtemperature fields in the chip and tool wedge areimportant for tool and process design. The author'sresearch group studied two techniques: Slip Line Fieldanalysis technique as proposed by Oxley [8], andnumerical techniques such as Finite Element and FiniteDifference methods. The objective is to analyze theprimary, secondary and tertiary deformation zones for anarbitrary cutting tool shape. Since there are stillfundamental difficulties in modeling the behavior of metalduring cutting, where the strain and strain rates reach tovery high values, two dimensional cutting operationshave been analyzed, but with tools having arbitrarycutting edge and rake face shapes. The slip line fielddiagram of a tool with chamfer edge is shown in Figure3.

Figure 3: Slip line field model of chamfered tool.

Chamfered cutting edges are used on carbide and CBNtools for the high speed machining of hardened tool anddie steels. The chamfer strengthens the wedge againstchipping caused by thermal and mechanical stresses.The slip line field is modeled in such a way that the metalis trapped over the chamfer and incoming chip materialflows over it. After the chip moves over the chamferzone, it is approximated that the sticking and slidingfriction zone lengths are equal. The total contact lengthon the rake face is predicted from force equilibrium [9].The temperature modified flow stress of the material isidentified from orthogonal cutting tests conducted withsharp tools [8]. The cutting forces and temperaturecontributed in the primary shear, chamfer, sticking andsliding zones are expressed as a function of unknownshear angle, and known friction constants on the rakeface and temperature modified flow stress in each zone.The total energy consumed in all deformation zones areexpressed mathematically, and minimum energyprincipal is used for the prediction of shear angle

[10],[11]. The expression is quite nonlinear, therefore aniterative solution was necessary. The method leads to theprediction of maximum temperature at the rake face aswell as cutting forces contributed by the chamfer and flatrake face zones. P20 mold steel is used as an examplework material. The carbide and CBN tools have bindingmaterials which have typically diffusion limits of 1300and 1600 Celsius, respectively. The analysis indicatedthat the most optimal chamfer angle is about -15degrees, and the undesirable tool temperature is reachedwhen the cutting speed is above 240m/min for carbidetools and 500 m/min for CBN tools. The cut thicknesswas 0.06 mm/rev in dry machining tests. The affect oftemperature on the diffusion wear can be seen from SEMpictures of tested CBN tools shown in Figure 4.

Figure 4: SEM pictures of chamfered CBN tools atdifferent cutting speeds.

The slip line field analysis relies heavily on physicalunderstanding and detailed modeling of cutting toolgeometry, and only provides approximate solution in theaverage sense. A general approach, which can alsoprovide more detailed information about the cuttingzones, is through numerical modeling, and in particular,finite element modeling. In this approach, various toolgeometry, cutting conditions and more sophisticatedmaterial and friction models can be incorporated, and thedistribution of solution variables such as stress, strainand temperature may be obtained along with cuttingforces. Nevertheless, owing to the large deformationsand very high strain rates and temperatures involved incutting process, such numerical modeling presentssignificant numerical and analytical challenges. AnArbitrary Lagrangian-Eulerian (ALE) formulation hasbeen developed at UBC and applied for the prediction ofcutting variables in machining [12],[13]. The developedALE code can handle any two-dimensional tool geometrywith rake face grooves, chamfers or edge radius on thecutting edge. Using this FE program, the machining ofP20 mold steel by chamfered Carbide and CBN toolswas analyzed and cutting variables such as temperature,strain, strain rate, stress distribution in the chip andresidual stresses on the finish surface were predicted.The FE analysis of cutting with different chamfer anglesand at different cutting speeds shows that there is indeeda trapped dead metal zone under the chamfer, but itssize is dependent on tool geometry and cuttingconditions. The dead zone diminishes as cutting speedincreases, which may be attributed to material softeningas a result of rapidly rising temperatures at high speed.Sample ALE results for cutting with chamfered tool areshown in Figure 5. Similar to slip line field analysis, FEalso predicted maximum temperature of about 1200Celsius on the rake face when the cutting speed and chiploads are 240m/min and 0.060mm/rev, respectively.

