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A Numerical and Experimental Investigation of Period-n Bifurcations in Milling
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Numerical and experimental analyses of milling bifurcations, or instabilities, are detailed. The time-delay equations of motions that describe milling behavior are solved numerically and once-per-tooth period sampling is ...
Process Damping Identification Using Bayesian Learning and Time Domain Simulation
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Process damping can provide improved machining productivity by increasing the stability limit at low spindle speeds. While the phenomenon is well known, experimental identification of process damping model parameters can ...
Milling Bifurcations: A Review of Literature and Experiment
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: This review paper presents a comprehensive analysis of period-n (i.e., motion that repeats every n tooth periods) bifurcations in milling. Although period-n bifurcations in milling were only first reported experimentally ...
A New Metric for Automated Stability Identification in Time Domain Milling Simulation
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: A new metric is presented to automatically establish the stability limit for time domain milling simulation signals. It is based on periodically sampled data. Because stable cuts exhibit forced vibration, the sampled points ...
Milling Stability Interrogation by Subharmonic Sampling
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: This paper describes the use of subharmonic sampling to distinguish between different instability types in milling. It is demonstrated that sampling time-domain milling signals at integer multiples of the tooth period ...
Surface Location Error and Surface Roughness for Period-N Milling Bifurcations
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: This paper provides time domain simulation and experimental results for surface location error (SLE) and surface roughness when machining under both stable (forced vibration) and unstable (period-2 bifurcation) conditions. ...
AFSD-Nets: A Physics-Informed Machine Learning Model for Predicting the Temperature Evolution During Additive Friction Stir Deposition
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: This study models the temperature evolution during additive friction stir deposition (AFSD) using machine learning. AFSD is a solid-state additive manufacturing technology that deposits metal using plastic flow without ...
Application of Bayesian Inference to Milling Force Modeling
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: This paper describes the application of Bayesian inference to the identification of force coefficients in milling. Mechanistic cutting force coefficients have been traditionally determined by performing a linear regression ...
Control of Lay on Cobalt Chromium Alloy Finished Surfaces Using Magnetic Abrasive Finishing and Its Effect on Wettability
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Freeform surfaces, including the femoral components of knee prosthetics, present a significant challenge in manufacturing. The finishing process is often performed manually, which leads to surface finish variations. In the ...
Bayesian Inference for Milling Stability Using a Random Walk Approach
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Unstable cutting conditions limit the profitability in milling. While analytical and numerical approaches for estimating the limiting axial depth of cut as a function of spindle speed are available, they are generally ...