Tool Wear, Surface Topography, and Multi-Objective Optimization of Cutting Parameters during Machining AISI 304 Flange
The application of AISI 304 austenitic stainless steel in various industrial fields has been greatly increased, but poor machinability classifies AISI 304 as a difficult-to-cut material. This study investigated the tool wear, surface topography, and optimization of cutting parameters during the machining of an AISI 304 flange component. The machining features of the AISI 304 flange included both cylindrical and end-face surfaces. Experimental results indicated that an increased cutting speed or feed aggravated tool wear and affected the machined surface roughness and surface defects simultaneously. The generation and distribution of surface defects was random. Tearing surface was the major defect in cylinder turning, while side flow was more severe in face turning. The response surface method (RSM) was applied to explore the influence of cutting parameters (e.g., cutting speed, feed, and depth of cut) on surface roughness, material removal rate (MRR), and specific cutting energy (SCE). The quadratic model of each response variable was proposed by analyzing the experimental data. The optimization of the cutting parameters was performed with a surface roughness less than the required value, the maximum MRR, and the minimum SCE as the objective. It was found that the desirable cutting parameters were v = 120 m/min, f = 0.18 mm/rev, and ap = 0.42 mm for the AISI 304 flange to be machined.
Materials and Methods
Workpiece Material and Cutting Tool
Experimental Equipment
Design of Experiments
Tool Wear
Surface Topography
Surface Defects
3D Surface Topography
Optimization
1. Introduction
2. Materials and Methods
2.1. Workpiece Material and Cutting Tool
Composition | C | Si | Mn | Cr | Ni | Mo | Cu | Fe |
---|---|---|---|---|---|---|---|---|
(wt) % | 0.055 | 0.64 | 1.66 | 18.2 | 9.11 | 0.092 | 0.14 | 69.7 |
Density (g/cm3) | Elastic Modulus (GPa) | Poisson′s Ratio | Coefficient of Thermal Expansion (10−6∙K−1) | Thermal Conductivity (W∙m−1∙K−1) | Specific Heat Capacity (J∙kg−1∙K−1) |
---|---|---|---|---|---|
7.93 | 193 | 0.3 | 17.2 | 16.3 | 500 |
2.2. Experimental Equipment
2.3. Design of Experiments
Parameters | Levels | ||||
---|---|---|---|---|---|
−α | −1 | 0 | +1 | +α | |
v (m/min) | 66.36 | 80 | 100 | 120 | 133.64 |
f (mm/rev) | 0.07 | 0.10 | 0.15 | 0.20 | 0.23 |
ap (mm) | 0.27 | 0.3 | 0.4 | 0.5 | 0.57 |
3. Results and Discussions
3.1. Tool Wear
3.2. Surface Topography
3.2.1. Surface Defects
3.2.2. 3D Surface Topography
3.3. Optimization
Run | V (m/min) | f (mm/rev) | ap (mm) | Sa (μm) | MRR (mm3/min) | SCE (J/mm3) |
---|---|---|---|---|---|---|
1 | 80.00 | 0.10 | 0.30 | 1.60 ± 0.10 | 2400 | 5.25 ± 0.25 |
2 | 120.00 | 0.10 | 0.30 | 1.23 ± 0.09 | 3600 | 4.33 ± 0.17 |
3 | 80.00 | 0.20 | 0.30 | 2.12 ± 0.16 | 4800 | 4.50 ± 0.13 |
4 | 120.00 | 0.20 | 0.30 | 1.63 ± 0.11 | 7200 | 3.67 ± 0.08 |
5 | 80.00 | 0.10 | 0.50 | 1.60 ± 0.10 | 4000 | 4.95 ± 0.15 |
6 | 120.00 | 0.10 | 0.50 | 1.34 ± 0.07 | 6000 | 4.20 ± 0.10 |
7 | 80.00 | 0.20 | 0.50 | 2.46 ± 0.12 | 8000 | 4.20 ± 0.08 |
8 | 120.00 | 0.20 | 0.50 | 2.18 ± 0.11 | 12,000 | 3.55 ± 0.05 |
9 | 66.36 | 0.15 | 0.40 | 2.04 ± 0.13 | 3982 | 5.13 ± 0.15 |
10 | 133.64 | 0.15 | 0.40 | 1.37 ± 0.08 | 8018 | 3.59 ± 0.07 |
11 | 100.00 | 0.07 | 0.40 | 1.25 ± 0.08 | 2800 | 5.14 ± 0.21 |
12 | 100.00 | 0.23 | 0.40 | 2.19 ± 0.15 | 9200 | 3.65 ± 0.07 |
13 | 100.00 | 0.15 | 0.23 | 1.57 ± 0.12 | 3450 | 4.17 ± 0.17 |
14 | 100.00 | 0.15 | 0.57 | 2.20 ± 0.11 | 8550 | 4.00 ± 0.07 |
15 | 100.00 | 0.15 | 0.40 | 1.32 ± 0.07 | 6000 | 3.90 ± 0.10 |
16 | 100.00 | 0.15 | 0.40 | 1.28 ± 0.10 | 6000 | 4.00 ± 0.10 |
17 | 100.00 | 0.15 | 0.40 | 1.46 ± 0.10 | 6000 | 4.10 ± 0.10 |
18 | 100.00 | 0.15 | 0.40 | 1.37 ± 0.11 | 6000 | 4.00 ± 0.10 |
19 | 100.00 | 0.15 | 0.40 | 1.31 ± 0.08 | 6000 | 4.00 ± 0.10 |
20 | 100.00 | 0.15 | 0.40 | 1.22 ± 0.09 | 6000 | 4.00 ± 0.10 |
Where, z(x, y) is the distance from the point on the surface contour to the reference plane, and A is the measurement area.
