Computer-Aided Manufacturing and Design

• Other Authors: Choi, Seung-Kyum (Editor), Gorguluarslan, Recep M. (Editor), Zhou, Qi (Editor)
• Format: Electronic Book Chapter
• Language: English
• Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2020
• Subjects: History of engineering & technology; 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
• Online Access: DOAB: download the publication; DOAB: description of the publication

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.