Reprint
Computer-Aided Manufacturing and Design
Edited by
November 2020
198 pages
- ISBN978-3-03943-134-2 (Hardback)
- ISBN978-3-03943-135-9 (PDF)
This book is a reprint of the Special Issue Computer-Aided Manufacturing and Design that was published in
Biology & Life Sciences
Chemistry & Materials Science
Computer Science & Mathematics
Engineering
Environmental & Earth Sciences
Physical Sciences
Summary
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.
Format
- Hardback
License
© 2021 by the authors; CC BY license
Keywords
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; n/a