a residual-stress model for the milling of.pdf

Journal of Materials Processing Technology

E L S E V I E R Journal of Materials Processing Technology 51 (1995) 87-105

A residual-stress model for the milling of aluminum alloy (2014-T6)

K u a n g - H u a F u h * , C h i h - F u W u

Department of Mechanical Engineering, Tatung Institute of Technology, 40 Chungshan North Road, 3rd Sec., Taipei, Taiwan, ROC

Received 26 October 1993

Industrial Summary

One of the important problems encountered in the milling processes is the elastic deformation of the workpiece; thus, how to select the cutting parameters to reduce the residual stress is especially crucial. A mathematical model is presented for predicting the residual stresses of alloy 2014-T6 caused by end-milling. Factors such as the cutting conditions (cutting speed, feed, and cutting depth) and the tool geometries (tool nose radius and flank wear) are considered in this paper. To reduce the number of experiments required and to build the mathematical model for these variables, Response Surface Methodology (RSM) with the Takushi method are used. In addition, variance analysis and an experimental check are conducted to determine the promin- ent parameters and the adequacy of the model. According to the above processes, it is shown that the cutting speed, feed, tool nose radius and flank wear have the most significant effect on the residual stresses and there is an interaction between the cutting speed and flank wear. The affect on the residual stress of the cutting conditions and tool geometries can be explained in terms of the cutting force, the rise in temperature and the microstructure variation. Therefore, this model, offering good correlation between the experimental and predicted results, is useful in selecting suitable cutting parameters for the machining of alloy 2014-T6.

Notations

E HV HRB A T

dimensionless hole-drilling calibration constants Young 's modulus Vickers microhardness Rockwell hardness (1/16 in ball, 100 kgf) rise in temperature f rom the initial temperature of the workpiece

* Corresponding author.

0924-0136/95/$09.50 % 1995 Elsevier Science S.A. All rights reserved ~.~DI 0 9 2 4 - 0 1 3 6 ( 9 4 } 0 1 3 5 5 - 5

88 K.-H. Fuh, C.-F. Wu/.Iournal ~['Materials Processing Technology 51 (1995) 87 105

AZ

~;i

G1

0" 2

O'n 1

O" n

0"Az

the different depth of the nth layer and the (n - 1)th layer angle between gauge 1 and the principle stress measured strain relaxation maximum principle stress minimum principle stress stress for the (n - 1) layer stress for the n layer stress for the nth layer Poisson's ratio

1. Introduction

The performance of parts for aircraft is sensitive to their surface condition as machined by milling, because a good milled surface significantly reduces the processing time and improves the fatigue strength, corrosion resistance and creep life. Thus, quality control to measure surface texture is necessary for these parts. An important criterion of surface quality is appraisal for residual stresses. Hence, the main points of the present investigation are the properties of the residual stresses caused by end- milling.

The presence of residual stresses in structures and components has long been recognized, but only recently have many investigations been conducted on their properties with the aim of quantifying them accurately. Generally the presence of compressive residual stresses is beneficial and of the tensile stresses is detrimental [1 4]. Earlier works [5 7] have revealed that the residual stresses result from thermal strain, elastic-plastic strain and microstructure change affected by the machining state, these factors in turn are affected by the tool geometries, the cutting conditions, and the properties of the work material. Mishra [8] derived the residual stresses due to a moving heat source under various simulated cutting conditions, but the predicted trend is not in agreement with the results of actual machining as the surface is approached. Response Surface Methodology (RSM) has been utilized for determining the residual stresses under different cutting conditions and for various tensile strengths presented by different materials [3]. Whilst the properties of the materials were not coincident except for tensile strength, some materials machined by a tool with a chamfer have been found to result in microstructure change because of the high rise in temperature [9,10]. The computer-simulation research of Den [11] has been concerned with the predominant effect of flank wear on the work temperature and on the residual stresses. Young and Oxley [12] have found that the cutting forces is affected significantly by the tool nose radius.

However, the researches mentioned above have paid no attention to the effect of the cutting conditions and tool geometries simultaneously, and cannot find the optimum tool geometries and cutting conditions for industrial machining by considering the tendency of these parameters [3, 9, 10, 13]. Mose of these previous work takes account of a single parameter whilst the others ar fixed, hence, the interactive influence between these parameters is neglected. If the effect of interaction between parameters

K.-H. Fuh, C.-F. Wu/Journal of Materials Processing Technology 51 (1995) 87-105 89

is encountered, a series of trials should be processed, which is a time-consuming work. Providing that an experimental design is applied to the surface roughness and frictional damping [14,15], then the number of trials may be reduced significantly, and at the same time can show the effect of each parameter and of their interactions.

