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Analyzing Tool Dynamics and Surface Roughness Variation for Low Depths of Cut when Milling 6061-T6 Aluminum

This study explores the relationship between endmill tool dynamics and cutting parameters, emphasizing the impact of these factors on machining dynamics, surface finish, and dimensional control. It introduces a novel approach to analyze and optimize the overall performance of a solid carbide endmill, with a specific focus on machining Aluminum 6066-T6. By using stability lobes diagrams (SLD), stable conditions for cutting were chosen, and then surface roughness and tool and workpiece vibration analyses were performed to assess machining performance. This work aims to understand the effects of operating below the peaks and valleys, inherent in the shape of the SLD, using different RPMs. The study's methodology involves tap tests using CutPro - Tap Test Module and milling tests on a horizontal machining center. The surface roughness measurement was performed using an Alicona Infinite Focus confocal microscope and accelerometers were positioned on the spindle bearing housing and workpiece. The findings suggest that within the stable range below the stability lobe diagram's boundary, there is a significant difference in vibration resulting in variation in surface roughness corresponding to the peaks and valleys of the SLD. The variation of acceleration, and consequently vibration, was considerably higher when operating below valleys which negatively affected the surface roughness of the workpiece. The surface roughness plays a pivotal role in tool performance and subsequently influences metal removal rate and tool and spindle life. For conditions closer to instability, this is even more important. In conclusion, this research lays the foundation for a holistic approach to solid carbide endmill design and cutting parameter selection, showing that the machining process can be optimized in terms of the SLDs, even in regions far below the stability limit / Thesis / Master of Applied Science (MASc)

Identiferoai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/29440
Date January 2024
CreatorsDaitch, Pavel
ContributorsVeldhuis, Stephen C., DePaiva, Jose Mario, Engineering
Source SetsMcMaster University
LanguageEnglish
Detected LanguageEnglish
TypeThesis

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