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Machining remains one of the most important manufacturing processes in the metalworking industry. Studies on this process have investigated the machinability of different materials, the behaviour of tools, chip formation, surface integrity, forces involved, and its economic and environmental sustainability. New materials are constantly being developed, and machining research needs to closely follow these developments. This book examines recent research in the machining field, covering several aspects and presenting very interesting developments in this area of knowledge.
Technology: general issues --- magnesium alloy --- UNS M11917 --- AZ91D --- hole repair --- surface roughness --- dry drilling --- re-drilling --- thin plates --- thin-wall --- machining --- aluminium --- cutting forces --- roughness --- dry --- carbide tool --- Haynes 282 --- finishing turning --- UNS A97075 --- dry turning --- surface integrity --- straightness --- parallelism --- roundness --- concentricity --- circular run-out --- total run-out --- cylindricity --- tool edge preparation --- segmented chip --- machining simulation --- burr --- optimization --- turning process --- turning tools --- solid tools --- cemented carbide --- coated tools --- coated cemented carbide --- Physical Vapor Deposition (PVD) --- Chemical Vapor Deposition (CVD) --- multilayered coatings --- nanolayered coatings --- wear mechanism --- tool life --- minimum quantity Lubricant (MQL) --- cutting energy --- tool damage --- liquid nitrogen --- carbon dioxide snow --- vibrations --- part quality --- flexible vacuum fixture --- AA2024 floor milling --- chip segmentation --- damage modeling --- dynamic strain aging --- stainless steel --- Ca treatment --- machinability --- turning --- chip breakability --- weight distribution --- non-metallic inclusions --- AWJM (abrasive water jet machining) --- CFRTP (carbon fiber-reinforced thermoplastics) --- hybrid structure --- surface quality --- Ra --- Rz --- C/TPU (carbon/thermoplastic polyurethane) --- milling --- tool coating --- TiAlN --- TiAlN-based coatings --- multilayer --- nanolayer --- wear mechanisms --- n/a
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Machining remains one of the most important manufacturing processes in the metalworking industry. Studies on this process have investigated the machinability of different materials, the behaviour of tools, chip formation, surface integrity, forces involved, and its economic and environmental sustainability. New materials are constantly being developed, and machining research needs to closely follow these developments. This book examines recent research in the machining field, covering several aspects and presenting very interesting developments in this area of knowledge.
magnesium alloy --- UNS M11917 --- AZ91D --- hole repair --- surface roughness --- dry drilling --- re-drilling --- thin plates --- thin-wall --- machining --- aluminium --- cutting forces --- roughness --- dry --- carbide tool --- Haynes 282 --- finishing turning --- UNS A97075 --- dry turning --- surface integrity --- straightness --- parallelism --- roundness --- concentricity --- circular run-out --- total run-out --- cylindricity --- tool edge preparation --- segmented chip --- machining simulation --- burr --- optimization --- turning process --- turning tools --- solid tools --- cemented carbide --- coated tools --- coated cemented carbide --- Physical Vapor Deposition (PVD) --- Chemical Vapor Deposition (CVD) --- multilayered coatings --- nanolayered coatings --- wear mechanism --- tool life --- minimum quantity Lubricant (MQL) --- cutting energy --- tool damage --- liquid nitrogen --- carbon dioxide snow --- vibrations --- part quality --- flexible vacuum fixture --- AA2024 floor milling --- chip segmentation --- damage modeling --- dynamic strain aging --- stainless steel --- Ca treatment --- machinability --- turning --- chip breakability --- weight distribution --- non-metallic inclusions --- AWJM (abrasive water jet machining) --- CFRTP (carbon fiber-reinforced thermoplastics) --- hybrid structure --- surface quality --- Ra --- Rz --- C/TPU (carbon/thermoplastic polyurethane) --- milling --- tool coating --- TiAlN --- TiAlN-based coatings --- multilayer --- nanolayer --- wear mechanisms --- n/a
Choose an application
Machining remains one of the most important manufacturing processes in the metalworking industry. Studies on this process have investigated the machinability of different materials, the behaviour of tools, chip formation, surface integrity, forces involved, and its economic and environmental sustainability. New materials are constantly being developed, and machining research needs to closely follow these developments. This book examines recent research in the machining field, covering several aspects and presenting very interesting developments in this area of knowledge.
