LEADER 04032nam 2200985z- 450 001 9910557700003321 005 20231214132857.0 035 $a(CKB)5400000000044557 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/69317 035 $a(EXLCZ)995400000000044557 100 $a20202105d2020 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aComputer-Aided Manufacturing and Design 210 $aBasel, Switzerland$cMDPI - Multidisciplinary Digital Publishing Institute$d2020 215 $a1 electronic resource (198 p.) 311 $a3-03943-134-X 311 $a3-03943-135-8 330 $aRecent 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. 606 $aHistory of engineering & technology$2bicssc 610 $aproduct service system (PSS) 610 $aavailability 610 $afield repair kit 610 $agradient-based algorithm 610 $arobust genetic algorithm 610 $awarpage 610 $adesign of experiments 610 $afringe pattern 610 $abirefringence 610 $aautomatic design 610 $aintelligent optimization method 610 $aCFD 610 $afluid machinery 610 $apumps 610 $amulti-function console 610 $adata-driven design 610 $amismatch equation 610 $aanthropometric measures 610 $aalgorithmic approach 610 $aoptimal design 610 $astretchable antenna-based strain sensor 610 $astructural optimization 610 $astructural health monitoring 610 $adimension reduction 610 $aentropy-based correlation coefficient 610 $amultidisciplinary design and analysis 610 $auncertainty-integrated and machine learning-based surrogate modeling 610 $aadditive manufacturing 610 $acomplexity 610 $amodular design 610 $apart consolidation 610 $aproduct recovery 610 $aproduct image design 610 $aKansei Engineering 610 $aintegrated decision system 610 $aqualitative decision model 610 $aquantitative decision model 610 $atrain seats 610 $ameasurement-assisted assembly 610 $acoordination space 610 $aassemblability 610 $asmall displacement torsor 610 $aKriging 610 $alower confidence bounding 610 $aentropy theory 610 $aproduct design 610 $asimulation-based design optimization 610 $aconvolutional neural network 610 $aobject detection 610 $apiping and instrument diagram 610 $aunsupervised learning 615 7$aHistory of engineering & technology 700 $aChoi$b Seung-Kyum$4edt$01323484 702 $aGorguluarslan$b Recep M$4edt 702 $aZhou$b Qi$4edt 702 $aChoi$b Seung-Kyum$4oth 702 $aGorguluarslan$b Recep M$4oth 702 $aZhou$b Qi$4oth 906 $aBOOK 912 $a9910557700003321 996 $aComputer-Aided Manufacturing and Design$93035610 997 $aUNINA