Research Papers

On the Development of an Experimental Testing Platform for the Vortex Machining Process

[+] Author and Article Information
Stephen C. Howard

e-mail: showar21@uncc.edu

Jacob W. Chesna

e-mail: Jacob@chesna.us

Stuart T. Smith

e-mail: stusmith@uncc.edu

Brigid A. Mullany

e-mail: bamullan@uncc.edu
Center for Precision Metrology,
University of North Carolina at Charlotte,
Charlotte, NC 28223

Contributed by the Manufacturing Engineering Division of ASME for publication in the JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING. Manuscript received January 12, 2013; final manuscript received July 5, 2013; published online September 11, 2013. Assoc. Editor: Eric R. Marsh.

J. Manuf. Sci. Eng 135(5), 051005 (Sep 11, 2013) (8 pages) Paper No: MANU-13-1013; doi: 10.1115/1.4025011 History: Received January 12, 2013; Revised July 05, 2013

The development of an experimental platform for studying Vortex Machining is presented. This process uses oscillating probes to generate localized vortices in polishing slurry in a region near to a workpiece surface. These vortices create material removal footprints having lateral dimensions typically measuring tens of micrometers. From studies of the process variables and subsequent machining footprints a number of process controls have been implemented and are discussed herein. These include a localized metrology frame to control specimen to probe position, coarse-fine translation axes for submicrometer motion control, closed-loop control of probe oscillation, and a slurry height control system. To illustrate the fidelity of these additional controls, the evolution from early machining footprints to the recent production of footprint arrays are presented. While process stability issues remain, machining footprints of near Gaussian shape having dimensions of 10–20 μm diameter and 40 nm depth after machining for 30 min can be reproduced.

Copyright © 2013 by ASME
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Nowakowski, B. K., Smith, S. T., Mullany, B. A., and Woody, S. C., 2009, “Vortex Machining: Localized Surface Modification Using an Oscillating Fiber Probe,” Mach. Sci. Technol., 13, pp. 561–570. [CrossRef]
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Howard, S., Chesna, J. W., Mullany, B., and Smith, S. T., 2012, “Observations During Vortex Machining Process Development,” Proceedings of ASME, Notre Dame.
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Howard, S. C., Chesna, J. W., Mullany, B. A., and Smith, S. T., 2012, “Preliminary Characterization of Vortex Machining,” Proceedings of 12th International Conference of Euspen, Bedford, pp. 50–53.
Howard, S., Mullany, B., Smith, S., 2013, “Design and Implementation of a High-Power Machining Facility for Investigations in Vortex Machining,” Proceedings of 13th International Conference of Euspen, Bedford, pp. 213–216.


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Fig. 1

Schematic diagram of Vortex Machining process

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Fig. 2

Block diagram showing circuit configuration of lock-in amplifier, buffer amplifier, probe, balanced bridge, difference amplifier, and gain (R) and phase (θ) outputs

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Fig. 3

Schematic diagram of Vortex Machining experimental platform. Modified from [5].

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Fig. 4

Images of complete Vortex Machining test facility (a), close-up view of machining area (b), and close-up view displaying Abbe offset between measurement axes and machining loop (c).

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Fig. 5

Experimental data showing positional drift in an uncompensated machine frame. (a) shows long-term drift with initial apparent settling over the first 10–20 h. (b) shows short-term cyclical drift with a 14–17 min period.

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Fig. 13

Contour plots of footprints machined during different phases of experimental facility design. Single footprints machined before (3 h test) and after (30 min test) implementation of slurry depth and probe controls are shown in (a) and (b), respectively. A 4 by 3 matrix of individually spaced footprints polished after implementation of slurry depth control, probe control, and automated CNC algorithm is shown in (c). All footprints were measured using a SWLI.

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Fig. 12

Slurry depth compensation control diagram illustrating bang–bang control algorithm. The reflective sensor output is amplified, calibrated, and compared against the desired slurry depth. If the output is less than the desired depth, a pulse is sent to trigger the automated syringe to add fluid.

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Fig. 11

Controller errors in x (a), y (b), and z (c) axes over a 17.5 h testing period. Only control errors after the axis had attained desired machining position are shown.

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Fig. 10

Control diagram for positioning system consisting of coarse displacement subsystem driven by ac servo motor (M) and fine displacement subsystem driven by flexure-constrained piezoelectric actuator (PZT). The individual controllers consist of proportional-plus-integral algorithms.

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Fig. 9

Experimental data showing probe response magnitude, phase, and frequency under phase-lock control (using frequency servo routine) over a 4 h testing period. (a) shows probe magnitude (square marker, left axis) and probe phase (triangle marker, right axis). (b) shows relative probe frequency deviation from 32.7178 kHz.

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Fig. 8

Experimental data showing the fluid depth control error (square marker, left axis) and the number of shots dispensed from the syringe (triangle marker, right axis) over a 3 h testing period.

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Fig. 7

Graph of infrared sensor voltage over time as slurry evaporated. Full-scale sensor nonlinearities can be noticed. Circle indicates region in which null-output control routine is locked to.

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Fig. 6

Image showing components of slurry depth compensation system



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