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Machining Dynamics and Parameters Process Optimization



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Autore: Urbicain Gorka Visualizza persona
Titolo: Machining Dynamics and Parameters Process Optimization Visualizza cluster
Pubblicazione: Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Descrizione fisica: 1 online resource (190 p.)
Soggetto topico: History of engineering and technology
Soggetto non controllato: additive manufacturing
AI
autoencoder
B-spline curve-fitting
bull-nose end mill
chatter
CNC parameters
CNN
complex part
deep learning
deep multi-layer perceptron
dynamic performance
dynamics
evolution algorithms
feedrate scheduling
five-axis linear-segment toolpath
flute-grinding
grinding
high accuracy
high speed
high surface quality
homotopy perturbation method
Industry 4.0
machine learning
machining
machining cycle optimization
machining mode
machining robot
magnetorheological damper
milling
model optimization
multivariable tool
n/a
natural frequency prediction
path smoothing
path synchronization
stability
stable peninsula
thin walled machining
thin-floor machining
tool change policy
tool condition monitoring
tool wear monitoring
wheel location and orientation
Persona (resp. second.): Olvera TrejoDaniel
UrbicainGorka
Sommario/riassunto: As we move further into the 21st century, despite the fact that new technologies have emerged, machining remains the key operation to achieve high productivity and precision for high-added value parts in several sectors, but recent advances in computer applications should close the gap between simulations and industrial practices. This book, "Machining Dynamics and Parameters Process Optimization", is oriented toward the different strategies and paths when it comes to increasing productivity and reliability in metal removal processes. The topics include the dynamic characterization of machine tools, experimental dampening techniques, and optimization algorithms combined with signal monitoring.
Titolo autorizzato: Machining Dynamics and Parameters Process Optimization  Visualizza cluster
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910557304603321
Lo trovi qui: Univ. Federico II
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