In order to predict and improve the residual stresses of the machined surface, the purpose of the present work is to study the influence exerted by the tool geometries and cutting conditions on the residual stresses and to build a model for predicting the residual stresses and choosing suitable cutting parameters for alloy 2014-T6.

2. Postulation of the mathematical model

Parameters that generally affect the residual stresses in a milled surface may be grouped into quantitative parameters such as cutting conditions, tool geometries and hardness of materials, and qualitative parameters such as fixed methods, lubricants, material properties, etc. In this investigation, all of the qualitative factors are kept constant for the milling of alloy 2014-T6. Since it is difficult to obtain the residual stresses of a machined surface according to the response surface design requirement for a variety of cases, this is also excluded from the model; therefore, only the quantitative parameters - cutting conditions and tool geometries - are considered in the present work.

In order to determine the independent, interactive and higher-order effects of the different variables on the residual stresses, a general form of polynomials that can be adopted to represent the response surface function is the second-order polynomial [16]:

5 5 5 5

a = bo + E bixi + E bi,x{ + ~" E b,~xixj + e, (1) i = 1 i - 1 i = l j = l

i< j

where xl , x2, x3, x4 and x5 represent the cutting speed, feed, cutting depth, flank- width and nose radius of the cutting tool, respectively; x 2, the quadratic effects of these variables; xixj, the interaction between them; bo, bi, b~, b~j, the coefficient parameters; and e the experimental error. The coefficient parameters are estimated by the method of least squares.

Table 1 Coding of milling parameters

Parameter Symbol Levels

- 3 l 0 2 3

Cutting speed (m/min) Xl 31.42 62.8 125.7 157.1 Feed (mm/edge) X2 0.03 0.05 0.1 0.15 Cutting depth (ram) X3 0.4 1 2.5 4 Flank wear (mm) X4 0.01 0.05 0.1 0.2 Tool nose radius (ram) X5 0.1 0.2 0.4 0.8

235.6 0.2 6 0.3 1.2

90 K.-H. Fuh, C.-F. Wu/Journal of Materials Processing Technology 51 (1995) 87 105

3. Experimental design and analysis

An e x p e r i m e n t a l de s ign for the f i t t ing o f a s e c o n d - o r d e r m o d e l m u s t h a v e at leas t

t h r e e levels o f e a c h f ac to r so t h a t t he m o d e l p a r a m e t e r s c a n be e s t i m a t e d ; f u r t h e r m o r e ,

it is n e c e s s a r y to i n v e s t i g a t e the effect o f the mi l l ing p r o c e s s p a r a m e t e r s ( cu t t ing

c o n d i t i o n s a n d too l g e o m e t r i e s ) u sed in th is w o r k a n d of the i r i n t e r a c t i o n s . T h e r e f o r e ,

a m o r e s imp le a n d a d e q u a t e e x p e r i m e n t a l des ign , r e s p o n s e sur face m e t h o d o l o g y

( R S M ) w i t h the T a k u s h i m e t h o d [17,18] , is f o u n d to be a su i t ab l e t e c h n i q u e for th is

Table 2 Experimental design matrix and residual stress

Wear Nose Cutting speed Feed Depth (mm) Residual stress (mm) (mm) (m/rain) (ram/edge) (MPa)

1 0.05 0.2 62.8 0.05 1 18.40 2 0.05 0.2 62.8 0.15 4 53.36 3 0.05 0.2 157.8 0.05 4 10.97 4 0.05 0.2 157.8 0.15 1 22.75 5 0.05 0.8 62.8 0.05 4 7.90 6 0.05 0.8 62.8 0.15 1 60.87 7 0.05 0.8 157.08 0.05 1 6.50 8 0.05 0.8 157.08 0.15 4 0.65 9 0.2 0.2 62.8 0.05 4 10.24

10 0.2 0.2 62.8 0.15 1 2.57 11 0.2 0.2 157.08 0.05 1 0.22 12 0.2 0.2 157.08 0.15 4 32.63 13 0.2 0.8 62.8 0.05 1 6.61 14 0.2 0.8 62.8 0.15 4 18.16 15 0.2 0.8 157.08 0.05 4 83.79 16 0.2 0.8 157.08 0.15 1 92.07 17 0.01 0.4 125.66 0.1 2.5 9.77 18 0.3 0.4 125.66 0.1 2.5 110.65 19 0.1 0.1 125.66 0.1 2.5 11.34 20 0.1 1.2 125.66 0.1 2.5 19.90 21 0.1 0.4 31.42 0.1 2.5 103.72 22 0.1 0.4 235.6 0.1 2.5 78.28 23 0.1 0.4 125.66 0.03 2.5 10.51 24 0.1 0.4 125.66 0.2 2.5 32.21 25 0.1 0.4 125.66 0.1 0.4 100.00 26 0.1 0.4 125.66 0.1 6 21.92 27 0.1 0.4 125.66 0.1 2.5 31.55 28 0.1 0.4 125.66 0.1 2.5 20.59 29 0.1 0.4 125.66 0.1 2.5 14.56 30 0.1 0.4 125.66 0.1 2.5 25.51 31 0.1 0.4 125.66 0.1 2.5 39.34 32 0.1 0.4 125.66 0.1 2.5 22.23 33 0.1 0.4 125.66 0.1 2.5 26.98 34 0.1 0.4 125.66 0.1 2.5 54.56 35 0.1 0.4 125.66 0.1 2.5 64.26 36 0.1 0.4 125.66 0.1 2.5 41.47

