Preliminary Experimental Comparison of Plunge Milling and Face Milling: Influences of Cutting Parameters on Cutting Force and Surface Roughness
The increasing demand for precision-engineered machined components across diverse sectors highlights the importance of optimizing machining procedures. The improvement of milling strategies is significant in the production of flat surfaces and slots of different sizes. The choice between milling tec...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
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| Series: | Eng |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-4117/6/6/128 |
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| Summary: | The increasing demand for precision-engineered machined components across diverse sectors highlights the importance of optimizing machining procedures. The improvement of milling strategies is significant in the production of flat surfaces and slots of different sizes. The choice between milling techniques can significantly impact the final product quality and production efficiency. This study provides a detailed examination of the relative effectiveness of plunge milling (axial feed) versus face milling (radial feed) techniques, concentrating on critical performance metrics such as cutting force and surface roughness. In our systematic approach, we varied key milling parameters (feed per tooth, depth of cut, and cutting speed). We conducted a series of experiments to quantify the resulting cutting forces and surface finish quality employed under different conditions. The analysis reveals notable performance differences between the two milling methods at various parameter settings. Through statistical and graphical analysis, we clarify the relationships between milling parameters and the resultant outputs, offering a deeper understanding of the factors influencing machining efficiency. The results reveal significant differences between plunge milling and face milling, with plunge milling exhibiting lower cutting forces, while face milling demonstrated superior surface quality. The insights granted from this research have implications for optimizing milling operations. |
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| ISSN: | 2673-4117 |