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MACHINING CONDITIONS OF HIGH PRESSURE SURFACEQUENCHED SABIC STRUCTURAL STEEL

Mahmoud S. Soliman1, Abdul-Rahman M. Al-Ahmari2, and Saied M. Darwish3 1. Professor, Mechanical Engineering Department, King Saud University, P.O. Box 800, Riyadh 11421, [email protected] 2. Associate Professor, 3. Professor, Industrial Engineering Department, King Saud University, P.O. Box 800, Riyadh 11421

ABSTRACT SABIC Hadeed Company in Saudi Arabia has introduced a new technology (bar quenching) to its rolling mills in Jubail, for the manufacture of superior quality concrete reinforcing bars. This technology uses the state of the art process involving high pressure surface quenching followed by self-tempering. As the bars emerge from the last rolling stand, the surface temperature is rapidly reduced by high-pressure water jets. This action causes change in the structure, making it harder and stronger. The production of this type of bars is so large that it has been decided to market it for some other purposes such as machining. Since no or little machining data are available for cutting SABIC structural steel, a machining database for SABIC structural steel is to be established. Also, the machining parameters of SABIC structural steels are to be optimized to enhance machinability. KEYWORDS SABIC structural steel, Machinability, Surface roughness, Cutting force, Hardness 1- INTRODUCTION The optimization of machining operations has been and continues to be a topic of interest to many practitioners in the metal cutting industry. As a result, countless system metrics and indices have been developed in an attempt to offer very much needed insight about the materials, cutting conditions and system attributes selected for an operation [1-7]. Machinability ratings are often descriptive system metrics. These ratings, sometimes called indices, attempt to quantitatively denote the relative ease with which a material (usually a metal) can be machined when using standard tooling and cutting conditions. Various criteria are used to evaluate machinability, some of which include the following: tool life, cutting forces and power requirements, surface finish, dimensional control, metal removal rate and chip control.

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Low-carbon steel or mild steel are often used to indicate carbon content of less than 0.25%. The structure of these steels is composed of ferrite and pearlite. Cold working can strengthen low carbon steel, but minor strengthening is possible by heat treatment. Such steels are used primarily in structural applications (bridges and buildings) and hence the term structural steel such as A36 was given according to ASTM standards. The chemical composition of these steels is in the range: 0.18-0.25% C, 0.6-1.25% Mn, 0.035% P, 0.04% S and 0.15-0.35% Si. Although moderate in yield strength and tensile strength, these steels have proper combination of strength, ductility, toughness and weldability to perform satisfactorily in structural application. Typical values for yield strength, tensile strength and ductility in A36 steel are 310, 450 MPa and 28% (in 50 mm gage length), respectively. The Vickers hardness HV for this steel can be estimated using the relationship between Vickers hardness HV and tensile strengthσu, which is usually expressed as [8] HV = 3σ

(1)

u

where HV is in MPa ( divide by 9.825 to convert to conventional hardness units kg/mm2). The calculated value for HV is 137, agrees very well with the tabulated value of hardness for hot rolled structural steels. The structural steels produced by SABIC in the form of reinforced bars, are usually quenched in water after hot deformation in the austenite region. Because of low hardenability (low carbon content ≤ 0.25) minor hardening is taking place; small fraction of austenite is transformed to martensite plus fine structure of ferrite and pearlite. Since no or little machining data are available for cutting SABIC structural steel, so the aim of the present work is to optimize the machining parameters of SABIC structural steels in order to enhance its machinability 2. EXPERIMENTAL WORK 2.1 Microstructure of SABIC Structural Steel The microstructures of the reinforced rods are shown in Figures 1 and 2. These figures suggest that the microstructure consists of ferrite and pearlite. It is possible that some martensite is formed on the surface of the specimens. In addition, the microstructure on the surface is finer than that in the center of the rod (Figure 2a). This microstructure reflects the high strength observed in reinforced bars produced by SABIC Hadeed Company. 2.2 Mechanical properties measurements Vickers hardness and tensile strength were measured for two bars of 12-mm and 16-mm diameters. The Vickers hardness was measured using diamond pyramid as indenter at 10 or 20 kg load, taking the average of the two diagonals for the indentation and reading the corresponding value of the hardness from the tables. The tensile strength was measured using an Instron machine operating at constant cross-head speed of 10 mm/min.

