Tony Schmitz | University of North Carolina at Charlotte (original) (raw)

Papers by Tony Schmitz

Research paper thumbnail of On Cutting Force Coefficient Model with Respect to Tool Geometry and Tool Wear

Procedia Manufacturing, 2015

Research paper thumbnail of Dynamics Prediction for Internet-based High-Speed Milling Process Parameter Selection

Research paper thumbnail of The Microphone Feedback Analogy for Chatter in Machining

Shock and Vibration, 2015

Research paper thumbnail of Estimation of Cutting Conditions in Precision Micromachining of CuNi Alloys of Varying Composition

Research paper thumbnail of Periodic error calculation from spectrum analyzer data

Precision Engineering, 2010

Research paper thumbnail of Sensor design and evaluation for on-machine probing of extruded tool joints

Precision Engineering, 2011

ABSTRACT This paper describes the design and evaluation of two contact probes used to measure the... more ABSTRACT This paper describes the design and evaluation of two contact probes used to measure the length and bore concentricity of cylindrical, extruded tool joints while clamped in a production lathe spindle. The probes consisted of an LVDT, a spring-preloaded shaft supported by linear bearings used to isolate the LVDT from side loads, and a hardened steel sphere to contact the rough surface. For bore concentricity measurements, a parallelogram leaf-type flexure and 45° surface was used to transfer radial deviations to the spindle/part/LVDT axis. The LVDT output was used in conjunction with the lathe turret position to determine the extruded part dimensions prior to machining. Experimental results are provided for measurements of multiple parts; variations in length, internal diameter, and bore concentricity are compared to the nominal dimensions. Additionally, a calibration artifact is described which enabled evaluation of the measurement accuracies for the two probes. Given the pre-machining part dimensions, it is shown how this information can be used to select from a pre-defined matrix of part programs to reduce cycle time and machining cost.

Research paper thumbnail of Chatter recognition by a statistical evaluation of the synchronously sampled audio signal

Research paper thumbnail of Variable Tuned Holder For Machine Tools

Research paper thumbnail of In situ monitoring and prediction of progressive joint wear using Bayesian statistics

Research paper thumbnail of TOOL LIFE PREDICTION USING RANDOM WALK BAYESIAN UPDATING

Http Dx Doi Org 10 1080 10910344 2013 806103, Jul 3, 2013

ABSTRACT According to the Taylor tool life equation, tool life reduces with increasing cutting sp... more ABSTRACT According to the Taylor tool life equation, tool life reduces with increasing cutting speed. The influence of additional factors can also be incorporated. However, tool wear is generally considered a stochastic process with uncertainty in the model constants. In this work, Bayesian inference is applied to predict tool life for milling/turning operations using the random walk/surface methods. For milling, Bayesian inference using a random walk approach is applied to the well-known Taylor tool life model. Tool wear tests are performed using an uncoated carbide tool and AISI 1018 steel work material. Test results are used to update the probability distribution of tool life. The updated beliefs are then applied to predict tool life using a probability distribution. For turning, both cutting speed and feed are considered. Bayesian updating is performed using the random surface technique. Turning tests are completed using a coated carbide tool and forged AISI 4137 chrome alloy steel. The test results are applied to update the probability distribution of tool life and the updated beliefs are used to predict tool life. While this work uses the Taylor model, by following the procedures described here, the technique can be applied to other tool life models as well.

Research paper thumbnail of A METHOD FOR PREDICTING CHATTER STABILITY FOR SYSTEMS WITH SPEED-DEPENDENT SPINDLE DYNAMICS

... Tony L. Schmitz, John C. Ziegert, Charles Stanislaus Department of Mechanical and Aerospace E... more ... Tony L. Schmitz, John C. Ziegert, Charles Stanislaus Department of Mechanical and Aerospace Engineering University of Florida Gainesville, FL KEYWORDS ... [1998], Davies et al. [1998], Schmitz and Donaldson [2000], Schmitz et al. [2001]), holder characteristics (Agapiou et al. ...

Research paper thumbnail of A Study of Linear Joint and Tool Models in Spindle-Holder-Tool Receptance Coupling

Volume 6: 5th International Conference on Multibody Systems, Nonlinear Dynamics, and Control, Parts A, B, and C, 2005

ABSTRACT

Research paper thumbnail of Improving the Fabrication Process of Micro-Air-Vehicle Flapping Wings

AIAA Journal, 2015

ABSTRACT The aerodynamic performance of flapping micro air vehicles in hover conditions is depend... more ABSTRACT The aerodynamic performance of flapping micro air vehicles in hover conditions is dependent on many parameters, including the wing design. With the goal of optimizing the wing for hover performance, the initial focus was to reduce the uncertainty in the thrust measurements. This is because lower uncertainty in this metric enables better resolution in comparing the performance of different designs. Aerodynamic performance variability was deemed to be the fault of an imprecise manufacturing technique. Therefore, adjustments were made to the fabrication process until a permissible level of uncertainty was attained for optimization; the goal was less than 5%. This paper chronicles the progression of the wing fabrication process and details how the uncertainty was evaluated. Four fabrication methods and two different wing designs are included in this study: a carbon fiber hand layup technique, carbon fiber cured in a machined mold, and two variations of a machined plastic skeleton reinforced with a carbon fiber rod. The uncertainty in thrust production, expressed in coefficient of variation, improved from 16.8% for the hand layup method to 2.6% for the computer numerically controlled plastic skeleton adhered to the nylon membrane with transfer tape. Additionally, the coefficient of variation for wing weight also reduced (from 11.4 to 2.0%). Read More: http://arc.aiaa.org/doi/abs/10.2514/1.J053884

