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Combined Scheduling and Control

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ISBN: 9783038428053 9783038428060 Year: Pages: VIII, 166 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Computer Science --- Business and Management
Added to DOAB on : 2018-04-13 15:56:34
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Scheduling and control are typically viewed as separate applications because of historical factors such as limited computing resources. Now that algorithms and computing resources have advanced, there are new efforts to have short-term decisions (control) interact or merge with longer-term decisions (scheduling). A new generation of numerical optimization methods are evolving to capture additional benefits and unify the approach to manufacturing process automation. This special issue is a collection of some of the latest advancements in scheduling and control for both batch and continuous processes. It contains developments with multi-scale problem formulation, software for the new class of problems, and a survey of the strengths and weaknesses of successive levels of integration.

Industry 4.0 and Regional Transformations

Authors: ---
ISBN: 9780367178413 Year: Pages: 276 Language: English
Publisher: Taylor & Francis
Subject: Economics --- Business and Management --- Manufactures --- Geology --- Earth Sciences --- Science (General)
Added to DOAB on : 2020-05-04 10:28:16
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This volume brings together expert contributors to explore opportunities and challenges that Industry 4.0 is likely to pose for regions, firms and jobs in Europe. Drawing on theory and empirical cases, it considers emerging issues like servitization, new innovation models for local production systems, and the increase in reshoring.

New Industry 4.0 Advances in Industrial IoT and Visual Computing for Manufacturing Processes

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ISBN: 9783039282906 9783039282913 Year: Pages: 428 DOI: 10.3390/books978-3-03928-291-3 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering --- Industrial Engineering
Added to DOAB on : 2020-04-07 23:07:09
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Modern factories are experiencing rapid digital transformation supported by emerging technologies, such as the Industrial Internet of things (IIOT), industrial big data and cloud technologies, deep learning and deep analytics, AI, intelligent robotics, cyber-physical systems and digital twins, complemented by visual computing (including new forms of artificial vision with machine learning, novel HMI, simulation, and visualization). This is evident in the global trend of Industry 4.0. The impact of these technologies is clear in the context of high-performance manufacturing. Important improvements can be achieved in productivity, systems reliability, quality verification, etc. Manufacturing processes, based on advanced mechanical principles, are enhanced by big data analytics on industrial sensor data. In current machine tools and systems, complex sensors gather useful data, which is captured, stored, and processed with edge, fog, or cloud computing. These processes improve with digital monitoring, visual data analytics, AI, and computer vision to achieve a more productive and reliable smart factory. New value chains are also emerging from these technological changes. This book addresses these topics, including contributions deployed in production, as well as general aspects of Industry 4.0.

Keywords

cutting insert selection --- cutting parameter optimization --- artificial neural networks --- genetic algorithm --- connected enterprise --- smart manufacturing --- big data --- machine learning --- data reduction --- predictive analytics --- in-line dimensional inspection --- warm forming --- 3D mesh reconstruction --- optical system --- revolution workpiece --- defect detection --- polymer lithium-ion battery --- convolutional neural network --- deep learning --- blister defect --- flower pollination algorithm --- Industry 4.0 --- anomaly detection --- scheduling --- neural network --- skyline queries --- Cyber-Physical Systems (CPS) --- scalability test --- Internet of Things (IoT) --- INDUSTRY 4.0 --- economic recession --- research and development indicators --- maintenance expert --- competence --- decision support --- micro-armature --- defect detection --- convolutional neural networks --- computer vision --- capacity control --- job shop systems --- RMTs --- operator theory --- 4th industrial revolution --- industry 4.0 --- AHP --- QFD --- matching --- fibre of preserved Szechuan pickle --- contour detection --- dilated convolutions --- HED --- social network --- industry 4.0 --- industrial knowledge graph --- deep learning --- industrial big data --- intellectualization of industrial information --- digital manufacturing --- smart factory --- Industry 4.0 --- digital platforms --- automated surface inspection --- D-VGG16 --- bilinear model --- Grad-CAM --- classification --- localization --- elliptical paraboloid array --- self-calibration method --- vertex distance --- optical slope sensor --- geometric relationship --- relative angle --- fabric defect detection --- LGM --- FCM --- image smoothing --- Industry 4.0 --- marketing innovations --- innovative marketing tools --- impacts marketing innovations --- Industry 4.0 --- configure-to-order --- BIM --- construction equipment --- digital information flow --- lean assembly --- digital twins --- cyber-physical production systems --- depthwise separable convolution --- YOLOv3 --- feature pyramid --- aircraft structure crack detection --- industrial load management --- demand-side management --- demand-side response --- energy flexibility --- IT concept --- platform-based ecosystem --- control service --- smart service --- control as a service --- cloud-based control system --- automation system --- chatter --- train wheel --- smart system --- turning --- edge computing --- n/a

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