… Industry 4.0 fields, namely the smart grid, where ML and DL models are presented and analyzed in terms of efficiency and effectiveness in smart grid applications. Lastly, trends and …
… PdM is inevitable for sustainable smartmanufacturing in I4.0. Machinelearning (ML) techniques have emerged as a promising tool in PdM applications for smartmanufacturing in I4.0, …
… Machinelearning (ML), as a subfield of AI, has become the main driver of those … for smart manufacturing and provides an overview of several ML algorithms (eg support vector machine, …
… MachineLearning (KML) framework for smartmanufacturing, which embeds knowledge from experience and, or physics information into the machinelearning … for smartmanufacturing …
J Wang, Y Ma, L Zhang, RX Gao, D Wu - Journal of manufacturing systems, 2018 - Elsevier
… Finally, the challenges as well as future trends of deep learning in smartmanufacturing are … smartmanufacturing to enable accurate insights for better decision making. Machinelearning …
… legacy manufacturing systems into smartmanufacturing … are based on classical machine learning techniques, such as … intelligence, various machinelearning algorithms have been …
… In manufacturing, a paradigm shift is happening right now. Advances in Big data and Machine Learning (ML) is changing the traditional manufacturing era into the smartmanufacturing …
… and machinelearning applied to smartmanufacturing are … production processes and machine learning techniques applied … designed platform for smartmanufacturing based on the six …
… opportunities to achieve smartmanufacturing. This kind of manufacturing requires machines … To attain this goal, data analytics and machinelearning are indispensable. In this paper, we …