TY - BOOK ID - 134239141 TI - Computer-Aided Manufacturing and Design AU - Choi, Seung-Kyum AU - Gorguluarslan, Recep M. AU - Zhou, Qi PY - 2020 PB - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute DB - UniCat KW - History of engineering & technology KW - product service system (PSS) KW - availability KW - field repair kit KW - gradient-based algorithm KW - robust genetic algorithm KW - warpage KW - design of experiments KW - fringe pattern KW - birefringence KW - automatic design KW - intelligent optimization method KW - CFD KW - fluid machinery KW - pumps KW - multi-function console KW - data-driven design KW - mismatch equation KW - anthropometric measures KW - algorithmic approach KW - optimal design KW - stretchable antenna-based strain sensor KW - structural optimization KW - structural health monitoring KW - dimension reduction KW - entropy-based correlation coefficient KW - multidisciplinary design and analysis KW - uncertainty-integrated and machine learning-based surrogate modeling KW - additive manufacturing KW - complexity KW - modular design KW - part consolidation KW - product recovery KW - product image design KW - Kansei Engineering KW - integrated decision system KW - qualitative decision model KW - quantitative decision model KW - train seats KW - measurement-assisted assembly KW - coordination space KW - assemblability KW - small displacement torsor KW - Kriging KW - lower confidence bounding KW - entropy theory KW - product design KW - simulation-based design optimization KW - convolutional neural network KW - object detection KW - piping and instrument diagram KW - unsupervised learning KW - n/a UR - https://www.unicat.be/uniCat?func=search&query=sysid:134239141 AB - 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. ER -