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    Online Maintenance Prioritization Via Monte Carlo Tree Search and Case-Based Reasoning 

    Source: Journal of Computing and Information Science in Engineering:;2022:;volume( 022 ):;issue: 004:;page 41005-1
    Author(s): Hoffman, Michael; Song, Eunhye; Brundage, Michael; Kumara, Soundar
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: When maintenance resources in a manufacturing system are limited, a challenge arises in determining how to allocate these resources among multiple competing maintenance jobs. This work formulates an online prioritization ...
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    Smart Vaccine Manufacturing Using Novel Biotechnology Platforms: A Study During COVID-19 

    Source: Journal of Computing and Information Science in Engineering:;2022:;volume( 022 ):;issue: 004:;page 40903-1
    Author(s): Kumar, Vishnu; Srinivasan, Vijay; Kumara, Soundar
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Healthcare experts have come to a consensus that effective and safe vaccines are necessary to control the rapid spread of the ongoing COVID-19 pandemic across the globe. Since the traditional vaccine development and ...
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    An Unsupervised Machine Learning Approach to Assessing Designer Performance During Physical Prototyping 

    Source: Journal of Computing and Information Science in Engineering:;2018:;volume( 018 ):;issue: 001:;page 11002
    Author(s): Dering, Matthew L.; Tucker, Conrad S.; Kumara, Soundar
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: An important part of the engineering design process is prototyping, where designers build and test their designs. This process is typically iterative, time consuming, and manual in nature. For a given task, there are ...
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    A Comparative Study on Machine Learning Algorithms for Smart Manufacturing: Tool Wear Prediction Using Random Forests 

    Source: Journal of Manufacturing Science and Engineering:;2017:;volume( 139 ):;issue: 007:;page 71018
    Author(s): Wu, Dazhong; Jennings, Connor; Terpenny, Janis; Gao, Robert X.; Kumara, Soundar
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Manufacturers have faced an increasing need for the development of predictive models that predict mechanical failures and the remaining useful life (RUL) of manufacturing systems or components. Classical model-based or ...
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    Cloud-Based Parallel Machine Learning for Tool Wear Prediction 

    Source: Journal of Manufacturing Science and Engineering:;2018:;volume( 140 ):;issue: 004:;page 41005
    Author(s): Wu, Dazhong; Jennings, Connor; Terpenny, Janis; Kumara, Soundar; Gao, Robert X.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The emergence of cloud computing, industrial internet of things (IIoT), and new machine learning techniques have shown the potential to advance prognostics and health management (PHM) in smart manufacturing. While model-based ...
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    Ontology NetworkBased InSitu Sensor Selection for Quality Management in Metal Additive Manufacturing 

    Source: Journal of Computing and Information Science in Engineering:;2022:;volume( 022 ):;issue: 006:;page 60905
    Author(s): Roh, ByeongMin;Kumara, Soundar R. T.;Yang, Hui;Simpson, Timothy W.;Witherell, Paul;Jones, Albert T.;Lu, Yan
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Metal additive manufacturing (MAM) offers a larger design space with greater manufacturability than traditional manufacturing. Despite continued advances, MAM processes still face huge uncertainty, resulting in variable ...
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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