Slip line field analysis requires fundamental expertise,and FE requires significant amount of computation time.Both techniques can be best used by the trainedengineers in metal cutting, and these techniques areuseful for tool design. However, more practical methodsare required for daily use in production floor for theselection of cutting speed and chip load which does notlead to thermal chipping or accelerated wear of thecutting edge. The author's group developed FiniteDifference technique for both continuous machining andmilling, which is integrated to our advanced cuttingprocess simulation software used in industry. The finitedifference technique uses average friction coefficient onthe rake face, and considers sharp cutting edge. Thetemperature distribution in both chip and tool arepredicted and displayed. When the temperature reachesto a critical threshold, which is about 1300 Celsius forcarbide and about 1600 for CBN tools, the planner iswarned for possible chipping or accelerated wear of thetool. The details of the finite difference modeling can befound in [14]. Briefly, in this temperature predictionmodel, the shear energy created in the primary zone, thefriction energy produced at the rake face-chip contactzone and heat balance between the moving chip and toolare considered. Heat balance equations were determinedin partial differential equations form for the chip and forthe tool. The finite difference method was utilized for thesolutions of the steady-state tool and chip temperaturefields (Figure 6).

Figure 5: ALE analysis results for chamfered CBN tool.

In order to determine the transient temperature variationin the case of interrupted machining, the chip thicknesswas discretized along the time. Steady-state chip andtool temperature fields were determined for each of thesediscretized machining intervals. Based on thermalproperties and boundary conditions, time constants were

determined for each discrete machining interval. Byknowing the steady-state temperature and time constantsof the discretized first order heat transfer system, analgorithm have been developed to determine thetransient temperature variations in interrupted turningand milling operations (Figure 7).

Figure 6: Predicted isotherm patterns of the chip duringthe machining of mild steel (cutting conditionas are givenin [14] , temperatures in °C).

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Figure 7: Measured and predicted average chip/toolinterface temperature during milling AISI-4140 cuttingconditions are given in [14].

It must be noted here that analysis methods in micro-mechanics of metal cutting heavily depend on not onlythe theory, but modeling of material behavior, such asfriction field on the rake face and temperature-strain-strain rate dependent flow stress of the material in thedeformation zones. If these physical parameters are notcorrectly identified, the methods used in the analysis ofmicro-mechanics of metal cutting may not yield reliableand practical results.

3 MECHANICS AND DYNAMICS OF MILLING

The author’s group has spent considerable researcheffort in modeling the milling process in time andfrequency domain. The time domain model is used topredict the cutting forces, torque, power, dimensionalsurface finish, and the amplitudes and frequency ofvibrations during a milling operation. The frequencydomain analysis leads to the identification of chattervibration free spindle speeds, axial and radial depth ofcut conditions in milling.

3.1 Time Domain Modeling of Milling

The work piece is fed linearly towards a rotating cutterhaving multiple teeth in milling operations. A point on thecutting edge of each tooth traces a trochoidal path [15],producing periodic chip loads at tooth passing frequency.The diagram of milling is shown in Figure 8.

If the radial width of cut is large, and the influence ofstructural vibrations is not considered in time domain, thecut thickness (h) can be approximated by assuming thatthe circular cutter body shifts at amount of feed per toothat tooth passing periods,

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Figure 8: The geometry of milling process.

φφ sin)( ch = (9)

where φ is the angular immersion of the tooth measuredfrom the axis normal to the feed and c is the feed pertooth [16]. However, if the analysis is expected to providedimensional surface finish, feed marks and interactionwith structural vibrations of the machine tool/fixture, truekinematics of dynamic milling are preferred. The author'sgroup included the structural dynamic models of bothwork piece and cutter at the cutting edge - finish surfacecontact zones, see Figure 9. For example, a point on thecutting edge has coordinates, which are dependent onspindle speed, tool geometry, radial immersion anddepth of cut:

[ ] [ ]tztytxtRftztytxP ttt ,),(),(),(,)(),(),( Ω= (10)

where the cutter axis may vibrate away from thestationary spindle axis in feed ( )(txt ) and normal ( )(tyt )

directions, and z is the elevation of cutting edge pointfrom the tip of the cutter. The cutter has a radius of Rand the spindle speed is )(tΩ which is used incalculating the angular immersion of the cutting edge,e.g. ttt )()( Ω=φ . A point on the work piece surfacemoves linearly towards the rotating but vibrating cutterwith a feed speed of f[mm/s], and its coordinates aredependent on the feed speed and part vibrations at thatpoint:

[ ] [ ]tfztytxftztytxP wwww ,,),(),()(),(),( = (11)

where ww yx , are the amplitudes of work piece vibrations

at this point, and f is the feed speed [mm/s]. Themathematical model of the kinematics, which isimplemented in a computer algorithm needs quite adetailed presentation which can be found in [17],[18].The intersection of )(tPt and )(tPw gives the cut surface.