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Figure 1. Microstructure of ferrite and pearlite in 12mm diameter rod.

. (a)

(b) Figure 2. Microstructure of ferrite and pearlite; (a) in the center of 16mm diameter rod, (b) in the periphery of 14mm diameter rod. The load-displacement curve was monitored using strip chart recorder. The load was measured using 100 kN-load cell. The average cross-section area, A was determined by weighing a specified length of the rods and finding the volume using the tabulated value for the density of structural steel (7.86x103 kg/m3). The calculations are given in Table1. The measured value for ultimate load Pu is also, included in the Table 1. Proceedings of the 7th Saudi Engineering Conference (SEC7)

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Table1. Dimensions of Tested Specimens (12mm-diam. rod) and their ultimate strength Sample Length, m Weight, Volume, A, m2 Pu, kN σu, MPa kg m3 1 0.299 0.257 3.3x10-5 1.1x10-4 76.5 695 2 0.199 0.165 2.1x10-5 1.1x10-4 78.2 711 The ductility (elongation percent) determined for specimen 2 is 26% in 100 mm. This value is comparable to that determined for A36 structural steel in specimens with 50 mm gage length. SABIC Structural steel has the advantage of high strength with moderate ductility as compared to ASTM standard steels. The ductility measurements require further investigation. The mechanical properties, HV and σu are listed in Table 2. The data for 12-mm bar is satisfying the relationship represented by Eq. 1, i.e., when the value of HV (MPa) in the center is divided by σu, gives a value of 2.9. Therefore, the ultimate strength in 16-mm bar was estimated using Eq. (1). Table 2. Mechanical properties of reinforced bars Rod diameter., mm HV(Surface) HV(Center) σu, MPa kg/mm2 kg/mm2 12 291 207 703 16 263 179 586* * estimated using the relation between HV andσu. 3. MACHINING SET-UP OF THE PRESENT WORK The experimental set-up used throughout the present work includes the following: 1- A 3-component Kistler dynamometer model (9257 B). 2- Multi channel Kistler amplifier model (5019 B). 3- Data acquisition card set-up (DAS 1602/12). 4- Dynoware software set-up (version 2825 A-12). 3.1 Work piece Materials The material used throughout this work was a SABIC structural steel (0.25% C, 0.61.25% Mn, 0.035% P, 0.04% S and 0.15-0.35% Si. The work pieces were in the form of cylinders 12 and 16 mm in diameter and 150 mm in length. 3.2 Tool material The cutting inserts used throughout the present work were carbide (triangular and diamond shape) tool bit inserts. In order to eliminate the effect of tool angles on the test results, a fresh identical cutting insert was used to conduct each cutting test condition. 3.3 Cutting force measurements A three-component 9257A Kistler dynamometer with special tool holder, connected to a 5001 three channel Kistler charge amplifier was used for measuring the cutting force components of the present work. It is worth noting that before running the cutting test,

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the Kistler dynamometer was calibrated on an Instron testing machine using a dummy tool, where the gain of the amplifier was adjusted at one volt for each one kN. 3.4 Surface roughness measurements The surface roughness was measured using the portable Suntronic-10 surface roughness meter. The center line average, Ra was taken to represent the particular test combination, and a cut-off value of 0.8 mm was used. Each cutting test was repeated four times. The average of the four readings was taken to represent the surface roughness of the particular test condition. It is worth mentioning that the work piece was not removed while measuring the surface roughness (in order to avoid the effect of different clamping on the test results) until all the cutting tests concerning a specific insert have been conducted. 3.5 Tool Flank Wear Measurements A Sptizenhope Carl – Ziess tool maker microscope was used for measuring the tool flank wear. Each cutting test was repeated four times, where the build-up of the tool flank wear was taken to represent the particular test condition. The workpiece was not removed until all the cutting tests concerning the specific insert have been conducted (in order to avoid the effect of different clamping on the test results). 4 CUTTING TEST PROCEDURE The process utilized was a turning operation, performed on a 10 kW SSSR (Russian made) engine lathe model 16K25. Cutting tests were conducted using carbide (triangular and diamond shape) identical tool bit inserts. Each test bar was placed between three jaws chuck and the tail stock of the lathe. The test bar was not removed until all different cutting tests concerning the specific tool bit insert have been conducted (in order to avoid the effect of different clamping on the test results). Table 3 shows the cutting conditions used. Table 3. The cutting conditions tested.

