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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.
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
Choose an application
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.
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
Choose an application
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.
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 --- 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
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