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    Model-Based Analysis of the Surface Generation in Microendmilling—Part I: Model Development

    Source: Journal of Manufacturing Science and Engineering:;2007:;volume( 129 ):;issue: 003::page 453
    Author:
    Xinyu Liu
    ,
    Richard E. DeVor
    ,
    Shiv G. Kapoor
    DOI: 10.1115/1.2716705
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: This paper presents the development of models that describe the surface-generation process for microendmilling. The surface-generation models for the sidewall and floor surfaces consist of deterministic and stochastic models. In the sidewall surface-generation model, the deterministic model characterizes the surface topography generated from the relative motion between the major cutting edge and the workpiece material. The model includes the effects of the process kinematics, dynamics, tool edge serration, and process faults (e.g., tool tip runout). The stochastic model predicts the increased surface roughness generated from ploughing due to the significant tool edge radius effect. In the floor surface-generation model, the deterministic model characterizes the three-dimensional surface topography over the entire floor surface and considers the effects of the minimum chip thickness, the elastic recovery, and the transverse vibration. The variation of the ploughing amount across the swept arc of the cutter due to the varying chip load conditions is considered in the stochastic model.
    keyword(s): Vibration , Cutting , Geometry , Model development , Thickness , Surface roughness AND Algorithms ,
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      Model-Based Analysis of the Surface Generation in Microendmilling—Part I: Model Development

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    http://yetl.yabesh.ir/yetl1/handle/yetl/136291
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    contributor authorXinyu Liu
    contributor authorRichard E. DeVor
    contributor authorShiv G. Kapoor
    date accessioned2017-05-09T00:24:45Z
    date available2017-05-09T00:24:45Z
    date copyrightJune, 2007
    date issued2007
    identifier issn1087-1357
    identifier otherJMSEFK-28004#453_1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/136291
    description abstractThis paper presents the development of models that describe the surface-generation process for microendmilling. The surface-generation models for the sidewall and floor surfaces consist of deterministic and stochastic models. In the sidewall surface-generation model, the deterministic model characterizes the surface topography generated from the relative motion between the major cutting edge and the workpiece material. The model includes the effects of the process kinematics, dynamics, tool edge serration, and process faults (e.g., tool tip runout). The stochastic model predicts the increased surface roughness generated from ploughing due to the significant tool edge radius effect. In the floor surface-generation model, the deterministic model characterizes the three-dimensional surface topography over the entire floor surface and considers the effects of the minimum chip thickness, the elastic recovery, and the transverse vibration. The variation of the ploughing amount across the swept arc of the cutter due to the varying chip load conditions is considered in the stochastic model.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleModel-Based Analysis of the Surface Generation in Microendmilling—Part I: Model Development
    typeJournal Paper
    journal volume129
    journal issue3
    journal titleJournal of Manufacturing Science and Engineering
    identifier doi10.1115/1.2716705
    journal fristpage453
    journal lastpage460
    identifier eissn1528-8935
    keywordsVibration
    keywordsCutting
    keywordsGeometry
    keywordsModel development
    keywordsThickness
    keywordsSurface roughness AND Algorithms
    treeJournal of Manufacturing Science and Engineering:;2007:;volume( 129 ):;issue: 003
    contenttypeFulltext
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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
    yabeshDSpacePersian