2004
DOI: 10.1115/1.1813470
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On the Modeling and Analysis of Machining Performance in Micro-Endmilling, Part I: Surface Generation

Abstract: This paper examines the surface generation process in the micro-endmilling of both single-phase and multiphase workpiece materials. We used 508 μm dia endmills with edge radii of 2 and 5 μm to machine slots in ferrite, pearlite, and two ductile iron materials at feed rates ranging from 0.25 to 3.0 μm/flute. A surface generation model to predict the surface roughness for the slot floor centerline is then developed based on the minimum chip thickness concept. The minimum chip thickness values were found through … Show more

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Cited by 261 publications
(169 citation statements)
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“…Liu et al [37] established an analytical model for predicting minimum chip thickness; this model is based on the thermo-mechanical properties of the machined material, which include cutting temperature, strain, and strain rate. Vogler et al [38,39] used finite element modeling approach to investigate the minimum chip thickness of steel; they found that the minimum chip thickness is approximately 0.2 and 0.3 times of the edge radius of a cutting tool for pearlite and ferrite, respectively. This finding validates the assumption that material property affects minimum chip thickness.…”
Section: Micro-cuttingmentioning
confidence: 99%
“…Liu et al [37] established an analytical model for predicting minimum chip thickness; this model is based on the thermo-mechanical properties of the machined material, which include cutting temperature, strain, and strain rate. Vogler et al [38,39] used finite element modeling approach to investigate the minimum chip thickness of steel; they found that the minimum chip thickness is approximately 0.2 and 0.3 times of the edge radius of a cutting tool for pearlite and ferrite, respectively. This finding validates the assumption that material property affects minimum chip thickness.…”
Section: Micro-cuttingmentioning
confidence: 99%
“…Cutting edge radius (sharpness) and its effect on other parameters such as forces [21,22], surface roughness [22][23][24], burr formation [25] and acoustic emissions (AE) [26] have also been studied. This literature supports the relevancy of this parameter to guarantee a complete chip formation and to predict other process responses.…”
Section: Size Effectmentioning
confidence: 99%
“…In this first case, the box 4 output is a scalar. On the other hand, when considering the effective rake angle (WE approach),  WE is proportional to α eff and their relationship can be found by means of a regression analysis, as done in [24,33] (box 4, WE approach, in Fig. 8).…”
Section: Box 4 -Shear Angle (Second Step)mentioning
confidence: 99%
“…Moreover, the authors took into account the dead metal cap presence and introduced the effective rake angle in the model as a function of the uncut chip thickness [33].…”
mentioning
confidence: 99%