Engineering, Environment

 

Effect of laser cutting parameters on surface roughness of stainless steel 307

 

Amal NASSAR*, Eman NASSAR, Mona A. YOUNIS

 

Dept. of Mechanical Engineering, Higher Technological Institute, Tenth of Ramadan City, Egypt

E-mails: *amal.nasser@hti.edu.eg; eman.nasser@hti.edu.eg; mona.younis@hti.edu.eg

*Corresponding author: Phone: +201006414107; Fax: +20224924319

 

Received: May 16, 2016 / Accepted: December 8, 2016 / Published: December 30, 2016

 

 

Abstract

Optimal parameters of laser cutting are an important step to improve surface quality of cutting edge in the laser cutting of stainless steel 307. This paper presents a new approach for optimizing the cutting parameters on stainless steel. Based on 33 full factorial experimental design, cutting experiments were conducted for stainless steel 307 plates using a laser machine (AMADA FONT 3015). The cutting parameters such as, cutting speed, cutting power and gas pressure are optimized for maximizing surface quality. The results indicated that cutting power and cutting speed play an important role in surface quality.

Keywords

Laser cutting parameters; Surface roughness; Stainless steel 307

 

 

Introduction

 

Laser Beam Machining is a thermal process considering the mechanisms of material removal, in this machine the electrical energy is used to produce high-energy coherent photons [1]. The advantage of laser Machining is with the high flexibility and its ability to cut metal elements with complex geometries at high preciseness, whereas manufacturing a high cut-edge quality [2]. Producing high-quality cut edges can be done by controlling the laser cutting parameters in a correct manner. There are many parameters for Laser process such as distance of the stand, speed of cutting, diameter of the nozzle, work pice thickness, pressure of the assist gas etc. Many researchers studied the effect of these parameters on widths of the kerf, angle of taper, rate of material removal, heat affected zone (HAZ) and roughness of surface [1, 3-8].

In order to evaluate the laser cutting effect on the surface roughness for a metallic material, stainless steel (SS-307) has been chosen and cutted by laser machine (AMADA FONT 3015) at different parameters. This research is an attempt to find the link between laser cutting parameters and surface roughness, to improve surface quality.

 

 

Experimental

 

A 2.0 kW AMADA FONT 3015 Laser machine is used for the experiments. Stainless steel grade 307 with a thickness of 4 mm and a length of 8 mm length was used in each experiment; workpieces were cut over a machined length of 10mm. Table 1 shows the chemical composition for the selected material.

Table 1: (SS-307) chemical composition

% from

C

Mn

Si

P

S

Cr

N

Ni

iron

0.080

2.000

0.750

0.045

0.030

18.000

0.100

8.000

Balance

 

The conditions of laser cutting are shown in table 2.

Table 2: Conditions of laser cutting

code

Power

Speed

 O2 pressure

 

code

Power

Speed

 O2 pressure

 

code

Power

Speed

 O2 pressure

A1

1200

2

4

 

A10

1000

2

4

 

A19

1000

5

3

A2

1500

2

3

 

A11

1000

3

3

 

A20

1200

2

5

A3

1500

5

5

 

A12

1500

5

3

 

A21

1200

3

4

A4

1200

5

3

 

A13

1000

5

5

 

A22

1200

2

3

A5

1500

3

3

 

A14

1200

3

5

 

A23

1000

5

4

A6

1200

3

3

 

A15

1500

5

4

 

A24

1000

3

5

A7

1200

3

4

 

A16

1000

3

4

 

A25

1500

2

5

A8

1000

2

4

 

A17

1200

5

3

 

A26

1500

3

5

A9

1000

2

3

 

A18

1200

5

5

 

A27

1500

2

4

 

Surface roughness was measured using portable tester (Mitutoyo, Model: 201 stylus profile meter) to find the roughness profile ((Ra, Rq, Rp and Rv). Digital imaging of the laser cut-edges was done using a Leica microscope and a Canon EOS 1100D digital camera. Statistical method (ANOVA) was used at the end of experiments to find out what factors have a significant effect on surface roughness.