IC-H. Fuh, C-F. Wu/Journal of Materials Processing Technology 51 (1995) 87 105 91

study. In the latter, each parameter has five levels selected from practical industry, as shown in Table 1, and a central composite rotatable design with an orthogonal table (as shown in Table 2) is used. The variance analysis is calculated by SAS package software to determine the significance of the parameters, and the t-test is used to determine which factors are significant. The F-ratio test is conducted to check the adequacy of the model proposed.

4. Experimental procedures

The process intends to build the mathematical model to check the parameters affected by residual stresses in terms of the measurement of residual stresses, cutting forces, temperature rise and hardness variation.

In the present investigation, 2014 aluminum alloy is adopted as the workpiece material because of its high sensitivity to deformation during machining. The workpiece material with HRB value between 85 and 89 (HV value between 164 and 180) is solution treated and aged for 18 h. Each workpiece is machined as a rectangular plate of dimensions 260 mm × 260 mm x 17 mm and is clamped onto a dynamometer which in turn is fixed onto the table of a CNC milling machine.

An IGTALLOY FMS end-milling cutter of 25 mm diameter was used to perform in the series of milling experiments. The cutting-tool tips were turning to the desired value of flank wear and tool nose radius, the geometries being examined before the set-up of the cutter.

Many methods are widely used for the measurement of residual stresses, such as X-ray diffraction, the hole-drilling method and other destructive methods. The X-ray method can give accurate measurement of the residual stresses on the surface but it is not able to provide the distribution of the residual stresses of over the depth; also, destructive methods are inadequate because the specimen must be sectioned and can not be used again. Thus, the adopt hole-drilling method is adopted, the latter being a widely-employed technique for determining the residual stresses near to the surface of a material. The procedure involves measuring the change in strains produced by the hole; the quantities measured then being related to the residual stresses present in the material before drilling. Although the method can be considered semi-destructive, the size of the hole is so small that the structural integrity of the part is not affected significantly.

The residual stresses are meaured by precision rosette strain gauges (TEA-13- 062RK-120) drilled with the RS-200 SYSTEM and recorded by a SYSTEM 4000 analyzer. According to ASTM standard E837-85 [19], the residual stresses by the blind-hole drilling method can be expressed as

_ _ _ _ ~ 2 0"1 "[- (~1 - - /~2) 2 -']- (/~2 3) , (2) 4A

o'2 -- 4 ~ ~ N / ( 1 - - ~2) 2 -[- (t32 - - /~3) 2, (3)

92 K.-H. Fuh, C.-F. Wu/Journal o f Materials Processing Technology 51 (1995) 87 105

- 7 5

- 1 0 0 0 . 0

,

t o o

75

25

C~ 0

- 2 5

- 5 0

0.'4 O.J8 1.2 1.16 2.0 Depth (n'trr 0

Fig. 1. Residual-stress distribution in the surface region.

81 - - 2~2 + ~3 (4) tan 2fi --

E3 ~1

l + v /~ . . . . . ~, (5)

2E

1 /~ . . . . ~. (6)

2 E

In order to determine the direction of cq, a cri terion for angle fi is shown as below: 1. if ~3 > ~:1, fi represents the angle between O'ma x and gauge 1; 2. if ~.3 < ~h, fi represents the angle between amln and gauge 1; or 3. i fc 3 = e l f i = _ + 4 5 ° ; f l = + 4 5 c ' w h e n c 2 < e l , o r f l = - 4 5 w h e n ~ : 2 > c l .