Technology: general issues --- magnesium alloy --- UNS M11917 --- AZ91D --- hole repair --- surface roughness --- dry drilling --- re-drilling --- thin plates --- thin-wall --- machining --- aluminium --- cutting forces --- roughness --- dry --- carbide tool --- Haynes 282 --- finishing turning --- UNS A97075 --- dry turning --- surface integrity --- straightness --- parallelism --- roundness --- concentricity --- circular run-out --- total run-out --- cylindricity --- tool edge preparation --- segmented chip --- machining simulation --- burr --- optimization --- turning process --- turning tools --- solid tools --- cemented carbide --- coated tools --- coated cemented carbide --- Physical Vapor Deposition (PVD) --- Chemical Vapor Deposition (CVD) --- multilayered coatings --- nanolayered coatings --- wear mechanism --- tool life --- minimum quantity Lubricant (MQL) --- cutting energy --- tool damage --- liquid nitrogen --- carbon dioxide snow --- vibrations --- part quality --- flexible vacuum fixture --- AA2024 floor milling --- chip segmentation --- damage modeling --- dynamic strain aging --- stainless steel --- Ca treatment --- machinability --- turning --- chip breakability --- weight distribution --- non-metallic inclusions --- AWJM (abrasive water jet machining) --- CFRTP (carbon fiber-reinforced thermoplastics) --- hybrid structure --- surface quality --- Ra --- Rz --- C/TPU (carbon/thermoplastic polyurethane) --- milling --- tool coating --- TiAlN --- TiAlN-based coatings --- multilayer --- nanolayer --- wear mechanisms --- magnesium alloy --- UNS M11917 --- AZ91D --- hole repair --- surface roughness --- dry drilling --- re-drilling --- thin plates --- thin-wall --- machining --- aluminium --- cutting forces --- roughness --- dry --- carbide tool --- Haynes 282 --- finishing turning --- UNS A97075 --- dry turning --- surface integrity --- straightness --- parallelism --- roundness --- concentricity --- circular run-out --- total run-out --- cylindricity --- tool edge preparation --- segmented chip --- machining simulation --- burr --- optimization --- turning process --- turning tools --- solid tools --- cemented carbide --- coated tools --- coated cemented carbide --- Physical Vapor Deposition (PVD) --- Chemical Vapor Deposition (CVD) --- multilayered coatings --- nanolayered coatings --- wear mechanism --- tool life --- minimum quantity Lubricant (MQL) --- cutting energy --- tool damage --- liquid nitrogen --- carbon dioxide snow --- vibrations --- part quality --- flexible vacuum fixture --- AA2024 floor milling --- chip segmentation --- damage modeling --- dynamic strain aging --- stainless steel --- Ca treatment --- machinability --- turning --- chip breakability --- weight distribution --- non-metallic inclusions --- AWJM (abrasive water jet machining) --- CFRTP (carbon fiber-reinforced thermoplastics) --- hybrid structure --- surface quality --- Ra --- Rz --- C/TPU (carbon/thermoplastic polyurethane) --- milling --- tool coating --- TiAlN --- TiAlN-based coatings --- multilayer --- nanolayer --- wear mechanisms
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As computer and space technologies have been developed, geoscience information systems (GIS) and remote sensing (RS) technologies, which deal with the geospatial information, have been rapidly maturing. Moreover, over the last few decades, machine learning techniques including artificial neural network (ANN), deep learning, decision tree, and support vector machine (SVM) have been successfully applied to geospatial science and engineering research fields. The machine learning techniques have been widely applied to GIS and RS research fields and have recently produced valuable results in the areas of geoscience, environment, natural hazards, and natural resources. This book is a collection representing novel contributions detailing machine learning techniques as applied to geoscience information systems and remote sensing.
artificial neural network --- n/a --- model switching --- sensitivity analysis --- neural networks --- logit boost --- Qaidam Basin --- land subsidence --- land use/land cover (LULC) --- naïve Bayes --- multilayer perceptron --- convolutional neural networks --- single-class data descriptors --- logistic regression --- feature selection --- mapping --- particulate matter 10 (PM10) --- Bayes net --- gray-level co-occurrence matrix --- multi-scale --- Logistic Model Trees --- classification --- Panax notoginseng --- large scene --- coarse particle --- grayscale aerial image --- Gaofen-2 --- environmental variables --- variable selection --- spatial predictive models --- weights of evidence --- landslide prediction --- random forest --- boosted regression tree --- convolutional network --- Vietnam --- model validation --- colorization --- data mining techniques --- spatial predictions --- SCAI --- unmanned aerial vehicle --- high-resolution --- texture --- spatial sparse recovery --- landslide susceptibility map --- machine learning --- reproducible research --- constrained spatial smoothing --- support vector machine --- random forest regression --- model assessment --- information gain --- ALS point cloud --- bagging ensemble --- one-class classifiers --- leaf area index (LAI) --- landslide susceptibility --- landsat image --- ionospheric delay constraints --- spatial spline regression --- remote sensing image segmentation --- panchromatic --- Sentinel-2 --- remote sensing --- optical remote sensing --- materia medica resource --- GIS --- precise weighting --- change detection --- TRMM --- traffic CO --- crop --- training sample size --- convergence time --- object detection --- gully erosion --- deep learning --- classification-based learning --- transfer learning --- landslide --- traffic CO prediction --- hybrid model --- winter wheat spatial distribution --- logistic --- alternating direction method of multipliers --- hybrid structure convolutional neural networks --- geoherb --- predictive accuracy --- real-time precise point positioning --- spectral bands --- naïve Bayes
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