 

ANOVA analysis for Surface roughness

A new mathematical model was designed using DESIGN EXPERT software to analyze the results, the full factorial design was selected and analysis of variance (ANOVA) was utilized to evaluate the results. Table 3 shows obtained surface roughness. Table 3 shows the selected factors operated for this study within working levels. Three factors and three levels were used in this experiment. 12 running processes were performed from the equation of full factorial design:

Full Factorial Equation = 2k                                                                            (1)

where k denotes the number of factors, i.e. 3: Power (W), Speed (mm\min), and O2 pressure, being examined in this experiment and three levels at the experiment were employed. Table3 shows the selected factors operated for this study.

Table 3. The selected factors operated for this study

Factors

Levels

Power (w)

1000

1200

1500

Cutting speed (m/min)

2

3

5

O2 pressure

3

4

5

 

 

Results and Discussion

 

Microstructures

Figure 1 shows the cutting surface for each condition. The micrographs of cutting edges revealed that cutting conditions affected on surface of cutting edge. Laser cutting left Striations parallel to cutting direction. These striations were visible at high cutting speeds and high power. When the gas pressure was high, the cut edges formed a melted surface and became less stable instead of controlled striation formations. The figure revealed that there is no correlation between the size of Striations and the parameters of cutting, and that striation size are depends on the thermal history during laser cutting. Marcelo [9] has predicted the distribution of the temperature at the cutting edge. Duley et al. [10] and Yang[11] have founded that there is no correlation between the size of Striations and cutting parameters.

C:\Users\sony\AppData\Local\Microcapture\photos\1502242040004233991.jpg

A4

C:\Users\sony\AppData\Local\Microcapture\photos\1502242034283901850.jpg

A27

C:\Users\sony\AppData\Local\Microcapture\photos\1502242038114124167.jpg

A25

C:\Users\sony\AppData\Local\Microcapture\photos\1502242038064119268.jpg

A15

 

 

 

 

C:\Users\sony\AppData\Local\Microcapture\photos\1502242023153228035.jpg

A2

C:\Users\sony\AppData\Local\Microcapture\photos\1502242025443377140.jpg

A3

C:\Users\sony\Desktop\laser photo\1502242025333366064.jpg

A22

C:\Users\sony\Desktop\laser photo\1502242019112984704.jpg

A12

Legend:  is 1408 μm on the images

Figure 1. Cutting surface for some samples at different conditions

 

Using high power leads to deeper striations. The figures reveal also, that the amount of laser power was the most significant factor in striations formation, and fine striations have appeared at high power and speed but at low gas pressure. This may be due to the gas pressure effect on the hydrodynamic behavior of molten metal which affected the molten metal expel from the cutting front and on striations formation [13]. Straight cut edges were found at low cutting speed and at low power.

 

Surface roughness properties

Figure 2 shows striations take a periodic series when the cutting process was made at low cutting speed and high power.

Figure 2. Striations generated using a power of 1500 W and gas pressure of 4 bar with traverse cutting speeds of a 5 m/min and 3 m/min

 

At high power and cutting speed, the figure 2 reveals inconsistent striations.

Figure 3 shows the roughness properties for cutting in different conditions, the least defined striations were produced at high power and speed and at low gas pressure. Increasing gas pressure leads to non-uniform striations (higher Rv and Rp). The optimum striation in the cutting-edge was found when using low power, speed, and gas pressure also, when using high power and speed, and low gas pressure. Using the right balance between traverse cutting speed and power and using a low gas pressure led to a uniform surface.

Figure 3. Roughness properties for the cutting surface (Ra) at different conditions

 

ANOVA analysis

The analysis of ANOVA is utilized to specify the Laser machining parameters, by using DESIGN EXPERT software version 9. Table 4 and 5 show the design data and design model used in the ANOVA analysis respectively.

Table 4. The design data used in ANOVA analysis

Run

Factor A

Factor B

Factor C

Response

 

Run

Factor A

Factor B

Factor C

Response

Power

Speed

O2 pressure

Roughness

 

Power

Speed

O2 pressure

Roughness

1

A level 2

B level 1

C level 2

11.56

 

15

A level 3

B level 3

C level 2

13.16

2

A level 3

B level 1

C level 1

19

 

16

A level 1

B level 2

C level 2

11.92

3

A level 3

B level 3

C level 3

13.78

 

17

A level 2

B level 3

C level 1

19

4

A level 2

B level 3

C level 2

14.67

 

18

A level 2

B level 3

C level 3

8.91

5

A level 3

B level 2

C level 1

16

 