The strain relief measured by RS-200 System is subst i tuted into Eqs. (2) and (3) to calculate the residual stresses whilst the values calculated f rom Eqs. (2) and (3) is the average stresses f rom surfrace points to the measured depths. The trend of residual stresses as a function of depth is shown in Fig. I. Nikola [20] p roposed the equal weight solut ion (EWS) me thod to determine the actual residual stress at each depth, which me thod gives

1 aa._ = [a.Z. a . 1 x Z. 1] AZ" (7)

After the milling process the residual stresses of the workpiece are tensile and increase to m a x i m u m value with an increase in depth, after which they decrease to compress ive

K.-H. Fuh, C-F. Wu/Journal o f Materials Processing Technology 51 0995) 87 105 93

F~ ~] ] ~ rMS)jr~. FF]]] I Workp iece / f A" \ "A"

Dynarr~o77zeter

K i s t l e r 9255A

"A" Thermal Electrzc Couple (K-Type)

KEITHLEY 556 GPIB Data MEASUREMENT AND PC CONTROL SYSTEM - - (Temperature /EEE 488 Recorder) I

l

Fx Fy ! Fz Fx

0 Data 7ape Recorder ~ i p T e c ~ s i o n 61oo 1

Forrt~analyzeT J

Fig. 2. Schematic diagram of the measurement system for rise in temperature and cutting force.

with further increase in depth. After a depth of 0.5 mm, the residual stresses approach a steady value.

The peak values of the principal stress calculated from Eq. (7) is substituted into the following equation, which latter is based on plane-stress theory, to find the specific residual stress.

S = X/(°1 0"2) 2

2 (8)

The peak-to-peak cutting forces Fx, Fy and F~, were measured by dynamometer (Kistler 9255A), and a thermal couple embedded in the workpiece was utilized for measuring the rise in temperature AT at 0.3 mm beneath the finished surface. The meaurement systems are set up as shown in Fig. 2.

The hardness and the microstructure of the milled workpieces are investigated to determine the effects of microstructure variation of the surface and the sub-surface. Metallographic samples were taken from the milled workpiece, ground, polished and then etched to reveal the microstructural features. The variation of hardness was determined from Vickers microhardness measurements, the load used for microhard- hess testing being 50 g. Measurements were taken at three different points measured and compared with those for the original material.

5. Presentation of results

The effect of the various parameters - - including the cutting conditions and the tool geometries-- on the residual stresses is seen readily, and a model has been derived


Table 3 Values of coefficient and the computed t-test of the response surface model for the evaluation of residual stress

Regression Standard t-value Parameter coefficient error

bo ~ 44.011 81.798 0.54 bl : 1.577 0.623 - 2 . 5 3 X~ b 2 = 1819.639 678.824 2.68 X~ b3=8 .638 20.527 0.42 X3 b 4 = - 9 0 4 . 4 6 412.13 2.19 X~ b5=76.341 105.568 0.72 X5 b~ =0 .004 0.002 2.00 X~ hv ~ 4752.106 2237.322 - 2 . 1 2 X~* bs = 0.014 2.086 --0.01 X~ b9~569 .599 882.858 0.65 X~ blo = - 120.132 58.586 - 2 . 0 5 X~* b~ = 1.453 2.659 - 0 . 5 5 X~ *X2 b12 - 0.004 0.089 - 0 . 0 4 X1 *X3 bl 3 - 5.662 1.746 3.24 X i * X~ h~4 = 0.557 0.438 1.27 Xt * X s bL 5 = -- 132.433 84.747 1.56 X2 * X3 b~6 = - 1300.646 1674.638 0.78 X z * X 4 b~7 = 19.672 418.659 0.05 X2 *X5 his - 70.548 55.83 1.26 X3 *X~ b19 = - 15.113 13.958 - 1.08 X~* X 5 b2o = 389.174 276.558 1.41 X4 *Xs

Significant, t0.os, 30 = s tandard critical value = 2.042.

Table 4 Analysis of variation (F-test)

Source Sum ofsquares Degree of f reedom Mean square F value

Model 27000.637 20 1350.032 2.089 Error 9659.768 15 646.385 Total 36660.405 35

The standard value of the F-ratio for the significant level ct = 0.10 and degrees of freedom 20 and 15 is Fo.lo (20, 15) - 1.92.

b y R S M w i t h a n o r t h o g o n a l t a b l e . A n a m o u n t o f d a t a h a s b e e n g e n e r a t e d , p r e s e n t e d

in t h e f o l l o w i n g .

F ig . 1 s h o w s t h a t t h e r e s i d u a l s t r e s s o f t h e m a c h i n e d s u r f a c e a r e l o w t e n s i l e b u t

i n c r e a s e r a p i d l y t o a m a x i m u m t e n s i l e s t r e s s , a n d t h e n d e c r e a s e t o a c o m p r e s s i v e s t r e s s

w i t h i n c r e a s i n g d e p t h b e n e a t h t h e m a c h i n e d s u r f a c e .

T a b l e 2 s h o w s t h e r e s u l t s o f t h e t h i r t y - s i x e x p e r i m e n t s c a r r i e d o u t in t h i s r e s e a r c h .