The instantaneous chip thickness removed by )(tPt is

most correctly evaluated by subtracting the present tool -work piece contact coordinates from the surfacegenerated and tracked by )(tPw previously.

The subtraction is done along the radial vector whichpasses through the cutting edge point and vibratingcutter center, see Figure 9. The approach allowsprediction of true chip load generated by the trochoidalmotion of the milling tool and structural vibrations of boththe cutter and work piece. The dimensional surfacegeneration is rather automatic with this method, and theradial and axial run outs can be easily integrated to themodel by defining each edge radius differently. Furtherdetails of the complete mathematical model of dynamicmilling can be found in [19],[20],[21]. The structuralvibrations of both the work piece and cutter are predictedby applying cutting forces to each structure at discretetime intervals [22],[23],[24],[25]:

)()()()(

)()()()(

tFtyktyctym

tFtxktxctxm

yyyy

xxxx

=++=++

&&&

&&&(12)

Figure 9: Surface and dynamic chip load evaluationusing true kinematics of milling.

where m, c, k are the mass, damping and stiffness ofeither tool or work piece at the contact zone in the feed(x) or normal (y) directions. The differential cutting forcesacting on a small cutting edge element with a height ofdz in the tangential, radial and axial directions areexpressed as :

[ ][ ][ ]dzKzhKzdF

dzKzhKzdF

dzKzhKzdF

aejjacja

rejjrcjr

tejjtcjt

+=

+=

+=

))((),(

))((),(

))((),(

,

,

,

φφ

φφ

φφ

(13)

where the cutting constants ( acrctc KKK ,, ) are either

obtained from orthogonal to oblique cuttingtransformation as shown in Eq. (8) where the obliqueangle is equal to helix angle in end mill and fcrc KK = , or

using mechanistic approach as presented in thefollowing. It must be noted that tooth number (j) atelevation z has different chip load than elsewhere if thereis helix angle, run out or both. Proper geometric handlingof the chip load calculation must be modeled asexplained in [7]. The differential cutting forces can beprojected in the three Cartesian axis as :

jajjz

jjrjjtjjy

jjrjjtjjx

dFzdF

zdFzdFzdF

zdFzdFzdF

,,

,,,

,,,

))((

)(cos)(sin))((

)(sin)(cos))((

+=

−+=

−−=

φ

φφφ

φφφ

(14)

The differential cutting forces can be integrated digitallyalong the flute-work piece contact when the vibrationsand true kinematics of milling are considered [26]. If onlystatic forces are to be evaluated, the approximate chipload given in Eq. (9) is substituted in Eqs. (13) and (14),and integrated along the flute-work piece engagementlength [27]:

[ ][ ]

[ ]))((2,

))((1,

,

)(cos)(sin1

)(2sin)(2)(2cos4

)(

zz

zz

jrejte

jjrcjtcjjx

jj

jj

zKzKk

zzKzKk

cF

φ

φβ

β

φφ

φφφφ

−+

−+−=

[ ]

[ ]))((2,

))((1,

,

)(sin)(cos1

2cos)2sin2(4

)(

zz

zz

jrejte

jrcjjtcjjy

jj

jj

zKzKk

KKk

cF

φ

φβ

β

φφ

φφφφ

++

+−−

=

[ ]))((2,

))((1,

, )(cos1

)(

zz

zz

jaejacjjz

jj

jj

KzcKk

F

φ

φβ

φφφ

−=

(15)

where )((2, zz jj φ and ))((1, zz jj φ are the upper and lower

boundaries of helical flute engagement, helix lagparameter Dk /tan2 β=β , and the instantaneous

immersion angle of a flute j is zkjz pj β−φ+φ=φ )( [7].