19

A level 1

B level 3

C level 1

10.11

6

A level 2

B level 2

C level 1

14

 

20

A level 2

B level 1

C level 3

7.89

7

A level 3

B level 2

C level 2

13.16

 

21

A level 2

B level 2

C level 2

11.92

8

A level 1

B level 1

C level 2

8.55

 

22

A level 2

B level 1

C level 1

12.43

9

A level 1

B level 1

C level 1

11

 

23

A level 1

B level 3

C level 2

8.76

10

A level 1

B level 1

C level 3

8.55

 

24

A level 1

B level 2

C level 3

6.16

11

A level 1

B level 2

C level 1

5.87

 

25

A level 3

B level 1

C level 3

10.15

12

A level 3

B level 3

C level 1

16.86

 

26

A level 3

B level 2

C level 3

7.4

13

A level 1

B level 3

C level 3

2.79

 

27

A level 3

B level 1

C level 2

10.15

14

A level 2

B level 2

C level 3

6.16

 

 

 

Based on ANOVA analysis of surface roughness in Table 5, it can be seen that the model is significant with probability, Prob>F value between 0.0001 to 0.0499 less than 0.05. It shows that Factors 1 and 2 are significant, while factor 3 is not significant.

Table 5. ANOVA analysis of surface roughness

 Source

Sum of

Squares

 

df

Mean

Square

F

Value

p-value

Prob > F

293.352311

 

 

 

 

Model

6

48.89205

7.880378

0.0002

A-Power

124.494289

2

62.24714

10.03294

0.0010

B-Speed

13.3406

2

6.6703

1.075113

0.3602

C-O2 pressure

155.517422

2

77.75871

12.53308

0.0003

Residual

124.085556

20

6.204278

 

 

Total

417.437867

26

 

 

 

 

Figure 4 displays the observed values compared with the predicted values calculated from the model.

Figure 4. Observed values compared with the predicted values

 

In figure 4 it can be seen that the regression model fairly well fits with the observed values (error less than 2.7%).

The response ranges from 2.79 µm to 15.91 µm and the ratio of maximum to minimum is 5.70 µm. After eliminating the non-significant terms (B is not significant in Table 5), the final response equation for Surface Roughness is given as:

Roughness = 10.20 – 2.01·A – 2.31·C                                                          (2)

Equations in terms of all coded factors as follows:

Roughness = 10.0375 - 3.2575·A - 0.9975·B + 0.7175·C + 0.0625·AB

- 0.095·AC + 0.9375·BC + 0.25·C2 + 1.5·ABC + 1.8775·AC2 – 1.965·BC2            (3)

where A: Power; B: Speed and C: O2 Pressure.

Equation 2 and 3 are multiple regression models based on data collected during the course of the experiment configuration given in Table 3. The obtained equations allow doing estimates. Figure 5 shows the estimated response in 3D surface the Surface Roughness with Speed and O2 pressure with different levels of the Power.

for Level 1 of C

 

for Level 2 of C

for Level 3 of C

Figure 5. Estimated response of Roughness in 3D surface

The surface roughness tends to increase considerably with the decrease of power and speed [12], [14]. It is clear from the figure that the higher surface roughness can be obtained using 1000 w, 5 bar and 5 mm/min. This is due to lower power and speed exhibits higher distortion on the surface, which leads to higher surface roughness.

In general, it is evident that the surface roughness decreases with an increase in cutting speed (Figure 5). A decrease in laser power, generally increases surface roughness, however the effect of laser power should be considered through interaction with cutting speed and assist gas pressure. Similarly, an increase in gas pressure increases surface roughness. The effects of cutting speed and assist gas pressure were more pronounced than the effect of laser power on surface roughness characteristics.

 

 

Conclusions

 

The present work studies the surface quality after cutting S.S 307 in different conditions (cutting speed, gas pressure and laser power) also it predicts the values of surface roughness with a mathematical model. The conducted experiments give the following conclusions:

¸        That higher surface roughness can be obtained using 1000 w and 5 mm\min. This is due to lower power and higher speed exhibits higher distortion on the surface, which leads to higher surface roughness.

¸        Gas pressure had less effect of surface roughness. This might be due to small variation in its level.

¸        The variation in % errors in the values of roughness was estimated around 2.7 %, so the mathematical model is valid and can be used in machine response’s prediction.

 

 

References

 

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