U s i n g S A S p a c k a g e s o f t w a r e fo r a n a l y s i s , t h e r e s u l t s o f t h e r e s i d u a l s t r e s s e s a r e

K.-H. Fuh, C.-F. Wu/Journal o f Materials Processing Technology 51 (1995) 87-105 95

~140

~ tO0 t~

• ~ 60

~ 2.0

Feed = 0.1 r a m / e d g e F lank Wear = 0.01 m m Cut t ing Depth = 2.5 m m Tool nose r a d i u s = 0.4 m m

o o o o o E x p e r i m e n t a l Resul ts

°'~'~ o j f

_ _ J

i i I ~ i

-Z~o 70 t to tso 19o z~o C u t t i n g S p e e d ( m / r a i n )

Fig. 3. Comparison of predicted and experimental results for various cutting speeds.

presented in Table 3, which shows that the cutting speed, the feed, the tool nose radius and the flank wear influence the residual stresses significantly. The values of coefficients of the proposed model are presented also in this Table. The model for residual stresses is tested by variance analyses (F-test), as shown in Table 4, experimental verifications also being performed, the results being shown in Fig. 3.

In this model by the RMS method, the relationship between the residual stresses and the significant variations are shown in Figs. 4 6.

The variation of the residual stresses with feed is shown in Fig. 4. In the environ- ment below 0.1 mm/edge, as the feed increases, so do the residual stresses. However, the tendency is reversed when feed is above 0.1 mm/edge.

Fig. 5 presents the effect of the flank wear on the peak residual stresses at various cutting speeds, showing an interaction between these two parameters. At low cutting speeds (up to a value of about 100 m/min) an increase in flank wear causes a reduction of the tensile residual stress for a given cutting speed. At high cutting speeds contrar- ily, an increase in flank wear results in an increase in tensile residual stress.

Fig. 6 also shows the effect of cutting speed with different tool nose radii on the residual stresses of the machined surface, from which figure there is seen to be a general trend of an increase in tool nose radius leading to an increase in the residual stress at a given cutting speed. However, a tool nose radius which is above 0.8 mm gives results that do not agree with the tendency: the residual stress is smaller at low cutting speed but the tensile stress increase rapidly at high cutting speed.

6 K.-H. Fuh, C.-F. Wu/Journal o f Materials Processing Technology. 5l (1995) 87 105

tO0 . . . . . . . . . . . . . . . . . . /

o / / C u t t i n g D e p t h = , . .5 m m / t / . . ~ . 8 0 ~ F l a n k W e a r = 0.1 m m / ~ ' / / / ~ \ \ Too l N o s e R a d i u s = 0.4 m m / / /

i ~ - ~ f = ~ . 2 / 7 /

-'.% ;o ,',o ,~o ,;o - - ~ . o C u t t i n g S p e e d ( m / r a i n )

Fig. 4. Effect of cutting speed on the residual stress for various feeds (mm/edge).

300

t~ c~

2 6 0

2 2 0

180

/ F e e d = 0.1 m m / e d g e C u t t i n g D e p t h = 2 .5 m m / Tool N o s e R a d i u s = 0 .4 m m

. / W=0.3 / / "

N / / / "

f 40 ' / " / j .

• s "

tO0-... " - . / " . W=0.1 -"

60- -'-'----._ "-~2_~ ~ . ~ " i1-1"-- / j l

, o ) _ z . ?o .o , _ 2 0 c , , h , L

30 70 I I 0 150 190 2 3 0 C u t t i n g S p e e d ( m / r r t i n )

F'ig. 5. Effect of cutting speed on the residual stress for various values of flank wear (r

K.-H. Fuh, C.-F. Wu/Journal of Materials Processing Technology 51 (1995) 87 105 97

,zo f

oot |

80t oo

6 0 t

? 40i

,.~ 2O

a~ o

- 2 ~ 30 Jo

.

r:02> / /

\ .2

i I , I I

1 I 0 150 190 2 3 0 Cutting Xpeed (rn/rrtirt)

Fig. 6. Effect of cutting speed on the residual stress for various tool nose radii (mm).

Y

t

10oo

800

600

,408}

0

• F x l • F y • • Fz

Ir V ± T ,, 8"

t ~ : S p e e d = 1 2 5 6 m, i n i ~ ~ D ~ l > t h = : 3 2 llln~

N o s c R a d i t l s = 0 /3 mr?q [[ • ~ ' l ank W e a r = O m m

3 0

£

( ;

I i

F e e d {tut t i ed£~ + )

Fig. 7. Effect of feed upon rise in temperature (AT) and cutting force.

In order to explain the residual-stress tendency, the cutting force and temperature rise in relation to the cutting conditions and tool geometries are shown in Figs. 7-10.

