Computer-Aided Manufacturing and Design
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| Author: |
Choi Seung-Kyum
|
| Title: |
Computer-Aided Manufacturing and Design
|
| Publisher: | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Physical description: | 1 online resource (198 p.) |
| Topical subject: | History of engineering and technology |
| Uncontrolled subject: | additive manufacturing |
| algorithmic approach | |
| anthropometric measures | |
| assemblability | |
| automatic design | |
| availability | |
| birefringence | |
| CFD | |
| complexity | |
| convolutional neural network | |
| coordination space | |
| data-driven design | |
| design of experiments | |
| dimension reduction | |
| entropy theory | |
| entropy-based correlation coefficient | |
| field repair kit | |
| fluid machinery | |
| fringe pattern | |
| gradient-based algorithm | |
| integrated decision system | |
| intelligent optimization method | |
| Kansei Engineering | |
| Kriging | |
| lower confidence bounding | |
| measurement-assisted assembly | |
| mismatch equation | |
| modular design | |
| multi-function console | |
| multidisciplinary design and analysis | |
| n/a | |
| object detection | |
| optimal design | |
| part consolidation | |
| piping and instrument diagram | |
| product design | |
| product image design | |
| product recovery | |
| product service system (PSS) | |
| pumps | |
| qualitative decision model | |
| quantitative decision model | |
| robust genetic algorithm | |
| simulation-based design optimization | |
| small displacement torsor | |
| stretchable antenna-based strain sensor | |
| structural health monitoring | |
| structural optimization | |
| train seats | |
| uncertainty-integrated and machine learning-based surrogate modeling | |
| unsupervised learning | |
| warpage | |
| Person (second resp.): | GorguluarslanRecep M |
| ZhouQi | |
| ChoiSeung-Kyum | |
| Summary, etc: | 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. |
| Preferred title for the work: | Computer-Aided Manufacturing and Design |
| Format: | Language material  |
| Bibliographic level | Monograph |
| Language: | English |
| Record Nr.: | 9910557700003321 |
| You will find it: | Univ. Federico II |
| Opac: | Check copies here |