Research paper thumbnail of UNCERTAINTY OF SPATIAL COORDINATE MEASUREMENTS USING TRILATERATION

Research paper thumbnail of Experimental validation of digital periodic error correction

Research paper thumbnail of DIGITAL PERIODIC ERROR CORRECTION: FURTHER TESTING AND RESULTS

Research paper thumbnail of Optimal Experimentation for Selecting Stable Milling Parameters: A Bayesian Approach

ASME 2009 International Manufacturing Science and Engineering Conference, Volume 1, 2009

Optimal Experimentation for Selecting Stable Milling Parameters: A Bayesian Approach. [ASME Confe... more Optimal Experimentation for Selecting Stable Milling Parameters: A Bayesian Approach. [ASME Conference Proceedings 2009, 277 (2009)]. Michael G. Traverso, Raúl Zapata, Tony L. Schmitz, Ali E. Abbas. Abstract. Bayesian ...

Research paper thumbnail of A Sapphire Based Fiber Optic Dynamic Pressure Sensor for Harsh Environments: Fabrication and Characterization

49th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition, 2011

Research paper thumbnail of Tool wear monitoring using naïve Bayes classifiers

The International Journal of Advanced Manufacturing Technology, 2014

ABSTRACT A naïve Bayes classifier method for tool condition monitoring is described. End-milling ... more ABSTRACT A naïve Bayes classifier method for tool condition monitoring is described. End-milling tests were performed at different spindle speeds and the cutting force was measured using a table-mounted dynamometer. The effect of tool wear on force features in the time and frequency domains was evaluated and used for training the classifier. The amount of tool wear was predicted using the naïve Bayes classifier method. Two cases are presented. First, the tool wear is divided into discrete states based on the amount of flank wear and the probability of the tool wear being in any state is updated using force data. Second, a continuous case is considered and the probability density function of the tool flank wear width is updated. The results are discussed.

Research paper thumbnail of Tool life prediction using Bayesian updating

Research paper thumbnail of On Cutting Force Coefficient Model with Respect to Tool Geometry and Tool Wear

Procedia Manufacturing, 2015

Research paper thumbnail of Dynamics Prediction for Internet-based High-Speed Milling Process Parameter Selection

Research paper thumbnail of The Microphone Feedback Analogy for Chatter in Machining

Shock and Vibration, 2015

Research paper thumbnail of Estimation of Cutting Conditions in Precision Micromachining of CuNi Alloys of Varying Composition

Research paper thumbnail of Periodic error calculation from spectrum analyzer data

Precision Engineering, 2010

Research paper thumbnail of Sensor design and evaluation for on-machine probing of extruded tool joints

Precision Engineering, 2011

ABSTRACT This paper describes the design and evaluation of two contact probes used to measure the... more ABSTRACT This paper describes the design and evaluation of two contact probes used to measure the length and bore concentricity of cylindrical, extruded tool joints while clamped in a production lathe spindle. The probes consisted of an LVDT, a spring-preloaded shaft supported by linear bearings used to isolate the LVDT from side loads, and a hardened steel sphere to contact the rough surface. For bore concentricity measurements, a parallelogram leaf-type flexure and 45° surface was used to transfer radial deviations to the spindle/part/LVDT axis. The LVDT output was used in conjunction with the lathe turret position to determine the extruded part dimensions prior to machining. Experimental results are provided for measurements of multiple parts; variations in length, internal diameter, and bore concentricity are compared to the nominal dimensions. Additionally, a calibration artifact is described which enabled evaluation of the measurement accuracies for the two probes. Given the pre-machining part dimensions, it is shown how this information can be used to select from a pre-defined matrix of part programs to reduce cycle time and machining cost.

