1. SALEM ABDULLAH BAGABER
A COMPARATIVE STUDY ON PERFORMANCE OF CBN INSERTS WHEN TURNING STEEL UNDER DRY AND WET CONDITIONS
SALEM ABDULLAH BAGABER
August

2. Total GHG emissions by sector (EU-27, 2011)
Characteristics of sustainable machine
(Chetan et al. 2015)
Total GHG emissions by sector (EU-27, 2011)
Power consumption of main functions in machine tools (Götze et al. 2012)

4. LITERATURE REVIEW

5. LITERATURE REVIEW

6. PROBLEM STATEMENT
The best technique of environmental machining is dry machining (Dixit et al. 2012; Schultheiss etal.2013).
Issues regarding thermal damage to the workpiece are with the dry machining (Iqbal etal.2009).
Cooling/lubrication fluids (CLFs) based oil are known one of the most unsustainable elements of machining processes (Pusavec et al. 2010) (King.etal.2001) .

7. Considering the increase of energy consumption - -Very limited research investigate of machinability includes power consumption often neglected (Nur2015)
-Studied rarely(Wang&Wang,2014).Still surveyed by experiments, not given attention (Gupta,2005)
-Most important factors among of factors (Yoon et al ), become a topic high on the agenda for manufacturing enterprises (Li 2015).
Interplay of energy consumption and other objectives are not clearly understood yet (Li et al. 2016)

8. The aims of this research is:
To evaluate performance of CBN inserts for the machining parameters PW and Ra. Comparative study on PW and Ra under dry and flood conditions

9. Dry condition apply as environment cutting.
This project focuses on the effect of cutting parameters of turning machine.
The material used to cut will be specification Stainless Steel 316 (63x120mm).
At less Three machine parameters will be varied to the experiments. Namely, cutting speed, feed rate and depth of cut.
Dry condition apply as environment cutting.
The type of cutting tool has been used coated Carbide tools
Design of Experiments (DOE) specify to BBD methods layout will be used for testing with five(5) level and analysing and optimizing using RSM.

10. The machine used will be CNC turning Machine (ROM-C420) -LCD with Siemens Sinumerik828D CNC programming.
A surface roughness will be measured by using a Mitutoyo Surftest SJ-210 portable surface roughness tester.
The digital Power Meter KEW6305 will be used to capture the power utilized during the cutting process.
Tool wear of the cutting tool will be measured using the high power optical microscope.

11. Response surface method (RSM) with box-behnken design (BBD)No
Factors
Symbol
type
Lowest level
Low level
mid-level
High level
Highest level 1
Cutting speed (rpm ) A
Numerical
(-2)
(-1)
(1)
(+2) 2
Feed rate (mm/min) B 3
Depth of cut (mm) C
The max and min value of parameters:
Vcmin = 90, Vcmax = 190 m/min frmin = 0.06, frmax = 0.23 mm/rev
ap, min = 0.6, ap, max=1.6 mm
-adapted from the Karoly handbook
-based on rough-finish cuts.
-Previous studies studies (Philip Selvaraj et al. 2014; Varaprasad et al. 2014; Berkani et al. 2015; Kara et al. 2014; Nur et al. 2015)

12. Experimental Equipmentsd

13. Mitutoyo tool maker microscope used in the presented research work To investigate this flank wear
Power Meter 6300 used to capture the power utilized during the cutting test
A surface roughness manufactured measured by using a Mitutoyo Surftest SJ-301

14. Materials workpiece Cutting tool length 120 mm Ø63 mm
properties (high mechanical properties and corrosion resistance)
widely used in many industries such as aerospace, components of contracture, automotive, chemical production, power plants, and medical instruments.
Researches regarding the machinability of the austenitic stainless steels have highlighted the insufficiency of the data for establishing of the optimum cutting conditions (Sultan et al. 2015). Machinability study on the stainless steel still is of interest (Nur et al. 2015)
length 120 mm
Ø63 mm
Cutting tool
Coating inserts carbide was selected.
Carbide tools CNMG Coated - PVD TiAlN coating designated as ISO CNMG , with 80o diamond sharp.
Cutting tools Young’s modulus: –H10, HRA 47 (103kgf/mm2)
Tool holder: BCLNR2525M12

15. Collection data &Analysis
Experiment setting
Collection data &Analysis
CBN

16. Results of the experiment
EVALUATION BASED ON LUBRICATION
Results of the experiment
Std Order
Dry
Flood PW
(Wh) Ra
(µm)
PW (Wh) 1
32.6
0.478
41.5
0.415 2
35.51
0.965
43.87
0.534 3
25.65
0.64
34.31
0.498 4
30.28
1.331
39.2
0.987 5
34.11
0.491
32.92
0.613 6
37.8
0.924
45.79
0.528 7
23.5
1.37
32.14
1.29 8
22.81
1.104
31.52
1.467 9
36.2
0.845
45.6
0.677 10
35.72
1.245
44.32 11
32.8
1.53
42.04 12
23.9
1.6
32.56
1.225 13
27.8
0.72
36.09
0.814 14
29.81
0.714
38.13
0.726 15
26.5
0.741
34.98
0.711

17. Effect
Compare

18. Effect
Compare

19. POWER CONSUMPTION (a) (b) (c) PW (W/h) Cutting speed (m/min)
Depth of cut (mm)
Feed rate (mm/rev)
PW (W/h)
(b)
(c)

20. SURFACE REGHNESS (a) (b) (c) Ra (µm) Depth of cut (mm)
Cutting speed (m/min)
Feed rate (mm/rev)
Depth of cut (mm)
Ra (µm)
(a)
(b)
(c)

21. Regression model and R-Squr values
AdjR-squr
PrdR-Squr
Energy (dry)= * v * f * d
0.8776
0.8546
0.7906
Energy (wet) = * v * f * f * f2
0.8805
0.8487
0.6707
Ra (dry)= * v * f+0.068* d * v * f * d * v * f * v*d
0.8610
0.7599
0.5631
Ra (wet) = * v+0.14* f * d-0.015* v * f * v * f * v * d * f * d
0.9263
0.8727
0.6894

22. Energy analysis Start-up power Spindle acceleration power
Machining power
Pst
Pcut
Pair P0
Setting-up power

23. Power (Kw)

24. Power consumption is affected mostly by feed rate followed by speed and depth of cut.
Optimum parameters determined (110m/min, 0.24mm/rev, 1.6mm) for power, for Ra (90m/min, 0.08mm/rev, 0.5mm) and (100m/min, 0.5mm) for TW based on minimum value of energy, tool wear and maximum of quality and tool life.
Feed rate, followed by depth of cut, was found to be the most influential factor on Ra
The analysis of results on the turning of AISI 316 was performed by using CBN in an environment cutting process with-without fluid.
AISI316 can be machined under dry to save energy and environment with acceptable quality compare to the wet condition
CONCLUSION

25. Thank you