Here, φ is the angular position of reference tooth 0=j

at elevation z = 0, helix angle is β , cutter pitch angle

Np /2π=φ , the number of teeth is N, and the cutter has

a diameter of D. If the helix angle is zero ( 0=β ), thedifferential element height is equal to the axial depth ofcut (dz = a), and the instantaneous cutting forces aregiven by Eq.(15). Note that when the tooth is outside the

entry ( stφ ) and exit ( exφ ) angles of the cut, there is zero

cutting force. The cutting forces contributed by all flutesare calculated and summed to obtain the total

instantaneous forces on the cutter at immersion φ .

;)(;)(;)( ∑∑∑−

=

−

=

−

=

===1N

0j

zz

1N

0j

yy

1N

0j

xx jjjFFFFFF φφφ (16)

Further details of computer algorithms in predicting thecutting forces are given in the text [7].

3.2 Mechanistic Modeling of Cutting ForceCoefficients in Milling

When cutter has inserts with complex edge shape andnon-uniform chip breaking grooves on the rake face, theorthogonal to oblique cutting transformation can not beused effectively. In this case, each insert must becalibrated mechanistically in order to identify its uniquecutting force coefficient.

Mechanistic modeling approach has been quite popularin order to predict the cutting force coefficients quickly fora set of fixed cutter geometry and material couple. Thecutting coefficient is either expressed as a constantnumber [28],[29],[30],[31], or as a function of cutthickness, cutting speed and tool geometry[32],[33],[34],[35],[36],[37]. Depending on the complexityof the tool geometry, behavior of the material at differentchip loads and cutting speeds, there may be quite anumber of machining tests to evaluate cuttingcoefficients mechanistically. The author adopted asimple cutting force relationship as shown in Eq. (13),which can be directly correlated with the unifiedorthogonal to oblique cutting mechanics transformationapproach proposed by Armarego [38].

The average milling forces per tooth period isindependent of helix angle, if the cutting coefficients areassumed to be chip load independent as expressed inEq. (13). Integrating the cutting forces (Eq. (15)) in allthree directions and dividing them by the pitch angle( Np /2π=φ ) gives the following average forces per tooth

period :

[ ][ ]

[ ]

[ ][ ]

[ ]

[ ] ex

st

ex

st

ex

st

aeacz

rete

rctc

y

rete

rctc

x

KcKNa

F

KKNa

KKNac

F

KKNa

KKNac

F

φφ

φ

φ

φ

φ

φφπ

φφπ

φφφπ

φφπ

φφφπ

+−=

+−

+−=

+−+

−−=

cos2

sincos2

2cos2sin28

cossin2

2sin22cos8

(17)

Full immersion slot milling experiments are usuallyconducted at a range of feed rates (c), and averageforces are measured during the cutting tests. Theaverage cutting force measurements are plotted as alinear function of feed rate (c) as,

),,( zyxqFcFF qeqcqe =+= (18)

where the intercepts at zero feed rate ( qeF ) correspond to

edge forces [39]. By applying the boundary conditions ofslot milling engagement ( π=φ=φ exst ,0 ) to the average

force equations (17), the average forces are found as:

aeacz

tetcy

rercx

K2

NacK

NaF

KNa

cK4

NaF

KNa

cK4

NaF

++=

++=

−−=

π

π

π

(19)

From the measured values of Eq. (18) and equivalentexpression Eq.(19), the cutting force coefficients arefound mechanistically as:

Na

F2K

Na

FK

Na

FK

Na

F4K

Na

FK

Na

F4K

zeae

zcac

xcte

xcrc

yete

yctc

==

−=

−=

==

;

;

;

π

π

π

(20)

It must be noted that the average forces in slotting maybe close to zero due to force cancellation with certainnumber of teeth. In those cases, less than full immersiontests can be conducted by considering proper immersionboundaries in Eq. (17). The mechanistic cuttingcoefficients are usually quite accurate since they arecalibrated directly from the milling tests conducted withthe same cutter to be modeled. However, themechanistic cutting coefficients are valid only for theparticular cutter geometry tested, hence the method cannot be used for cutter design purposes [40]. Some insertsmay have varying rake angle along its rake face, hencethe cutting coefficients may not be the same along theedge. In such cases, the cutting coefficients must beidentified as a function of depth of cut or insert edgeposition. The resulting cutting force coefficient may be apolynomial function of insert location, which is presentedin the following section.

