LEADER 04699nam 2201009z- 450 001 9910580213603321 005 20220706 035 $a(CKB)5690000000011952 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/87488 035 $a(oapen)doab87488 035 $a(EXLCZ)995690000000011952 100 $a20202207d2022 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aAlgorithms and Methods for Designing and Scheduling Smart Manufacturing Systems 210 $aBasel$cMDPI - Multidisciplinary Digital Publishing Institute$d2022 215 $a1 online resource (200 p.) 311 08$a3-0365-4509-3 311 08$a3-0365-4510-7 330 $aThis book, as a Special Issue, is a collection of some of the latest advancements in designing and scheduling smart manufacturing systems. The smart manufacturing concept is undoubtedly considered a paradigm shift in manufacturing technology. This conception is part of the Industry 4.0 strategy, or equivalent national policies, and brings new challenges and opportunities for the companies that are facing tough global competition. Industry 4.0 should not only be perceived as one of many possible strategies for manufacturing companies, but also as an important practice within organizations. The main focus of Industry 4.0 implementation is to combine production, information technology, and the internet. The presented Special Issue consists of ten research papers presenting the latest works in the field. The papers include various topics, which can be divided into three categories-(i) designing and scheduling manufacturing systems (seven articles), (ii) machining process optimization (two articles), (iii) digital insurance platforms (one article). Most of the mentioned research problems are solved in these articles by using genetic algorithms, the harmony search algorithm, the hybrid bat algorithm, the combined whale optimization algorithm, and other optimization and decision-making methods. The above-mentioned groups of articles are briefly described in this order in this book. 606 $aHistory of engineering and technology$2bicssc 606 $aTechnology: general issues$2bicssc 610 $aassembly line balancing 610 $aBaltic 610 $abottleneck station 610 $acandidate order-based genetic algorithm 610 $acell formation 610 $acell manufacturing design 610 $acluster algorithm 610 $acombinatorial optimization 610 $acustomization 610 $acutting force 610 $adecision-making 610 $adesign of experiments 610 $adigital platforms 610 $aelectrochemical machining (ECM) 610 $afacility layout 610 $aflexible job-shop scheduling problem 610 $agenetic algorithm 610 $agrass-hooper optimization algorithm 610 $agrey wolf optimizer (GWO) 610 $agroup technology 610 $aharmony search algorithm 610 $aHastelloy X 610 $aheuristic approach 610 $ahybrid bat algorithm 610 $ainsurance 610 $aliquid nitrogen 610 $amachine and process selection 610 $amakespan 610 $amaterial removal rate (MRR) 610 $ametaheuristic algorithm 610 $aMonel 400 alloys 610 $amoth-flame optimization algorithm 610 $amoth-flame optimization algorithm (MFO) 610 $amulti-criteria assessment 610 $amultichromosome 610 $an/a 610 $anickel presence (NP) 610 $aoperational complexity 610 $aoptimization 610 $aoptimization problem 610 $aoutput rate 610 $aoverrunning clutch assembly 610 $apersonalization 610 $aproduction line balancing rate 610 $aselective assembly 610 $asurface roughness 610 $athe distributed assembly permutation flowshop scheduling problem 610 $atolerance allocation 610 $aturning 610 $aunivariate search method 610 $avariable neighborhood descent 610 $awhale optimization algorithm 615 7$aHistory of engineering and technology 615 7$aTechnology: general issues 700 $aModrak$b Vladimir$4edt$01297587 702 $aSoltysova$b Zuzana$4edt 702 $aModrak$b Vladimir$4oth 702 $aSoltysova$b Zuzana$4oth 906 $aBOOK 912 $a9910580213603321 996 $aAlgorithms and Methods for Designing and Scheduling Smart Manufacturing Systems$93024579 997 $aUNINA