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Autore: | Choi Seung-Kyum |
Titolo: | Computer-Aided Manufacturing and Design |
Pubblicazione: | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
Descrizione fisica: | 1 electronic resource (198 p.) |
Soggetto topico: | History of engineering & technology |
Soggetto non controllato: | product service system (PSS) |
availability | |
field repair kit | |
gradient-based algorithm | |
robust genetic algorithm | |
warpage | |
design of experiments | |
fringe pattern | |
birefringence | |
automatic design | |
intelligent optimization method | |
CFD | |
fluid machinery | |
pumps | |
multi-function console | |
data-driven design | |
mismatch equation | |
anthropometric measures | |
algorithmic approach | |
optimal design | |
stretchable antenna-based strain sensor | |
structural optimization | |
structural health monitoring | |
dimension reduction | |
entropy-based correlation coefficient | |
multidisciplinary design and analysis | |
uncertainty-integrated and machine learning-based surrogate modeling | |
additive manufacturing | |
complexity | |
modular design | |
part consolidation | |
product recovery | |
product image design | |
Kansei Engineering | |
integrated decision system | |
qualitative decision model | |
quantitative decision model | |
train seats | |
measurement-assisted assembly | |
coordination space | |
assemblability | |
small displacement torsor | |
Kriging | |
lower confidence bounding | |
entropy theory | |
product design | |
simulation-based design optimization | |
convolutional neural network | |
object detection | |
piping and instrument diagram | |
unsupervised learning | |
Persona (resp. second.): | GorguluarslanRecep M |
ZhouQi | |
ChoiSeung-Kyum | |
Sommario/riassunto: | Recent advancements in computer technology have allowed for designers to have direct control over the production process through the help of computer-based tools, creating the possibility of a completely integrated design and manufacturing process. Over the last few decades, "artificial intelligence" (AI) techniques, such as machine learing and deep learning, have been topics of interest in computer-based design and manufacturing research fields. However, efforts to develop computer-based AI to handle big data in design and manufacturing have not yet been successful. This Special Issue aims to collect novel articles covering artificial intelligence-based design, manufacturing, and data-driven design. It will comprise academics, researchers, mechanical, manufacturing, production and industrial engineers and professionals related to engineering design and manufacturing. |
Titolo autorizzato: | Computer-Aided Manufacturing and Design |
Formato: | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 9910557700003321 |
Lo trovi qui: | Univ. Federico II |
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