3.3 Generalized Geometric Modeling of End Millsand Inserted Cutters

Variety of helical end mills and inserted cutters withvarying geometry is used in industry. Helical cylindrical,helical ball, taper helical ball, bull nosed and specialpurpose end mills are widely used in aerospace,automotive and die machining industry. While thegeometry of each cutter may be different, the mechanicsand dynamics of the milling process at each cutting edgepoint are common. The author's group developed ageneralized mathematical model of most helical end millsused in industry [41]. The end mill geometry is modeledby wrapping helical flutes around a parametric cutterenvelope. The envelope of the cutter geometry isparametrically modeled using standard CAM definition,see Figure 10. The coordinates of a cutting edge pointalong the parametric helical flute are mathematicallyexpressed.

Figure 10: Parametric definition of general cuttergeometry.

Sample end mills with helical flutes are shown in Figure11. The chip thickness at each cutting point is evaluatedby using the true kinematics of milling including thestructural vibrations of both cutter and work piece, asexplained in section 3.1. By digitally integrating theprocess along each cutting edge, which is in contact withthe work piece, the cutting forces, vibrations, dimensionalsurface finish and chatter stability lobes for an arbitraryend mill can be predicted [18]. Experimental andsimulation results are shown for sample end mills withcomplex geometry in the experimental section 5.

Inserted cutters are also modeled using a similarphilosophy [41]. The insert geometry and distribution ofinserts on the cutter body vary significantly in industrydepending on the application. A generalizedmathematical model of inserted cutters is developed. Theedge geometry is defined in the local coordinate systemof each insert, and placed and oriented on the cutterbody using cutter's global coordinate system, see Figure12. The cutting edge locations are definedmathematically, and used in predicting the cut thicknessdistribution along the cutting zone. Each insert may havea different geometry, such as rectangular, convextriangular or a mathematically definable edge. Eachinsert can be placed on the cutter body mathematicallyby providing the coordinates of insert center with respectto the cutter body center. The inserts can be oriented byrotating them around the cutter body, thus each insertmay be assigned to have different lead and axial rakeangles. By solving the mechanics and dynamics ofcutting at each edge point, and integrating them over theedge contact zone, it is shown that the milling processcan be predicted for any inserted cutter. As noted earlier,the cutting coefficients may be different for each insert,and may even vary along the insert's cutting edge, whichare considered in the mathematical model. A sampleapplication of inserted cutter modeling and analysis isprovided in the experimental section 5.

Figure 11: Helical cutting edges wrapped around endmills.

Figure 12: Geometric modeling of inserted cutters.

4 CHATTER STABILITY IN MILLING

Chatter vibrations are still most limiting factor inpreventing high material removal rates in machining.Unfortunately, chatter is avoided by reducing spindlespeed and depth of cut, hence the productivity, in mostproduction floors. Since Tlusty [42] and Tobias [43], therehas been significant amount of research andunderstanding accomplished in chatter. However, due tothe complexity of chatter, its physics and mathematics,the machine tool and manufacturing engineers somehowhave not absorbed the knowledge. The author's group

has spent considerable effort and years in modeling andunderstanding the chatter vibrations, and has beensuccessful in using and transferring the methods toindustry which led to noted productivity gains.

