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

• Format: eBook
• Language: English
• Published: MDPI - Multidisciplinary Digital Publishing Institute 2020
• Subjects: History of engineering and technology; 3D mesh reconstruction; 4th industrial revolution; AHP; aircraft structure crack detection; anomaly detection; artificial neural networks; automated surface inspection; automation system; big data; bilinear model; BIM; blister defect; capacity control; chatter; classification; cloud-based control system; competence; computer vision; configure-to-order; connected enterprise; construction equipment; contour detection; control as a service; control service; convolutional neural network; convolutional neural networks; cutting insert selection; cutting parameter optimization; cyber-physical production systems; Cyber-Physical Systems (CPS); D-VGG16; data reduction; decision support; deep learning; defect detection; demand-side management; demand-side response; depthwise separable convolution; digital information flow; digital manufacturing; digital platforms; digital twins; dilated convolutions; economic recession; edge computing; elliptical paraboloid array; energy flexibility; fabric defect detection; FCM; feature pyramid; fibre of preserved Szechuan pickle; flower pollination algorithm; genetic algorithm; geometric relationship; Grad-CAM; HED; image smoothing; impacts marketing innovations; in-line dimensional inspection; industrial big data; industrial knowledge graph; industrial load management; industry 4.0; Industry 4.0; INDUSTRY 4.0; innovative marketing tools; intellectualization of industrial information; Internet of Things (IoT); IT concept; job shop systems; lean assembly; LGM; localization; machine learning; maintenance expert; marketing innovations; matching; micro-armature; n/a; neural network; operator theory; optical slope sensor; optical system; platform-based ecosystem; polymer lithium-ion battery; predictive analytics; QFD; relative angle; research and development indicators; revolution workpiece; RMTs; scalability test; scheduling; self-calibration method; skyline queries; smart factory; smart manufacturing; smart service; smart system; social network; train wheel; turning; vertex distance; warm forming; YOLOv3
• Online Access: Open Access: DOAB: description of the publication; Open Access: DOAB, download the publication

 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.