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    Enriching STEP Product Model With Geometric Dimension and Tolerance Information for One-Dimensional Tolerance Analysis 

    Source: Journal of Computing and Information Science in Engineering:;2017:;volume( 017 ):;issue: 002:;page 21004
    Author(s): Sarigecili, Mehmet I.; Roy, Utpal; Rachuri, Sudarsan
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Information exchange and sharing become a necessity for digital factory but they have been more challenging as the industry is computerized more. This is mainly because the capabilities of computerized systems have grown ...
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    Analysis and Evaluation for STEP-Based Electromechanical Assemblies 

    Source: Journal of Computing and Information Science in Engineering:;2006:;volume( 006 ):;issue: 003:;page 276
    Author(s): Xuan F. Zha; Sebti Foufou; Rachuri Sudarsan; Ram D. Sriram
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: In this paper, we propose an integrated approach to analysis and evaluation for STEP-based (STandard for the Exchange of Product model data, officially ISO 10303) electromechanical assemblies. ...
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    Towards a Reference Architecture for Archival Systems: Use Case With Product Data 

    Source: Journal of Computing and Information Science in Engineering:;2014:;volume( 014 ):;issue: 003:;page 31005
    Author(s): Barbau, Raphael; Lubell, Joshua; Rachuri, Sudarsan; Foufou, Sebti
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Longterm preservation of product data is imperative for many organizations. A product data archive should be designed to ensure information accessibility and understanding over time. Approaches, such as the Open Archival ...
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    Toward a Generalized Energy Prediction Model for Machine Tools 

    Source: Journal of Manufacturing Science and Engineering:;2017:;volume( 139 ):;issue: 004:;page 41013
    Author(s): Bhinge, Raunak; Park, Jinkyoo; Law, Kincho H.; Dornfeld, David A.; Helu, Moneer; Rachuri, Sudarsan
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Energy prediction of machine tools can deliver many advantages to a manufacturing enterprise, ranging from energy-efficient process planning to machine tool monitoring. Physics-based energy prediction models have been ...
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