Chatter occurs due to relative structural vibrationsbetween the tool and the work at the cutting zone.Consider a simple case where the cutter has structuralflexibility in the feed (x) and normal (y) directions, seeFigure 9. When a tooth enters the cut, it excites thenatural modes of the structure, hence leaving a wavysurface finish behind due to transient vibrations. Whenthe second tooth comes, it also experiences vibrationsand leaves a wavy surface behind. The true dynamic chipthickness is therefore dependent on not only the rigidbody motion (i.e. feed and spindle speed) but on thepresent and past vibration marks left on the cut surfaceas well. If the present (i.e. inner wave) and previous (i.e.outer wave) are parallel or in phase, the dynamic chipload would still remain the same regardless of vibrations.However, when the phase shift is close to 180 degrees,than the chip thickness oscillates between two extremevalues. If the system can not absorb the energy, theprocess becomes unstable, and the vibrations may growexponentially until the tool jumps out of cut or breaks.Since the cutting forces are proportional to the chipthickness, they too oscillate with large magnitudes, whichmay damage the cutter, work piece or spindle bearings.Chatter occurs close to one of the dominant modes of themachine tool structure. At slow speeds and heavy cuts,the chatter is mainly dominated by the low frequencyspindle and machine tool column-table modes. Highernatural modes of the machine tool structure such asspindle, or slender end mill may dominate the chatter athigher speeds.

Budak and Altintas [44] developed a chatter theoryspecifically for milling operations. The details of thederivations can be found in the text [7] and articles [45],[46],[47] published by the author's group. The solution isbriefly summarized here. The chatter stability equation isreduced to the following quadratic form:

)()(

))(()(

01

1

0

12

0

cyyyycxxxx

yxxyyyxxcyycxx

iGiGa

iGiGa

aa

ωαωα

ααααωω

+=

−==+Λ+Λ

(21)

and yyxx GG , are the direct frequency response functions

of the machine tool/work piece structure measured at thecutter tip, and Λ is the eigenvalue. The cross frequencyresponse functions can also be included as shown in[45]. The directional factors are dependent on the cutterengagement angles with the work piece, and given as :

[ ]

[ ]

[ ]

[ ] ex

st

ex

st

ex

st

ex

st

rryy

ryx

rxy

rrxx

KK

K

K

KK

φφ

φφ

φφ

φφ

φφφα

φφφα

φφφα

φφφα

2sin22cos5.0

2cos22sin5.0

2cos22sin5.0

2sin22cos5.0

−−−=

++−=

+−−=

+−=

(22)

where tcrcr KKK /= . The eigenvalue Λ is obtained as:

IR0211

0ia4aa

a2

1ΛΛΛ +=−±−= )( (23)

The critical depth of cut for chatter stability limit is givenby,

)(lim2

t

R 1NK

2a κ

Λπ+−= (24)

where RI ΛΛ=κ / and smaller axial depth of cut isaccepted from the two values of the eigenvalues used.The corresponding tooth period ( [ ]sT ) and spindle speed

( )min]/[revn are given by,

NT

60nk2

1T

c=→+= )( πε

ω (25)

where the phase shift between the inner and outer chip

surface waves is ,tan23 1 κ−π=ε − and k = 0, 1, 2, 3, …represents the number of lobes or the number of wavesleft on the cut surface within one tooth period. When theaxial depth of cut and spindle speed is selected under thechatter stability limits defined by the depth of cut andspindle speed values predicted by the theory, the chattervibrations are avoided and higher material removal ratescan be obtained. The theory presented here is based onlinear stability laws, which do not consider time varyingcutting coefficients, tool jumping out of cut, and processdamping caused by the friction of tool flank with the wavyfinish surface . However, a time domain simulation ofchatter stability, which is also developed by the author'sgroup as explained in the previous section, considers allof the non-linearities, and is used to predict forces,vibrations, torque, power and surface form errors. Theauthor's group compared their the time domain andfrequency domain solutions, as well as experimentalobservations, at a variety of cutting conditions withstructural dynamic modes. The agreement was found tobe very satisfactory as supported by the experimentalresults presented in the following section.

5 INDUSTRIAL APPLICATION ANDEXPERIMENTAL RESULTS

The milling algorithms presented in the article have beenapplied in modeling some sophisticated end mills andinserted cutters for the benefit of industrial partners ofour laboratory. Some of the applications are presentedhere.

Tapered helical ball end mills are used in five-axisperipheral milling of jet engine compressors made ofTitanium alloy Ti6Al4V. The orthogonal cuttingparameters of Ti6Al4V are modeled from tube turningtests and given in Table 1.

The cutter geometry, and predicted and measured cuttingforces are shown in Figure 13.

Figure 13: Predicted and measured cutting forces for atapered helical ball end mill.

Table 1:Orthogonal cutting parameters of Ti6Al4V.

