Precision machining refers to a process that achieves dimensional accuracy between 0.1 and 1 μm, with surface roughness values of Ra ranging from 0.02 to 0.1 μm. This advanced technique is a cornerstone of the mechanical manufacturing industry and serves as an indicator of a country’s overall technological capabilities. However, traditional precision machining often involves lower cutting speeds compared to conventional methods, which can lead to reduced efficiency, higher costs, and longer production cycles. For instance, when machining aluminum alloys, the cutting speed for precision operations is typically around 100 m/min, significantly slower than the 200–300 m/min used in standard processes. To address these challenges, modern precision machining must not only ensure high accuracy but also enhance productivity and reduce costs.
To explore this, we conducted high-speed precision cutting tests using diamond tools on a high-speed CNC lathe. By optimizing cutting parameters, we achieved a high-quality surface finish and analyzed the effects of tool material, cutting method (dry or wet), and other factors on surface roughness.
In our test setup, we used LY12 high-strength aluminum alloy workpieces measuring 140 × 150 mm. Two types of diamond tools were employed: one was a polycrystalline diamond (PCD) tool with a linear bevel of 0.11 mm and Ra < 0.02 μm after grinding; the other was a natural diamond tool with a circular tip radius of 0.9 mm and similar surface finish. The machine used was a Hawk 150 high-speed CNC lathe, with a special emulsified cutting fluid applied during the process. Cutting parameters included depths of cut (ap) between 0.025 and 0.1 mm, feed rates (f) ranging from 0.005 to 0.02 mm/rev, and cutting speeds (v) between 400 and 1200 m/min.
Surface roughness was measured using a computer-aided profiler, which scans the machined surface with a stylus. The resulting electrical signal was converted into digital data through A/D conversion, allowing us to calculate Ra, Rz, Ry, s, and sm values and generate profile graphs.
The impact of cutting conditions on surface roughness was significant. Natural single-crystal diamond tools demonstrated superior performance due to their sharp edges, low friction coefficient, and excellent thermal conductivity, making them ideal for ultra-precision cutting. In contrast, PCD tools, while more cost-effective, struggled to achieve the same level of surface quality due to their inability to produce sharp edges below 1 μm.
Our experiments showed that natural diamond tools produced a 27% reduction in Ra and a 40% reduction in Ry compared to PCD tools under identical cutting conditions. Additionally, the grinding quality of the tool significantly influenced surface roughness, with finer grinding leading to better results.
Dry cutting at high speeds often resulted in increased built-up edge formation, negatively affecting surface finish. Wet cutting with emulsified fluids improved surface quality and matched the results of conventional precision cutting.
Cutting speed had a complex effect on surface roughness. While increasing speed initially raised roughness, it stabilized at higher speeds, especially for natural diamond tools. Feed rate also played a critical role, with optimal values around 0.02 mm/rev offering a balance between surface quality and efficiency.
Back cutting depth (ap) affected surface roughness differently depending on the tool. For natural diamond tools, smaller ap values led to smoother surfaces, while PCD tools required careful selection to avoid excessive roughness.
In conclusion, both natural and polycrystalline diamond tools can achieve high-precision machining within the speed range of 400–1200 m/min. Natural diamond tools offer superior surface quality, while PCD tools provide economic benefits. Proper selection of cutting parameters, including speed, feed, and depth, is essential to optimize efficiency and surface finish. The use of emulsified cutting fluids further enhances surface quality, making high-speed precision machining more viable and efficient.
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