Level Factor Velocity, v (m/min) Feed Rate, f (mm/rev) Depth of cut, d (mm) Work piece Hardness, h

High Level

Low Level

(+)

(-)

50.9 0.08 1.5 232

20.6 0.04 0.6 200

5. FACTORIAL DESIGN AND DESIGN MATRIX Full factorial design consists of all possible combinations of the factors and their levels. In the present work a 2k factorial design is adopted, where each factor in the experiment is studied at only two levels. There are several reasons for emphasizing the 2k design, such as relatively few runs are required, the design is easy to use in sequential experimentation and the data can be processed using graphical methods. Also, when a large number of factors are studied, the fractions of 2k designs can be used to keep the experiment at reasonable size [9-11]. Table 4 contains a list of the test combinations of these factors. Proceedings of the 7th Saudi Engineering Conference (SEC7)

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6. STATISTICAL ANALYSIS OF RESULTS The design of experiments (DOE) capabilities are used to provide simultaneously an investigation of the effect of multiple variables of cutting process (depth of cut, feed, speed and material hardness) on the output variables (responses). Four types of experiments [9-11] are supposed to be carried out in this paper for cutting force, surface roughness, tool wear, and tool life. These types of experiments are called factorial experiments, because each machining conditions of major concern to the experimenter. The value of the factors (machining conditions) in these experiments is called levels. Thus we deal with models in which the four machining conditions (v, f, d, h) are studied within two levels of each factor. Experiments are carried out to investigate the effect of the four machining conditions on cutting force, tool wear and surface roughness. The data collected is shown in Table 4. 6.1 Postulation of the surface roughness and force models In this experiment, the four factors (v, f, d, h) are considered using factorial design to investigate their effect on the output (F and Ra). These experiments aim to study the general behavior of SABIC structural steel in machining. It is well known from the literature that the cuttings force, F and surface roughness, Ra is experimentally related by the cutting conditions as follows: F = C F v n1 f n2 d n3 h n4

(2)

Ra = C R v f d h

(3)

c1

c2

c3

c4

where CF and CR are constants depending on the cutting parameters. The above relationships can generally be expressed in a logarithmic form as follows: Ln F= ln CF + n1 ln v + n2 lnf + n3ln d+ n4lnh Ln Ra= ln CR + c1 ln v + c2ln f + c3 ln d + c4 lnh

(4) (5)

In the present preliminary experiments, each machining variables is given two levels coded (- and +), which represent low level and high level of the variable. 16 experiments were conducted during which the response variables (surface roughness and cutting force) were measured. The obtained results from the regression analysis are shown in Table 4 for Ra and Force, respectively. From the above results of regression analysis the equations of force and surface roughness can be written as follows: F = 3.62 × 10 5 v 0.001 f 0.738 d 0.638 h − 0.929

(6)

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Ra = 9.85 × 10 − 3 v − 0.181 f 0.969 d 0.555 h1.53 A sample of residual graphs is shown in Fig. 3.

(7)

6.2 analyses of the results The models are fitted to the data and graphs are generated to evaluate the effects of machining conditions on cutting forces and surface roughness. The results obtained from the fitted models and graphs are used to analyze which are important for reading the value of cutting force and surface roughness. In this section the Minitab results and illustrations provided by the software, to visualize the effects of machining conditions, are plotted and analyzed. Table 4. The implemented design matrix Factors Test

Cutting

Feed,

Depth

No.