6. Discussion

A predictive model of residual stress, affected by cutting conditions and tool geometries, has been employed for the purposes of predicting and improving the value


v

o

8

(} 0

i ) i ;

(;

S p e e d : 1~5 6 I u . l u l n F e e d () ] rurrl tiM, c l ) e p l h = 3 ~ m m I ' l a n k Woal 0 i rut~

• : :: : m . | •

v •

• • F x

• 1

, i , '

I 'o~l N o ~ , 14adius (u !~n)

0 -; 2

Fig. 8. Effect of tool nose radius upon rise in temperature (AT) and cutting force

_2

) ( , ( )

%( )~ ;

( ) ! )

,)

F e e d 0 I m u l eM~e D e p l h ~ 2 I n n l Tool N o s e [4adiu~ 0 a I /Ira ~']al114 Wf,,t 1" 0 ll]l]l

• } , x • • / , v

• t,'x • v , / I

I

C u l t i r l ~ ~[>eed { ] r l r l l i n )

Z ̧

Fig. 9. Effect of cutting speed upon rise in temperature (AT) and cutting force.

Z

c b.

1 ) , ,

?',), D t ' p t h = t 3 I~][11

• ! ~i( ;,' :, m : |

4 1 ,'~) • • • [ ; x

• F v

• F z

• T

i I 1 i

}"],lll]( ~,/'41 ( I t l l t ' )

~ p e e d I ] 5 6 m " m i n F e ~ d = O I l l ] l ] l , , e d g e Tool No-~ RadiLis 8 ,t [ [ l l l ]

C, c~

' ]

Fig. 10. Effect of flank wear upon rise in temperature (AT) and cutting force.


Prima ry Deformation I~: ;£~L~{~I \ Zone ~ ~ o n ~

~stic-Plastic~----~Third / Dean Zo.e Defomat~n

~ Path2 Material Flow

Fig. 11. The deformation mechanism at the tool-workpiece in the cutting process.

of residual stresses by controlling the cutting parameters. However, the results of this model provide no satisfactory explanation for all of the phenomena of residual stress. Consequently, the mechanism of metal cutting and some relaxed experiments are used to elucidate the phenomena of the residual stress.

The geometry of tool-chip contact in the cutting process can be seen in Fig. 11, and is noted to be divided into three regions [5,21]. From these regions, it is found that the residual stress is influenced more by the first region and the third region simultaneously, because these two regions mainly produce the mechanical load and conduct the heat to the finished surface. Moreover, according to the results of investigations done in the past [4, 5, 9, 10], the residual stress can be attributed mainly to the variations in microstructure and to the mechanical and thermal loads on the workpiece. However, from the hardness tests, HV values of between 172 and 216 (as shown in Appendix A) are obtained, compared with the original hardness of HV = 164~180, and the microstructure, as shown in Fig. 12, is characterized by the variations being small. Okushima and Kakino [-6] have proposed that the tensile residual stress is caused by thermal load and the compressive residual stress by mechanical load. Chou [5] also felt that the tensile residual stress is affected by thermal load, but with the mechanical load resulting in tensile or compressive residual stress as determined by elastic deformation in the sub-surface. However, from Fig. 13, it is shown that the grain size of the sub-surface is lengthened by the mechanical load, although not prominently so. Furthermore, the general tendency of the residual stress is in agreement with the rise in temperature AT at the central cutting condition, as shown in Figs. 7 10. Thus, the principle factor which affects the residual stresses is the thermal loads.

In this study, the general distributed tendency of the residual stresses measured by the hole-drill method agrees with that of E1-Khabeery [3] and Mishra [8] investigated by means of the electrolytic etching method and F.E.M., respectively. According to numerical analysis of a moving heat source [8], simulating the cutting conditions without lubricant, the maximum residual stress is presented on the surface. However, in practical measurement the maximum value exists at the sub-surface, the surface

100 K.-H. Fuh, C.-F. Wu/Journal ~?f Materials Processing Technolo~, 51 (1995) 87 105

Fig. 12. Mic ros t ruc tu re of the mach ined surface for 2014 a l u m i n u m al loy (400 x ) (cut t ing depth = 3 mm: f lank wear - 0.1 ram; feed = 0.1 mm/edge : cu t t ing speed = 125.7 m/min; and tool nose radius = 0.4 mm).

Fig. 13. As for Fig. 12 but for a feed of 0.2 mm/edge (100 x ).

being affected deleteriously, as shown in Fig. 12. Thus, the residual stress of a machined surface is reduced abnormally, it may produce a poor surface roughness. When the thermocouples are located beneath the finished surface at depths of 0.5 and 0.7 mm, for the same cutting conditions AT are 12.55cC and 11.79<-(7 respectively: the difference of these temperatures is minute. Therefore, the distribution of the tensile stress is shallow; and when the depth is greater than 0.5 ram, the distribution of the residual stress remains steadily compressive.

