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    Procedure for Selecting Key Performance Indicators for Sustainable Manufacturing 

    Source: Journal of Manufacturing Science and Engineering:;2018:;volume( 140 ):;issue: 001:;page 11005
    Author(s): Kibira, Deogratias; Brundage, Michael P.; Feng, Shaw; Morris, K. C.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The need for an open, inclusive, and neutral procedure in selecting key performance indicators (KPIs) for sustainable manufacturing has been increasing. The reason is that manufacturers seek to determine what to measure ...
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    Toward Standards-Based Generation of Reusable Life Cycle Inventory Data Models for Manufacturing Processes 

    Source: Journal of Manufacturing Science and Engineering:;2019:;volume( 141 ):;issue: 002:;page 21017
    Author(s): Brundage, Michael P.; Lechevalier, David; Morris, K. C.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The production stage of a product's life cycle can significantly contribute to its overall environmental impact. Estimates of environmental impact for a product are typically produced using life cycle assessment (LCA) ...
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    Standalone Throughput Analysis on the Wave Propagation of Disturbances in Production Sub Systems 

    Source: Journal of Manufacturing Science and Engineering:;2013:;volume( 135 ):;issue: 005:;page 51001
    Author(s): Li, Yang; Chang, Qing; Brundage, Michael P.; Xiao, Guoxian; Biller, Stephan
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Standalone throughput (SAT) of a single station is one of the most widely used performance indexes in industry due to its clear definition, ease of evaluation and the ability to provide a guidance for continuous improvement ...
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    Where Do We Start? Guidance for Technology Implementation in Maintenance Management for Manufacturing 

    Source: Journal of Manufacturing Science and Engineering:;2019:;volume( 141 ):;issue: 009:;page 91005
    Author(s): Brundage, Michael P.; Sexton, Thurston; Hodkiewicz, Melinda; Morris, KC; Arinez, Jorge; Ameri, Farhad; Ni, Jun; Xiao, Guoxian
    Publisher: American Society of Mechanical Engineers (ASME)
    Abstract: Recent efforts in smart manufacturing (SM) have proven quite effective at elucidating system behavior using sensing systems, communications, and computational platforms, along with statistical methods to collect and analyze ...
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