Machining Dynamics and Parameters Process Optimization
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 simul...
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| Year of Publication: | 2021 |
| Language: | English |
| Physical Description: | 1 electronic resource (190 p.) |
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(CKB)5400000000042810 (oapen)https://directory.doabooks.org/handle/20.500.12854/68501 (EXLCZ)995400000000042810 |
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Urbicain, Gorka edt Machining Dynamics and Parameters Process Optimization Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021 1 electronic resource (190 p.) text txt rdacontent computer c rdamedia online resource cr rdacarrier 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. English History of engineering & technology bicssc 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 3-0365-0294-7 3-0365-0295-5 Olvera Trejo, Daniel edt Urbicain, Gorka oth Olvera Trejo, Daniel oth |
| language |
English |
| format |
eBook |
| author2 |
Olvera Trejo, Daniel Urbicain, Gorka Olvera Trejo, Daniel |
| author_facet |
Olvera Trejo, Daniel Urbicain, Gorka Olvera Trejo, Daniel |
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g u gu t d o td tdo |
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HerausgeberIn Sonstige Sonstige |
| title |
Machining Dynamics and Parameters Process Optimization |
| spellingShingle |
Machining Dynamics and Parameters Process Optimization |
| title_full |
Machining Dynamics and Parameters Process Optimization |
| title_fullStr |
Machining Dynamics and Parameters Process Optimization |
| title_full_unstemmed |
Machining Dynamics and Parameters Process Optimization |
| title_auth |
Machining Dynamics and Parameters Process Optimization |
| title_new |
Machining Dynamics and Parameters Process Optimization |
| title_sort |
machining dynamics and parameters process optimization |
| publisher |
MDPI - Multidisciplinary Digital Publishing Institute |
| publishDate |
2021 |
| physical |
1 electronic resource (190 p.) |
| isbn |
3-0365-0294-7 3-0365-0295-5 |
| illustrated |
Not Illustrated |
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Machining Dynamics and Parameters Process Optimization |
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