In accordance with the model of the moving heat source adopted in [8], with a greater feed a greater residual stress is created on the workpiece because of the greater heat flux. From Fig. 7, the rise in temperature decreases with increase in feed, because the table speed increases, whilst keeping a constant cutting speed. Thus, a greater feed will induce large but shallow residual stresses. However, the surface roughness increases in relation to the increase of feed, as shown in Fig. 14 of Appendix B. Hence, for the feed greater than 0.1 ram/edge, the residual stress decreases.


According to Young and Oxley [12], the mechanical load increases with increase of the tool nose radius. Despite the component Fz also increasing in the milling process, as shown in Fig. 8, the mechanical load compared with thermal load is still not significant. From Figs. 4-10, it is found that the tendency of the thermal load and the residual stress is coincident without considering the surface roughness at the central cutting condition. The values of the residual stresses decrease suddenly when the tool nose radius is 1.2 mm with a low cutting speed, because the surface roughness is poor for this cutting condition (see Fig. 15 of Appendix B).

At smaller flank width with increased cutting speed, the peak residual stress decreases, because the thermal load decreases, as shown in Fig. 9. However, when the rise in temperature, AT, is 12.90°C and 15.69°C, with flank wear 0.1 mm, feed 0.1 mm/edge, tool nose radius 0.4 mm and cutting depth 3.2 mm, the cutting speed increases from 125.6 to 188.4 m/min, respectively. There is a significant interaction found between the cutting speed and the flank width by the t-test; this reveals that an increase in cutting speed with a greater flank width induces a higher tensile stress because thermal load increase rapidly, not the mechanical load.

7. Conclusions

The milling process is quite complicated, and many factors affect the integrity of the surface and the sub-surface. How to find the optimum cutting conditions and how to control the residual stresses are very important for industry. According to this investigation, some of the results can be summarized as follows:

80

~ 6o

f, ~ 4 o Q

J

s o 7o

Fig. 14.

C u t t i n g D e p t h = 2 .5 m m F l a n k Wear = 0.1 m m Tool Nose R a d i u s = 0 .4 m m

f = 0 . 1 5

f=O. l

f=O.05

f=O.03

i i i i

110 150 190 2 3 0 Cu~ing Speed ( m / r a i n )

Effect of cut t ing speed on surface roughness for var ious feeds (ram).


80

~6o co

~ 2o

o,

-2(30 7~0

Cut t ing Depth -- 2.5 m m Flank Wear = 0.1 m m Feed = 0.1 m m / e d g e

r=0.1

r=0 .2

r = l . 2

r--0.4

r=0 .8

I i I I

110 150 190 230 C u t t i n g S p e e d

Fig. 15. Effect of cutting speed on surface roughness for various tool nose radii (mm).

(1) A good correlation between the experimental and predicted results derived from the model is exhibited in this research. Thus, using the proposed procedure, the opt imum cuttings conditions for the tool geometries should be obtained to control the residual stress of other metals also.

(2) It is shown that the cutting speed, feed, tool nose radius and flank wear have the most significant effect on the residual stresses and that there is an interaction between the cutting speed and the flank wear.

(3) The residual stresses generated in the end-milling cutting processes without lubricant are tensile on the machined surface and increase rapidly to a maximum value beneath the surface, thereafter decreasing with further increase in depth to reach a steady value.

(4) The principle factor which affects the residual stress is the thermal loads, and there is insignificant variation of the hardness and the microstructure of the 2014 aluminum as a result of end milling.

(5) A large feed will generally induce large and shallow residual stresses (see Fig. 4) but produce a poor surface roughness (see Fig. 14 of Appendix B): thus, the residual stresses decrease when the feed is large (0.15 and 0.2 mm/edge).

(6) From Fig. 6, a large tool radius (r = 0.12 ram) with a low cutting speed can reduce the residual stresses. However, this will induce poor surface roughness (see Fig. 15 of Appendix B) and thus should be avoided.


References

[1] E.C. Reed and J.A. Viens, Trans. ASME J. Eng. Ind., 60 (1960) 76. [2] J.A. Bailey, S. Jeelani and S.E. Becker, Surface integrity in machining AISI 4340 Steel, ASME J. Eng.

Ind., 98 (August 1976) 1007. I-3] M.E. E1-Khabeery and M. Fattouh, Residual stress distribution caused by milling, Int. J. Mach. Tools

Manufact., 29(3) (1989) 391 401. [4] K.H. Fuh, C.F. Wu, H.M. Lin and H. Juan, The residual stress caused by end milling of aluminum

alloy, Proc. 9th National Conf. of the Chinese Society of Mechanical Engineers, Kaohsiung, Taiwan, 1992.

