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    An Automated Approach to Enhance Multiscale Signal Monitoring of Manufacturing Processes 

    Source: Journal of Manufacturing Science and Engineering:;2016:;volume( 138 ):;issue: 005:;page 51003
    Author(s): Grasso, Marco; Maria Colosimo, Bianca
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Multiscale signal decomposition represents an important step to enhance process monitoring results in many manufacturing applications. Empirical mode decomposition (EMD) is a data driven technique that gained an increasing ...
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    Prescriptive Data-Analytical Modeling of Laser Powder Bed Fusion Processes for Accuracy Improvement 

    Source: Journal of Manufacturing Science and Engineering:;2019:;volume( 141 ):;issue: 001:;page 11008
    Author(s): Luan, He; Grasso, Marco; Colosimo, Bianca M.; Huang, Qiang
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Laser powder bed fusion (LPBF) has the ability to produce three-dimensional lightweight metal parts with complex shapes. Extensive investigations have been conducted to tackle build accuracy problems caused by shape ...
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    In-Process Monitoring of Selective Laser Melting: Spatial Detection of Defects Via Image Data Analysis 

    Source: Journal of Manufacturing Science and Engineering:;2017:;volume( 139 ):;issue: 005:;page 51001
    Author(s): Grasso, Marco; Laguzza, Vittorio; Semeraro, Quirico; Colosimo, Bianca Maria
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Selective laser melting (SLM) has been attracting a growing interest in different industrial sectors as it is one of the key technologies for metal additive manufacturing (AM). Despite the relevant improvements made by the ...
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