)(MPa613s =τ

(deg).. ra 290119 αβ +=

1c0c hCr =

r0 02807551C α.. −=

r1 008203310C α.. −=

)/( mmN24K te =

)/( mmN43K fe =

The tapered cutter has a constant lead, therefore it has avarying helix or oblique angle along the helical flute [41].The cutting coefficients vary at each point along thecutting edge, and they are modeled by orthogonal tooblique cutting transformation as proposed by Armarego[6]. Similarly, a cutter with two coated circular inserts isused in milling Ti6Al4V. The geometric model, picture ofthe cutter, and the predicted and measured milling forcesare presented in Figure 14.

Figure 14: Predicted and measured cutting forces for acutter with circular inserts.

Figure 15: Predicted and experimentally observed chatter stability lobes, frequency spectrum and dimensional surfacefinish in ball end milling of Titanium Ti6Al4V.

Again, the orthogonal cutting parameters presented inTable 1 is used in oblique transformation [48],[49]. Themethod is applied in predicting chatter stability lobes, aswell as the forces, dimensional surface finish, vibrationamplitudes when chatter is present during milling. Notethat average, constant cutting coefficients are used inpredicting the chatter stability solved in the frequencydomain. The chatter stability is also predicted in timedomain, where the varying cutting coefficients and non-linearities in the process are considered [20], [21]. Asample ball end milling of Ti6Al4V is presented in Figure15. The details of the machine dynamics and cuttergeometry can be found in [26],[46]. As indicated before,the analytical frequency domain chatter stability solutionagrees well with the time domain simulation. An accuratetime domain solution takes number of hours, whereasthe frequency domain solution takes few seconds with anacceptable accuracy. However, both time domain andfrequency domain solutions may lead to inaccuratepredictions due to neglected process damping, which canbe identified only experimentally for a reliable solution.

The stability lobes allow the process planner to select thehighest possible depth of cut and spindle speed, i.e.

material removal rate, without causing chatter vibrations.Because the author's group uses true kinematics ofmilling with the presence of vibrations, the dimensionalsurface errors, vibration amplitudes and frequency, andthe cutting forces are predicted with a very reasonableaccuracy. By considering variety of end mill geometry,about 85% of the force predictions have less than 10%deviation from measurements, with a maximum deviationin all cases less than 20% [21][54]. It can be stated thatthe orthogonal to oblique transformation is quite useful inpredicting the performance of the end mills during thedesign stage before they are manufactured. However, foran accurate prediction, the cutting edges must not havechip breakers or chamfers, and orthogonal cuttingparameters must be carefully identified from orthogonaltube turning tests.

A sample multi-level inserted milling cutter and itsgeometric model is shown in Figure 16. There are twoflutes and four rectangular inserts on each flute. Oneseries of inserts have 10 degrees of helix, while thesecond series have 20 degrees helix. The cuttingcoefficients of each insert type are modeledmechanistically, and given in Table 2 for inserts with 10degrees helix angle [50].

Table 2: Mechanistically modeled cutting coefficients forinserts shown in Figure 16. (z is the insert edge length.)

Cutting Coef. Fitted curve

tcK [N/mm2] 5.10734.909.7 2 +− zz

rcK [N/mm2] 1.7953.22298.25 2 +− zz

acK [N/mm2] 55.2944.15955.19 2 +− zz

teK [N/mm] 78.3891.134.0 2 +−− zz

reK [N/mm] 80.2398.2215.3 2 ++− zz10°°

helix

ang

le

aeK [N/mm] 80.5456.2766.2 2 −+− zz

tcK [N/mm2] 4.92576.226.5 2 ++− zz

rcK [N/mm2] 1.4096.850.13 2 ++− zz

acK [N/mm2] 6.2279.1813.15 2 −+− zz

teK [N/mm] 86.3304.204.0 2 +−− zz

reK [N/mm] 86.5338.146.0 2 ++− zz20°°

helix

ang

le

aeK [N/mm] 92.656.225.0 2 −+− zz

Figure 16: Predicted and experimentally evaluated cuttingforces produced by a two fluted four layer indexed cutter.

