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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.

History of engineering & technology --- CNC parameters --- machining mode --- high speed --- high accuracy --- high surface quality --- five-axis linear-segment toolpath --- path smoothing --- B-spline curve-fitting --- path synchronization --- feedrate scheduling --- flute-grinding --- evolution algorithms --- wheel location and orientation --- thin-floor machining --- chatter --- magnetorheological damper --- bull-nose end mill --- tool wear monitoring --- milling --- complex part --- deep learning --- autoencoder --- deep multi-layer perceptron --- tool condition monitoring --- tool change policy --- Industry 4.0 --- machine learning --- CNN --- AI --- additive manufacturing --- thin walled machining --- dynamics --- machining cycle optimization --- multivariable tool --- stable peninsula --- homotopy perturbation method --- machining robot --- natural frequency prediction --- model optimization --- dynamic performance --- stability --- machining --- grinding --- n/a

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

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.

CNC parameters --- machining mode --- high speed --- high accuracy --- high surface quality --- five-axis linear-segment toolpath --- path smoothing --- B-spline curve-fitting --- path synchronization --- feedrate scheduling --- flute-grinding --- evolution algorithms --- wheel location and orientation --- thin-floor machining --- chatter --- magnetorheological damper --- bull-nose end mill --- tool wear monitoring --- milling --- complex part --- deep learning --- autoencoder --- deep multi-layer perceptron --- tool condition monitoring --- tool change policy --- Industry 4.0 --- machine learning --- CNN --- AI --- additive manufacturing --- thin walled machining --- dynamics --- machining cycle optimization --- multivariable tool --- stable peninsula --- homotopy perturbation method --- machining robot --- natural frequency prediction --- model optimization --- dynamic performance --- stability --- machining --- grinding --- n/a