Speed,

f

of cut,

Hardness

d

h

Fs

Ff

Fr

F

v

Ra

Cutting force

(µm)

1

-

-

-

-

56.99

10.04

117.37

130.86

2.2

2

+

-

-

-

137.14

18.78

131.51

190.93

1.4

3

-

+

-

-

107.97

27.32

190.96

221.06

4.1

4

+

+

-

-

152.9

46.88

191.25

249.30

3.3

5

-

-

+

-

93.05

57.66

232.97

257.40

3.5

6

+

-

+

-

113.68

72.41

134.41

190.35

4.6

7

-

+

+

-

191.9

147.91 463.54

523.04

7.3

8

+

+

+

-

226.21

137.57

317.5

413.40

3.5

9

-

-

-

+

36.41

33.42

121.97

131.60

2.1

10

+

-

-

+

45.55

43.5

123.68

138.79

2.5

11

-

+

-

+

83.97

54.61

170.56

197.80

4.8

12

+

+

-

+

92.41

65.36

157.57

194.01

4.8

13

-

-

+

+

85.82

79.67

202.76

234.15

4.7

14

+

-

+

+

93.01

93.78

209.1

247.32

4.2

15

-

+

+

+

124.31

164.94

366.3

420.52

6.0

16

+

+

+

+

142.04

156.36 343.14

402.95

5

Fig. 4 shows the effect of factors levels on cutting force, F. It is clear from the figure that, high cutting speeds generate less cutting forces than at low levels. This may be explained by the fact that, higher cutting speeds generates higher temperatures which Proceedings of the 7th Saudi Engineering Conference (SEC7)

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soften the material and reduces its shear strength, so less cutting force is required to shear the material. The feed rate and depth of cut showed an opposite effect on cutting force. Increasing feed rate and depth of cut produce higher cutting forces than those at low levels of these factors. It can be observed from the figure that, the low level of material hardness generates higher cutting forces when compared with the high hardness level. This can be explained by the fact that low hardness allows more chance to the work piece material to adhere to the tool which calls for higher cutting force to overcome it. Since the interaction in these experiments is significant, the interaction plot is generated as shown in Fig. 5. The interaction between every two factors is shown in the figure. It is clear from the plots that there is interaction between all factors except between depth of cut and hardness. Residual Plots for lnforce Residuals Versus the Fitted Values 0.30

90

0.15 Residual

Percent

Normal Probability Plot of the Residuals 99

50 10

-0.15 -0.30

1 -0.4

-0.2

0.0 Residual

0.2

0.4

5.00

Histogram of the Residuals 6.0 4.5

0.15

3.0 1.5 0.0

5.25 5.50 5.75 Fitted Value

6.00

Residuals Versus the Order of the Data 0.30

Residual

Frequency

0.00

0.00 -0.15 -0.30

-0.3

-0.2

-0.1

0.0 0.1 Residual

0.2

0.3

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16

Observation Order

Figure3. The force residual graphs

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Fi

Main Effects Plot (fitted means) for Force v

350

f

300

Mean of Force

250 200 22

51

0.04

0.08

d

350

hd

300 250 200 0.6

1.5

263

291

Figure 4. Main effects plot (cutting force)

Interaction Plot (fitted means) for Force 0.04

0.08

0.6

1.5

263

291 400 300

v

v 22 51

200

400 300

f

f 0.04 0.08

200 400 300

d

200

hd

Figure 5.Interaction between factors (cutting force)

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d 0.6 1.5

Fig. 6 shows the effect on factors levels on the surface roughness of the machined work pieces. It is clear from the figures that, high cutting speeds generate less surface roughness than at low levels of speed. The feed rate shows the same trend as the cutting force although the depth of cut shows an opposite effect on surface roughness. The high feed rate and high depth of cut produce higher surface roughness than at low levels of these factors. The low level of material hardness generates higher roughness when compared with the high hardness level.

Main Effects Plot (fitted means) for Ra v

5.0

f

4.5 4.0

Mean of Ra

3.5 3.0 22

51

0.04

d

5.0

0.08 hd

4.5 4.0 3.5 3.0 0.6

1.5

263

291

Figure 6. Main effects plot (surface roughness condition)

Other analysis is given to illustrate more details about the effects of the considered factors in Figs 7 and 8. These figures show the plots of normal probability and pareto charts of the effects for both responses surface roughness, Ra and cutting force, F. 6.3 Surface Analysis After determining the models and the effects, surface plots of surface roughness and cutting forces can be generated vs. two of the variables. In present case there are four variables, therefore, six surface plots are generated for each response, as shown in Figs 9-12.

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Normal Probability Plot of the Effects (response is Ra, Alpha = .05) 99

E ffect Ty p e N o t S ign ifican t S ig n ifican t

C

95 90

B

Percent

80 70 60 50 40 30

F actor A B C D

N ame v f d hd

F actor A B C D

N ame v f d hd

20 10 5 1

-1.0

-0.5

0.0

0.5 Effect

1.0

1.5

2.0

Lenth's PSE = 0.5625

Figure 7. Normal probability plot of the effects.

