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TECHNICAL PAPERS

Investigation of the Dynamics of Microend Milling—Part II: Model Validation and Interpretation

[+] Author and Article Information
Martin B. Jun, Richard E. DeVor, Shiv G. Kapoor

Department of Mechanical and Industrial Engineering, University of Illinois at Urbana-Champaign, 1206 West Green Street, Urbana, IL 61801-2906

J. Manuf. Sci. Eng 128(4), 901-912 (Mar 28, 2006) (12 pages) doi:10.1115/1.2335854 History: Received March 10, 2005; Revised March 28, 2006

In Part II of this paper, experimental and analytical methods have been developed to estimate the values of the process faults defined in Part I of this paper. The additional faults introduced by the microend mill design are shown to have a significant influence on the total net runout of the microend mill. The dynamic model has been validated through microend milling experiments. Using the dynamic model, the effects of minimum chip thickness and elastic recovery on microend milling stability have been studied over a range of feed rates for which the cutting mechanisms vary from ploughing-dominated to shearing-dominated. The minimum chip thickness effect is found to cause feed rate dependent instability at low feed rates, and the range of unstable feed rates depends on the axial depth of cut. The effects of process faults on microend mill vibrations have also been studied and the influence of the unbalance from the faults is found to be significant as spindle speed is increased. The stability characteristics due to the regenerative effect have been studied. The results show that the stability lobes from the second mode of the microend mill, which are generally neglected in macroscale end milling, affect the microend mill stability significantly.

Copyright © 2006 by American Society of Mechanical Engineers
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References

Figures

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Figure 1

Process fault measurement at the tool with optical microscope

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Figure 2

Pictures taken by the microscope for both cutting edges at 3000× magnification

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Figure 3

Experimental setup for validation test

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Figure 4

Experimental and predicted peak-to-valley forces at 75,000 and 150,000rpm for pearlite

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Figure 5

Experimental and predicted peak-to-valley forces at 75,000 and 150,000rpm for ferrite

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Figure 6

Chip load/force relationship for (a) pearlite and (b) ferrite

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Figure 7

Experimental and predicted slotting forces and their spectra at 75,000rpm for pearlite

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Figure 8

Experimental and predicted slotting forces and their spectra at 150,000rpm for pearlite

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Figure 9

Spectra of the acoustic emission signal during slotting at feed rates of 0.1 and 2.0μm∕tooth and 75,000rpm

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Figure 10

Tool tip vibration history and frequency spectra for machining pearlite at different feed rates

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Figure 11

Tool tip vibration history and frequency spectra for machining pearlite at 30μm axial depth of cut

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Figure 12

Tool tip vibration history with and without considering elastic recovery

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Figure 13

Peak-to-valley vibrations

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Figure 14

Spectra of the tool tip vibrations at 500,000rpm

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Figure 15

Stability lobes when Ls=17mm and Lt=1.5mm

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Figure 16

Stability lobes when Ls=10mm and Lt=2.5mm

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Figure 17

Spectra of the tool tip vibrations

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Figure 18

Contour map of the X direction shank and tool tip vibrations for case (a) Ls=17mm and Lt=1.5mm and case (b) Ls=10mm and Lt=2.5mm

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