The study on the effect of various tool wear indicators on the machining of MMCs
This paper aims to conduct tool wear experiments on cutting SiCp/Al composite materials, and methodically reveal the wear evolution of PCD tools in some detail. Based on the experiments, five-tool wear schemes are rationally developed, including free from wear, crater wear, flank wear, combined crat...
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Veröffentlicht in: | Journal of materials research and technology 2024-05, Vol.30, p.231-244 |
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Sprache: | eng |
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Zusammenfassung: | This paper aims to conduct tool wear experiments on cutting SiCp/Al composite materials, and methodically reveal the wear evolution of PCD tools in some detail. Based on the experiments, five-tool wear schemes are rationally developed, including free from wear, crater wear, flank wear, combined crater and flank wear, and edge blunting. The accurate equivalent homogeneous material (EHM) turning simulation model of SiCp/Al composite material is constructed and verified using AdvantEdge software. Subsequently, comprehensive studies have been conducted to analyze the effect of various tool wear patterns on the SiCp/Al cutting process. The results indicate that the crater wear of the tool is positively correlated with the radius of curvature of the chip. Additionally, the flank wear of the tool demonstrates a negative correlation with both the thickness and length of the chips. The actual cutting temperature is 11.3% lower compared to the simulated data, whereas the actual cutting forces in the X and Y directions are 16.1% and 13.7% higher, respectively. The flank wear degree of the tool and the edge blunting both remarkably influence the cutting force in the Y direction and the surface residual stress after machining. As the degree of wear increases, the cutting force in the Y direction and the surface residual stress rise, and the penetration layer of the residual stress becomes deeper, which is attributed to the significantly enhanced ploughing effect of the tool. This study provides a valuable reference for predicting the wear status of cutting tools, particularly in machining difficult-to-machine materials. |
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ISSN: | 2238-7854 |
DOI: | 10.1016/j.jmrt.2024.03.010 |