Sample comparison of predicted and measured cuttingforces are shown in Figure 16. The chatter stability lobeswere predicted in time domain using the cuttingcoefficients given in Table 2. By using average cuttingcoefficients along the insert edge length (z) the stabilitylobes are predicted in the frequency domain as well, seeFigure 17. The model considers the tool geometry, feedand speed, as well as vibrations, which are used inpredicting the cutting forces and dimensional surfacefinish, described by the kinematics of milling andvibrations. It can be seen that the simulated andexperimentally obtained stability lobes chatter frequencyand dimensional surface finish are in good agreement.

The author's group developed various methods inimproving milling process planning and productivity. Themilling process is integrated to solid model based CADsystem, and part geometry dependent milling process issimulated and the feed at each NC block is optimized[16],[27]. Radial width of cut and feed are analyticallyidentified to lead minimum static form errors when thinwebs are milled with long slender end mills [51],[52],[53],[54]. The influence of variable pitch cutters ondimensional surface finish is analyzed, and the pitchangle of the cutter is tuned to dominant structural modein the frequency domain which allows chatter free millingat a desired speed and depth of cut [47],[55]. Theknowledge of milling process modeling is applied tomonitoring and adaptive control of milling operations,spindle design as well as high speed feed drive controlsystem which are not listed here.

Figure 17: Stability lobes for Al-7075 with cutter shown in Figure 16. Cutting Conditions: Half immersion down milling with0.05mm/tooth feed rate.

6 CONCLUDING REMARKS

A brief overview of the research conducted by theauthor's research group is presented here. The detailedanalysis of metal cutting is attempted using slip line fieldand Finite Element modeling techniques, which arecalled micro-metal cutting mechanics here. Micro-metalcutting mechanics include the behavior of the plasticallydeformed metal in the cutting, rake face-chip interfaceand flank -finish work piece interface zones. The success

of the analysis models is heavily dependent on the abilityto model the material behavior during cutting, tool rakeface - chip friction contact, and interaction between theflank and elasto-plastically deformed finish surface. Wehave not been able to sufficiently understand and modelthis phenomenon up to the present. The material modelsare best estimated from orthogonal cutting tests due topresence of high strains, strain rates and temperaturedistribution in metal cutting zone. However, since we arenot able to measure the strain, strain rate and

temperature distribution in the chip and shear zoneaccurately, the predicted flow stresses are still veryapproximate. The same criticism is valid for chip-rakeface interface, where the friction field may varysignificantly depending on the state of material.Instruments and methods, which allow accuratemeasurement of temperature and tool-chip interfacepressure, have yet to be developed for deeperunderstanding and modeling of micro-mechanics ofmetal cutting.

The same argument is not valid for macro mechanicsmodels, which are heavily dependent on experimentallyidentified average values of pressure and temperature inthe cutting zone. It is possible to predict the cuttingforces, torque, power, and dimensional surface finish andchatter stability with satisfactory accuracy using thepresent knowledge of the macro-mechanics of millingoperations. We are still not able to analytically model theinteraction between the flank face of the tool and wavyfinish surface, i.e. process damping, in machining whichmay suppress the chatter vibrations at the expense ofaccelerated tool wear. However, this problem alsobelongs to the micro-mechanics of metal cuttingresearch.

ACKNOWLEDGEMENTS

The research reviewed in this article is based on thethesis of graduate students supervised by the author. Thework of following graduate students and visitingacademics have been most relevant to the article. A.Spence (Ph.D., 1992), E. Budak (Ph.D., 1995), S. Engin(Ph.D., 1999), M. Movahheddy (Ph.D.2000), Dr. G.Yucesan (1992), Dr. K. Sirashe (1995), Dr. E. Shamoto(1996), Dr. I. Lazoglu (1999-2000), D. Montgomery(M.A.Sc. 1990), P. Lee (M.A.Sc. 1996), H. Ren (M.A.Sc.,1998), M.L. Campomanes (M.A.Sc. 1998). The author'sresearch laboratory received financial and materialsupport from various research centers and companies.The major funding sources include Natural Sciences andEngineering Council of Canada (NSERC), Pratt &Whitney Canada, General Motors USA and Canada,Boeing Corporation, Mitsubishi Materials, Weiss,Milacron and Mori Seiki.

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