Pareto Chart of the Effects (response is Ra, Alpha = .05) 1.446 C

Term

B A AB BC A BC D A BC D AD A BD AC CD BC D ACD BD

0.0

0.5

1.0 Effect

1.5

2.0

Lenth's PSE = 0.5625

Figure 8. Pareto chart of the effects

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Surface Plot of Ra vs d; v Ho ld Values f 0.04 hd 263

4 Ra

3 2 1.5 1

1.0

20

30 v

40

d

0.5

50

Figure 9. Surface plot for surface roughness

Surface Plot of Ra vs hd; v Ho ld Values f 0.04 d 0.6

2.5

Ra

2.0

1.5

290 280 20

270

30 v

40

hd

260

50

Figure10. Surface plot for surface roughness

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Surface Plot of Force vs d; f Ho ld Values v 22 hd 263

500 400 Force

300 200

1.5 1.0

0.04 f

0.06

0.08

d

0.5

Figure11. Force surface plot

Surface Plot of Force vs d; v Ho ld Values f 0.04 hd 263

250

Force

200

150

1.5 20

1.0 30 v

40

d

0.5

50

Figure12. Force surface plot

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7. CONCLUSIONS • SABIC is producing two levels of structural steel with respect to material hardness. The harder material demonstrated higher machinability characteristics (demonstrated in lower cutting forces and surface roughness). • At present experiments, the speed has very little effect on both cutting force and surface roughness. • The cutting force is inversely proportional to hardness. • Higher surface quality is associated with higher cutting speeds and material hardness. • Feed rate and depth of cut are the most factors affecting surface roughness. • It is advisable to SABIC company to change the flow rate of quenching, in accordance with diameter of quenched bar to obtain the higher level of hardness despite changing the bars diameters. • The equations of surface roughness and cutting force are useful in predicting, the appropriate machining parameters for certain conditions. 8. ACKNOWLEDGEMENTS This work was supported by SABIC company (grant number 28/423) through the Research Center, College of Engineering, King Saud University. This support is gratefully acknowledged. REFERENCES 1. Shaw, M.C., Vyas, A. (1993), "Chip Formation in The Machining of Hardened Steel", Annals of CIRP, vol. 42, No. 1, pp. 29-33. 2. Narutaki, N., Yamne, Y., (1993), "High-Speed Machining of Inconel 718 With Ceramic Tools", Annals of CIRP, vol. 42, No. 1, pp 100-105.

3. Hodgson, T.; Trendler, P. (1981),"Turning Hardened Tool Steel With Cubic Boron Nitride", Annals of the CIRP, vol. 30, pp 63. 4. Koning, et al (1984), "Machining of Hard Materials", Annals of the CIRP, vol. 32, No. 2, pp 417-427. 5. Daniel, E.H., (1982),"Now: Turn Hardened Steel and Tough Super-alloys as Easily as Mild Steels", Machining of Hard Materials, ASM. 6. Farag, M.M., (1989),"Selection of Materials and Manufacturing Processes for Engineering Design", Prentice Hall, New York.

7. Darwish, S. and Davies, R., (1989),"Investigation of Heat Flow Through Bonded and Brazed Metal Cutting Tools", Int. J. Mach. Tools & Manufacture., vol. 29, No. 2, pp. 229-237. 8. Ashby, M. F. and Jones, D. R. H., (1998) “Materials Engineering” 2nd edition, Butterworth-Heinemann, Oxford. 9. Janc, D.Y.; Choi, Y.; Kim, H.; Hsiano, A., (1996),"Study of The Correlation Between Surface Roughness and Cutting Vibrations to Develop on-line Measuring Technique in Hard Turning", Int. J. Mach. Tools Manufacture., vol. 36, No. 5, pp. 453-464. 10. Ronald, D.M.; Thomas, W.; Lloyd, P.P., (1991),"Improving Quality Through Planned Experimentation", McGraw-Hill, New York.

11. Montgomery, D.C., (1996), "Design and Analysis of Experiments”, 4th edition, John Wiley & Sons, U.S.A.

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