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From the Guest Editors–Machine Learning for Industry 4.0

June 23, 2023 by Mengchu Zhou

The Fourth Industrial Revolution, also known as Industry 4.0, marks the technological shift from traditional manufacturing systems to smart cyberphysical systems. It leads to an improvement in overall productivity and a reduction in environmental impact and promotes sustainable economic development. Industry 4.0 has been driven by emerging technologies such as the Internet of Things (IoT), also called the Industrial Internet of Things; digital twins; artificial intelligence; cloud computing; and edge/fog computing [1] , [2] , [3] , [4] , [5] . It is a hot topic in both academia and industry. The implementation of IoT connects physical assets to cybernetworks and captures a significant amount of data. These data, often “big”, are then fed to AI-based mission-critical systems to perform production monitoring, quality inspection, fault root cause analysis, quality prediction, and process control. The proper adoption of relevant Industry 4.0 technologies should lead to significant efficiency improvements and cost reductions in various industrial sectors.

For more about this article see link below.

https://ieeexplore.ieee.org/document/10153151

For the open access PDF link of this article please click here.

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As the flagship magazine of the IEEE Robotics and Automation Society, IEEE Robotics and Automation Magazine (RAM) covers the latest developments in robotics and automation. Its scope ranges from cutting-edge technological advances to emerging social, economic, ethical, and policy issues shaping the field.  Published quarterly (March, June, September, and December), RAM features both high-impact original research articles written in an engaging and accessible style, as well as reviews, columns and opinion pieces addressing a wide range of timely topics.

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IEEE Robotics & Automation Magazine  publishes four issues per year: March, June, September and December.