Stochastic Characteristics in Microgrinding Wheel Static Topography using Machine Vision
Date
2013-03-25Author
Kunz, Jacob A
Mayor, James R
Publisher
8th International Conference on MicroManufacturing (ICOMM 2013)
Metadata
Show full item recordAbstract
Superabrasive grinding wheels are used for the machining of
brittle materials such tungsten carbide. Stochastic modeling
of the wheel topography can allow for statistical bounding of
the grind force characteristics allowing improved surface
quality without sacrificing productivity. This study utilizes a
machine vision method to measure the wheel topography of
diamond microgrinding wheels. The results showed that there
are large variances in wheel specifications from the manufacturer.
The numerical simulation and analytic models used
to describe the wheel topography were seen to estimate the
static grit density to within 4.5% using measured wheel geometry
specifications. Utilizing only manufacturer-supplied
specifications caused the models to predict the static grit
density to within 24% leading to a need for improved wheel
tolerancing and in situ wheel measurement.
Subject
Grinding
Microgrinding
Stochastic modeling
Permanent Link
http://digital.library.wisc.edu/1793/65321Citation
ICOMM 2013 No. 120
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