Probabilistic modeling of microgrinding wheel topographyReport as inadecuate

Probabilistic modeling of microgrinding wheel topography

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This work addresses the advanced probabilistic modeling of the stochastic nature ofmicrogrinding in the machining of high-aspect ratio, ceramic micro-features. Theheightened sensitivity of such high-fidelity workpieces to excessive grit cutting forcedrives a need for improved stochastic modeling. Statistical propagation is used togenerate a comprehensive analytic probabilistic model for static wheel topography.Numerical simulation and measurement of microgrinding wheels show the modelaccurately predicts the stochastic nature of the topography when exact wheelspecifications are known. Investigation into the statistical scale affects associatedmicrogrinding wheels shows that the decreasing number of abrasives in the wheelincreases the relative statistical variability in the wheel topography although variability inthe wheel concentration number dominates the source of variance. An in situmicrogrinding wheel measurement technique is developed to aid in the calibration of theprocess model to improve on the inaccuracy caused by wheel specification error. Aprobabilistic model is generated for straight traverse and infeed microgrinding dynamicwheel topography. Infeed microgrinding was shown to provide a method of measuringindividual grit cutting forces with constant undeformed chip thickness within the grindzone. Measurements of the dynamic wheel topography in infeed microgrinding verifiedthe accuracy of the probabilistic model.

Georgia Tech Theses and Dissertations - School of Mechanical Engineering Theses and Dissertations -

Author: Kunz, Jacob Andrew - -


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