Computer-Aided Manufacturing and Design
Choi, Seung-Kyum (editor)
Gorguluarslan, Recep M. (editor)
Zhou, Qi (editor)
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.
Keywordsproduct 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
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Publication date and placeBasel, Switzerland, 2020
History of engineering & technology