1. Comparison of tool life and surface roughness with MQL, flood cooling, and dry cutting conditions with P20 and D2 steels
S W M A I Senevirathne M.Eng., B.Sc.
H K G Punchihewa Ph.D., M.Sc. B.Sc.
Department of Mechanical Engineering
University of Moratuwa, Sri Lanka

2. Minimum Quantity Lubrication
Aerosol
MQL (50 – 400 ml / hr) Vs Flood (~10 l / min)
Evaporative cooling dominates
Better lubrication
Not obstructing
Promising results
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Rationale
High cost of CF : 20% of total mfg. cost
Trend of MQL
Effect of MQL on hard-to-cut material?
Effect of work-piece material on machining performance?
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Aim & Objectives
Aim
Study the effect of MQL & WP material on machining performances
Objectives
To select material for the experiment
To evaluate machining performance against MQL & WP material
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Cooling Condition
Material
Response variable
TNW | SR
P20
Dry
Flood
MQL D2
Experiment Design
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Research parameters
Predictors
Work material
P20 D2
Cooling method
Dry
Flood
MQL
Response variables
Tool nose wear
Surface roughness (Ra)
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7. Controlled Parameters
Value
Turning Operation
Straight
Flow Rate (MQL)
160 ml/ hour
Feed Rate
0.5 mm / rev
Pneumatic Pressure
7 bar
Depth of Cut
0.5 mm
Flow Rate (Flood)
9 l/min
Length of the Cut
500 mm
Nozzle Target Area
Rake Face
Surface Cutting Speed
150 m/min
Nozzle Angle (H)
≈ 60o
Spindle Speed
1220 rpm
Nozzle Distance
150 mm
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Experimental setup
3.0 kW horizontal lathe
WC tool insert
90.3 HRA
Emulsion CF
1:9 v/v water
Work-pieces
AISI P20 (52 HRC)
AISI D2 (62 HRC)
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Application of MQL
Applied to : rake face
Flow rate : 160 ml / hr
Pressure : 7 bar
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Response variables
Tool nose wear
Arithmetic average SR (Ra)
CNC-CMM
Resolution : mm
Digital SR tester
Accuracy : 0.01 µm
Cut-off length : 2.5 mm
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11. Tool Nose Wear & Mean Ra Mean Tool Nose Wear (mm) Mean Ra (μm)
Mean Tool Nose Wear (mm)
Mean Ra (μm)
Cooling Condition
P20 D2
Dry
0.0643
0.0557
1.514
1.623
Flood
0.0283
0.0299
1.406
1.373
MQL
0.0867
0.0907
1.594
1.518
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ANOVA of P20 Groups
TNW groups
F = | P = (<0.05) | CI = 95%
⸫ at least one mean TNW of the tested 3 groups is significantly different from the others
Ra groups
F = | P = (<0.05) | CI = 95%
⸫ at least one mean Ra of the tested 3 groups is significantly different from the others
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ANOVA of D2 Groups
TNW groups
F = | P = (<0.05) | CI = 95%
⸫ at least one mean TNW of the tested 3 groups is significantly different from the others
Ra groups
F = | P = (<0.05) | CI = 95%
⸫ at least one mean Ra of the tested 3 groups is significantly different from the others
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t-Test on P20 Groups
Tool nose wear Ra
Flood
MQL
Dry
Significantly high
Significantly low
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t-Test on D2 Groups
Tool nose wear Ra
Flood
MQL
Dry
Significantly high
Significantly low
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Work Material Effect
Tool nose wear Ra
Dry (P20)
Flood (P20)
MQL (P20)
Dry (D2)
Not
Sig.
high
Flood (D2)
low
MQL (D2)
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Work Material Effect
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Conclusions
MQL causes higher TNW in P20 & D2 with coated carbide tools
SR of P20 & D2 with MQL was higher than flood cooling
In P20, SR with MQL higher than dry cutting
Non-favourable performance with P20 or D2 steels
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Conclusions
TNW with P20 & D2, in dry, flood cooling, or MQL, is not different
SR varied significantly with the material
In dry, SR in D2 lower than P20,
Flood cooling & MQL SR in P20 lower than D2
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Thank you!
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