Research paper thumbnail of Chatter recognition by a statistical evaluation of the synchronously sampled audio signal

Research paper thumbnail of Variable Tuned Holder For Machine Tools

Research paper thumbnail of In situ monitoring and prediction of progressive joint wear using Bayesian statistics

Research paper thumbnail of TOOL LIFE PREDICTION USING RANDOM WALK BAYESIAN UPDATING

Http Dx Doi Org 10 1080 10910344 2013 806103, Jul 3, 2013

ABSTRACT According to the Taylor tool life equation, tool life reduces with increasing cutting sp... more ABSTRACT According to the Taylor tool life equation, tool life reduces with increasing cutting speed. The influence of additional factors can also be incorporated. However, tool wear is generally considered a stochastic process with uncertainty in the model constants. In this work, Bayesian inference is applied to predict tool life for milling/turning operations using the random walk/surface methods. For milling, Bayesian inference using a random walk approach is applied to the well-known Taylor tool life model. Tool wear tests are performed using an uncoated carbide tool and AISI 1018 steel work material. Test results are used to update the probability distribution of tool life. The updated beliefs are then applied to predict tool life using a probability distribution. For turning, both cutting speed and feed are considered. Bayesian updating is performed using the random surface technique. Turning tests are completed using a coated carbide tool and forged AISI 4137 chrome alloy steel. The test results are applied to update the probability distribution of tool life and the updated beliefs are used to predict tool life. While this work uses the Taylor model, by following the procedures described here, the technique can be applied to other tool life models as well.

Research paper thumbnail of A METHOD FOR PREDICTING CHATTER STABILITY FOR SYSTEMS WITH SPEED-DEPENDENT SPINDLE DYNAMICS

... Tony L. Schmitz, John C. Ziegert, Charles Stanislaus Department of Mechanical and Aerospace E... more ... Tony L. Schmitz, John C. Ziegert, Charles Stanislaus Department of Mechanical and Aerospace Engineering University of Florida Gainesville, FL KEYWORDS ... [1998], Davies et al. [1998], Schmitz and Donaldson [2000], Schmitz et al. [2001]), holder characteristics (Agapiou et al. ...

Research paper thumbnail of A Study of Linear Joint and Tool Models in Spindle-Holder-Tool Receptance Coupling

Volume 6: 5th International Conference on Multibody Systems, Nonlinear Dynamics, and Control, Parts A, B, and C, 2005

ABSTRACT

Research paper thumbnail of Improving the Fabrication Process of Micro-Air-Vehicle Flapping Wings

AIAA Journal, 2015

ABSTRACT The aerodynamic performance of flapping micro air vehicles in hover conditions is depend... more ABSTRACT The aerodynamic performance of flapping micro air vehicles in hover conditions is dependent on many parameters, including the wing design. With the goal of optimizing the wing for hover performance, the initial focus was to reduce the uncertainty in the thrust measurements. This is because lower uncertainty in this metric enables better resolution in comparing the performance of different designs. Aerodynamic performance variability was deemed to be the fault of an imprecise manufacturing technique. Therefore, adjustments were made to the fabrication process until a permissible level of uncertainty was attained for optimization; the goal was less than 5%. This paper chronicles the progression of the wing fabrication process and details how the uncertainty was evaluated. Four fabrication methods and two different wing designs are included in this study: a carbon fiber hand layup technique, carbon fiber cured in a machined mold, and two variations of a machined plastic skeleton reinforced with a carbon fiber rod. The uncertainty in thrust production, expressed in coefficient of variation, improved from 16.8% for the hand layup method to 2.6% for the computer numerically controlled plastic skeleton adhered to the nylon membrane with transfer tape. Additionally, the coefficient of variation for wing weight also reduced (from 11.4 to 2.0%). Read More: http://arc.aiaa.org/doi/abs/10.2514/1.J053884

Research paper thumbnail of UNCERTAINTY OF SPATIAL COORDINATE MEASUREMENTS USING TRILATERATION

Research paper thumbnail of Experimental validation of digital periodic error correction

Research paper thumbnail of DIGITAL PERIODIC ERROR CORRECTION: FURTHER TESTING AND RESULTS

Research paper thumbnail of Optimal Experimentation for Selecting Stable Milling Parameters: A Bayesian Approach

ASME 2009 International Manufacturing Science and Engineering Conference, Volume 1, 2009

Optimal Experimentation for Selecting Stable Milling Parameters: A Bayesian Approach. [ASME Confe... more Optimal Experimentation for Selecting Stable Milling Parameters: A Bayesian Approach. [ASME Conference Proceedings 2009, 277 (2009)]. Michael G. Traverso, Raúl Zapata, Tony L. Schmitz, Ali E. Abbas. Abstract. Bayesian ...

Research paper thumbnail of A Sapphire Based Fiber Optic Dynamic Pressure Sensor for Harsh Environments: Fabrication and Characterization

49th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition, 2011

Research paper thumbnail of Tool wear monitoring using naïve Bayes classifiers

The International Journal of Advanced Manufacturing Technology, 2014

ABSTRACT A naïve Bayes classifier method for tool condition monitoring is described. End-milling ... more ABSTRACT A naïve Bayes classifier method for tool condition monitoring is described. End-milling tests were performed at different spindle speeds and the cutting force was measured using a table-mounted dynamometer. The effect of tool wear on force features in the time and frequency domains was evaluated and used for training the classifier. The amount of tool wear was predicted using the naïve Bayes classifier method. Two cases are presented. First, the tool wear is divided into discrete states based on the amount of flank wear and the probability of the tool wear being in any state is updated using force data. Second, a continuous case is considered and the probability density function of the tool flank wear width is updated. The results are discussed.

Research paper thumbnail of Tool life prediction using Bayesian updating