New Industry 4.0 Advances in Industrial IoT and Visual Computing for Manufacturing Processes / / Luis Norberto López de Lacalle, Jorge Posada.

• VerfasserIn: Lacalle, Luis Norberto López de,; Posada, Jorge,
• TeilnehmendeR: Posada, Jorge,
• Place / Publishing House: Basel : : MDPI - Multidisciplinary Digital Publishing Institute,, 2020.
• Year of Publication: 2020
• Language: English
• Physical Description: 1 online resource (428 pages)

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.

Table of Contents

About the Special Issue Editors -- Luis Norberto L ´opez de Lacalle and Jorge Posada Special Issue on New Industry 4.0 Advances in Industrial IoT and Visual Computing for Manufacturing Processes Reprinted from: Appl. Sci. 2019 -- Phillip M. LaCasse, Wilkistar Otieno and Francisco P. Maturana A Survey of Feature Set Reduction Approaches for Predictive Analytics Models in the Connected Manufacturing Enterprise Reprinted from: Appl. Sci. 2019 -- Reinhard Langmann and Michael Stiller The PLC as a Smart Service in Industry 4.0 Production Systems † Reprinted from: Appl. Sci. 2019 -- Martin Roesch, Dennis Bauer, Leon Haupt, Robert Keller, Thomas Bauernhansl, Gilbert Fridgen, Gunther Reinhart and Alexander Sauer Harnessing the Full Potential of Industrial Demand-Side Flexibility: An End-to-End Approach Connecting Machines with Markets through Service-Oriented IT Platforms Reprinted from: Appl. Sci. 2019 -- SungUk Lim and Junmo Kim Technology Portfolio and Role of Public Research Institutions in Industry 4.0: A Case of South Korea Reprinted from: Appl. Sci. 2019 -- Jon Kepa Gerrikagoitia, Gorka Unamuno, Elena Urkia and Ainhoa Serna Digital Manufacturing Platforms in the Industry 4.0 from Private and Public Perspectives Reprinted from: Appl. Sci. 2019 -- Jena Svarcov´a, Tom´ˇaˇs Urb´anek, Lucie Povoln´a and Eliˇska Sobotkov´a Implementation of R&D Results and Industry 4.0 Influenced by Selected Macroeconomic Indicators Reprinted from: Appl. Sci. 2019 -- Aitziber Iglesias, Goiuria Sagardui and Cristobal Arellano Industrial Cyber-Physical System Evolution Detection and Alert Generation Reprinted from: Appl. Sci. 2019 -- Daniel Mejia-Parra, Jairo R. S´anchez, Oscar Ruiz-Salguero, Marcos Alonso, Alberto Izaguirre, Erik Gil, Jorge Palomar and Jorge Posada In-Line Dimensional Inspection of Warm-Die Forged Revolution Workpieces Using 3D Mesh Reconstruction Reprinted from: Appl. Sci. 2019 -- Huanhuan Zhang, Jinxiu Ma, Junfeng Jing and Pengfei Li Fabric Defect Detection Using L0 Gradient Minimization and Fuzzy C-Means Reprinted from: Appl. Sci. 2019 -- Zekui Lv, Zhikun Su, Dong Zhang, Lingyu Gao, Zhiming Yang, Fengzhou Fang, Haitao Zhang and Xinghua Li The Self-Calibration Method for the Vertex Distance of the Elliptical Paraboloid Array Reprinted from: Appl. Sci. 2019 -- Fei Zhou, Guihua Liu, Feng Xu and Hao Deng A Generic Automated Surface Defect Detection Based on a Bilinear Model Reprinted from: Appl. Sci. 2019 -- Liyong Ma, Wei Xie and Yong Zhang Blister Defect Detection Based on Convolutional Neural Network for Polymer Lithium-Ion Battery Reprinted from: Appl. Sci. 2019 -- Hongyang Li, Lizhuang Liu, Zhenqi Han and Dan Zhao Contour Detection for Fibre of Preserved Szechuan Pickle Based on Dilated Convolution Reprinted from: Appl. Sci. 2019 -- Jiange Liu, Tao Feng, Xia Fang, Sisi Huang and Jie Wang An Intelligent Vision System for Detecting Defects in Micro-Armatures for Smartphones Reprinted from: Appl. Sci. 2019 -- Ruben Merino, I ˜nigo Bediaga, Alexander Iglesias and Jokin Munoa Hybrid Edge-Cloud-Based Smart System for Chatter Suppression in Train Wheel Repair Reprinted from: Appl. Sci. 2019 -- Yi-Chung Chen, Kuo-Cheng Ting, Yo-Ming Chen, Don-Lin Yang, Hsi-Min Chen and Josh Jia-Ching Ying A Low-Cost Add-On Sensor and Algorithm to Help Small- and Medium-Sized Enterprises Monitor Machinery and Schedule Processes Reprinted from: Appl. Sci. 2019 -- Bolivar Solarte-Pardo, Diego Hidalgo and Syh-Shiuh Yeh Cutting Insert and Parameter Optimization for Turning Based on Artificial Neural Networks and a Genetic Algorithm Reprinted from: Appl. Sci. 2019 -- Yadan Li, Zhenqi Han, Haoyu Xu, Lizhuang Liu, Xiaoqiang Li and Keke Zheng YOLOv3-Lite: A Lightweight Crack Detection Network for Aircraft Structure Based on Depthwise Separable Convolutions Reprinted from: Appl. Sci. 2019 -- Ping Liu, Qiang Zhang and J¨urgen Pannek Development of Operator Theory in the Capacity Adjustment of Job Shop Manufacturing Systems Reprinted from: Appl. Sci. 2019 -- Justyna Patalas-Maliszewska and Sławomir Kłos An Approach to Supporting the Selection of Maintenance Experts in the Context of Industry 4.0 Reprinted from: Appl. Sci. 2019 -- Christoph Paul Schimanski, Gabriele Pasetti Monizza, Carmen Marcher and Dominik T. Matt Pushing Digital Automation of Configure-to-Order Services in Small and Medium Enterprises of the Construction Equipment Industry: A Design Science Research Approach Reprinted from: Appl. Sci. 2019, -- Otakar Ungerman and Jaroslava Dˇedkov´a Marketing Innovations in Industry 4.0 and Their Impacts on Current Enterprises Reprinted from: Appl. Sci. 2019 Mingxiong Zhao, Han Wang, Jin Guo, Di Liu, Cheng Xie, Qing Liu and Zhibo Cheng Construction of an Industrial Knowledge Graph for Unstructured Chinese Text Learning Reprinted from: Appl. Sci. 2019.