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date accessioned2022-02-04T14:51:09Z
date available2022-02-04T14:51:09Z
date copyright2020/03/03/
date issued2020
identifier issn1530-9827
identifier otherjcise_20_2_020301.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4274517
description abstractMachine learning (ML) has recently become a power-engine transforming various manufacturing research and applications. In the era of Smart Manufacturing and I4.0, the abundance of smart sensors and industrial Internet of things has made manufacturing systems a data-rich environment. ML techniques play a significant role in uncovering fine-grained complex production patterns and offering timely decision support in a wide range of applications, to name a few, robotics and human–machine interaction, predictive maintenance, process optimization, task scheduling, quality improvement, and so on. While different ML techniques have been researched and deployed in manufacturing, many open challenges and questions still remain, from data understanding, data and knowledge representation, and data reasoning in ML to advanced topics such as predictive analytics, edge computing, and cybersecurity. Therefore, this special issue is dedicated to harvesting the latest research and development of ML in manufacturing. The papers are in no particular order.
publisherThe American Society of Mechanical Engineers (ASME)
titleSpecial Issue: Machine Learning Applications in Manufacturing
typeJournal Paper
journal volume20
journal issue2
journal titleJournal of Computing and Information Science in Engineering
identifier doi10.1115/1.4046427
page20301
treeJournal of Computing and Information Science in Engineering:;2020:;volume( 020 ):;issue: 002
contenttypeFulltext


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