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Cyber-Physical Systems: A Model-Based Approach

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ISBN: 9783030360719 Year: Pages: 187 DOI: 10.1007/978-3-030-36071-9 Language: English
Publisher: Springer Nature
Subject: Computer Science --- Agriculture (General)
Added to DOAB on : 2020-09-23 00:03:28
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In this concise yet comprehensive Open Access textbook, future inventors are introduced to the key concepts of Cyber-Physical Systems (CPS). Using modeling as a way to develop deeper understanding of the computational and physical components of these systems, one can express new designs in a way that facilitates their simulation, visualization, and analysis. Concepts are introduced in a cross-disciplinary way. Leveraging hybrid (continuous/discrete) systems as a unifying framework and Acumen as a modeling environment, the book bridges the conceptual gap in modeling skills needed for physical systems on the one hand and computational systems on the other. In doing so, the book gives the reader the modeling and design skills they need to build smart, IT-enabled products. Starting with a look at various examples and characteristics of Cyber-Physical Systems, the book progresses to explain how the area brings together several previously distinct ones such as Embedded Systems, Control Theory, and Mechatronics. Featuring a simulation-based project that focuses on a robotics problem (how to design a robot that can play ping-pong) as a useful example of a CPS domain, Cyber-Physical Systems: A Model-Based Approach demonstrates the intimate coupling between cyber and physical components, and how designing robots reveals several non-trivial control problems, significant embedded and real-time computation requirements, and a need to consider issues of communication and preconceptions.

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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