where, P refers to the total power, and P0 is the idle power. The idle power consists of standby power and spindle rotation power. Pc represents the power consumed by the material removal.
Response | P-Value of Model | Std. Dev. | R2 | Adj. R2 | Pred. R2 | Adeq. Precision |
---|---|---|---|---|---|---|
Sa | <0.0001 | 0.079 | 0.9799 | 0.9618 | 0.9166 | 23.489 |
MRR | <0.0001 | 105.94 | 0.9990 | 0.9980 | 0.9909 | 124.592 |
SCE | <0.0001 | 0.086 | 0.9858 | 0.9730 | 0.9156 | 29.391 |
No. | Factors | Responses | Desirability | ||||
---|---|---|---|---|---|---|---|
v (m/min) | f (mm/rev) | ap (mm) | Sa (μm) | MRR (mm3/min) | SCE (J/mm3) | ||
1 | 120.00 | 0.18 | 0.42 | 1.600 | 9324.13 | 3.525 | 0.843 |
2 | 120.00 | 0.18 | 0.43 | 1.600 | 9331.76 | 3.527 | 0.843 |
3 | 119.95 | 0.18 | 0.43 | 1.600 | 9323.84 | 3.526 | 0.843 |
4 | 120.00 | 0.18 | 0.43 | 1.600 | 9340.35 | 3.531 | 0.843 |
5 | 119.99 | 0.18 | 0.43 | 1.600 | 9342.00 | 3.532 | 0.843 |
6 | 119.98 | 0.19 | 0.41 | 1.600 | 9263.11 | 3.516 | 0.842 |
7 | 120.00 | 0.19 | 0.41 | 1.600 | 9254.63 | 3.515 | 0.841 |
8 | 120.00 | 0.18 | 0.44 | 1.600 | 9350.67 | 3.543 | 0.840 |
9 | 119.67 | 0.18 | 0.44 | 1.600 | 9331.16 | 3.542 | 0.840 |
10 | 120.00 | 0.19 | 0.40 | 1.600 | 9201.12 | 3.512 | 0.839 |
4. Conclusions
- (1) The main types of tool wear included crater wear, flank wear, notch wear, BUE, BUL, chipping, etc. In cylinder turning, BUE formed at a lower speed, and lower feed effectively protected the tool tip and reduced tool wear. The rise of cutting speed or feed aggravated tool wear. In face turning, the impact of depth of cut and feed on tool wear was relatively insignificant.
- (2) There were a lot of defects on the surface for both cylindrical turning and face turning. The main types of surface defects included tearing surface, adhered material particles, scratch marks, feed marks, side flow, plastic flow, and plowing grooves. Tearing surface was the major defect in cylinder turning, while side flow was more severe in face turning. The generation and distribution of surface defects was random, and there was no obvious change trend under different cutting parameters.
- (3) The turning surface presented regular peaks and valleys. Peak height of the cylinder turning surface at a lower cutting speed was higher than that at a higher speed, and higher feed corresponded to higher peak height. In face turning, the peak height of the machined surface at a lower feed was lower than that at a higher feed, and it was higher under a larger depth of cut than under a smaller one.
- (4) The effect of the cutting parameters on surface roughness, MRR, and SCE was studied. The quadratic model of each response variable was proposed by analyzing the experimental data. The RSM was employed to achieve the optimization of the cutting parameters, with the surface roughness below 1.6 μm, the maximum MRR, and the minimum SCE as the objective. The optimization of the cutting parameters was carried out when the three desired responses were in equal weight, and the most desirable cutting parameters are v = 120 m/min, f = 0.18 mm/rev, and ap = 0.42 mm.
Source: China Flange Manufacturer – Yaang Pipe Industry Co., Limited (www.ugsteelmill.com)
(Yaang Pipe Industry is a leading manufacturer and supplier of nickel alloy and stainless steel products, including Super Duplex Stainless Steel Flanges, Stainless Steel Flanges, Stainless Steel Pipe Fittings, Stainless Steel Pipe. Yaang products are widely used in Shipbuilding, Nuclear power, Marine engineering, Petroleum, Chemical, Mining, Sewage treatment, Natural gas and Pressure vessels and other industries.)
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