1-5] C.H. Chou, Metal Cutting Principles, Shanghai, 1984, p. 120. I-6] K. Okushima and Y. Kakino, The residual stress produced by metal cutting, Ann. CIRP, 21 (1) (1971)

13-14. I-7] C.R. Liu and M.M. Barash, The mechanical state of the sublayer of a surface generated by chip

removal process, Part 1: Cutting with a sharp tool, ASME J. Eng. lnd., 98(4) (1976) 1192-1201. 1-8] A. Mishra and T. Prasad, Residual stresses due to a moving heat source, lnt. J. Mech. Sci., 27(9) (1985)

571-581. [-9] W. Wu and Y. Matsumoto, The effect of hardness on residual stresses in orthogonal machining of

AISI 4340 steel, ASME J. Eng. Ind., 112 (August 1990) 245 252. 1-10] Y. Matsumoto, M.M. Barash and C.R. Liu, Effect of hardness on the surface integrity of AISI 4340

steel, ASME J. Eng. Ind., 108 (August 1986) 169 175. [11] S.L. Den, Effect of flank wear on the stress of workpiece, Mater Theories, Taipei, 1986. [12] H.T. Young, P. Mathew and P.L.B. Oxley, Allowing for nose radius effects in predicting the chip

direction and cutting forces in bar turing, Proc. Instn. Mech. Engrs., 201(C3) (1987) 213-226. [13] A.B. Sadat and J.A. Bailey, Residual stress distribution in machining an annealed bearing bronze, Int.

J. Mech. Sci., 27(11/22) (1985) 717-724. [14] M.A. Ei Baradie, Surface roughness model for turning gray cast iron (154 BHN), Proc. Instn. Mech.

Engrs., 207 (1993) 43-54. [15] K.K. Padmanabhan and A.S.R. Murty, Evaluation of friction damping by response surface methodo-

logy, Int. J. Mach. Tools Manufact., 31(1) (1991) 95-105. [16] G.E. Boxand and J.S. Hunter, Ann. Math. Star., 28 (1957) 195. [17] D.C. Montgomery, Design and Analysis of Experiments, New York, 1984. [18] Takushi and Y.Y. Wu, Orthogonal Table and Line-Point Figures, Taipei, 1970. [19] Determining Residual Stresses by the Hole-drilling Strain-Gage Method, A S T M Standard E837. [20] W.E. Nikola, Practical subsurface residual stress evaluation by the hole-drilling method, Proc. SEM

Spring. Conf. on Exp. Mech., June 1986. [21] M.C. Shaw, Metal Cutting Principles, Clarendon Press, Oxford, 1984, 18 21.

Appendix A

Experimental results of surface roughness and hardness

E x p t . N o . S u r f a c e H a r d n e s s

r o u g h n e s s ( H V )

1 15.12 199.5

2 35.98 197.4

3 8.1 192.6

4 43 .67 208.1

5 4.75 195.8


6 9.45 185.2 7 3.2 212.2 8 12.15 197.5 9 8.13 205.6 10 29.42 206.6 11 4.17 216 12 44.5 196.8 13 3.4 183 14 8.23 215.2 15 5.83 215.5 16 8.45 198.3 17 8.73 177.4 18 12.06 187.1 19 72.33 211.4 20 5.76 171.6 21 9.26 184 22 8.16 195.5 23 2.95 186.5 24 24.2 182.8 25 5.06 193.6 26 16.56 188.1 27 9.73 203.9 28 10.1 203.4 29 11.5 200.1 30 9.6 189.9 31 9 196.5 32 11.54 197.8 33 10.83 192.3 34 12.01 185.4 35 11.57 202.3 36 8.95 202.4

Appendix B

The second-order polynomial of surface roughness (R), determined by the regrcs sion coefficients of the Appendix A experimental data, is

R : 33.576 -- 0.020Xl + 255.004x2 -- 4.164x3 -- 152.068x~ 88.675x5

- 0.002x~ -- 164.787x~ + 0.185x~ + 72.10x~ + 88.121x~

+ 0.777xlx2 + 0.013xlx3 + 0.301xlx4 -- O.122xlx5 + 7.458x2x3

+ 92.518XzX4 -- 376.620x2x5 + 15.935x3x4 - O.125x3x5 + 88.139x~xs,

K.-H. Fuh, C.-F. Wu/Journal of Materials Processing Technology 51 (1995) 87 105 105

where xl , x2, x3, x4 and x5 represent cutting speed, feed, cutting depth, flank wear and tool nose radius, respectively. The F-value of this model is 2.209 (Fo.o5(20, 15) = 2.33). According to the surface-roughness model, the tendency of significant factors (feed and tool nose radius) can be found in following figures.

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