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    Special Issue: Machine Learning Applications in Manufacturing

    Source: Journal of Computing and Information Science in Engineering:;2020:;volume( 020 ):;issue: 002
    DOI: 10.1115/1.4046427
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Machine 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.
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      Special Issue: Machine Learning Applications in Manufacturing

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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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    DSpace software copyright © 2002-2015  DuraSpace
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