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    A Cloud Manufacturing Architecture for Complex Parts Machining

    Source: Journal of Manufacturing Science and Engineering:;2015:;volume( 137 ):;issue: 006::page 61009
    Author:
    Liu, Xu
    ,
    Li, Yingguang
    ,
    Wang, Lihui
    DOI: 10.1115/1.4029856
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Service provider (SP) knowhows are essential in machining service (MS) encapsulation in the cloud. However, since the acquisition of the knowhows for complex parts machining requires investing considerable manpower and resources in R&D, this kind of machining knowhows is usually considered as one of the core competences of the SP who makes them unshareable. Targeting the problem, this paper presents a new cloud manufacturing (CM) architecture in which MSs are encapsulated within each SP with standardized machining task description strategies (SMTDS). Only the capability information about what the SP can do is provided to the cloud. During service matching, SMTDS is also applied for user request formulation to improve the matching efficiency and quality. For complex parts in large size, high machining requirements, high value, short delivery cycle, and complex structures, e.g., aircraft structural parts, unacceptable machining quality or delivery delay may cause a much greater loss not only in economy. In the proposed CM architecture, to guarantee the feasibility of the MSs for complex structural parts, machining operations for the user preferred services could be generated by mapping the corresponding typical machining plans (TMP) to the part based on the dynamic feature concept to support accurate evaluations of the MSs. The machining of an aircraft structural part is then applied as a test user request to demonstrate how the proposed method works for finding MS for complex parts.
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      A Cloud Manufacturing Architecture for Complex Parts Machining

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    http://yetl.yabesh.ir/yetl1/handle/yetl/158762
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    contributor authorLiu, Xu
    contributor authorLi, Yingguang
    contributor authorWang, Lihui
    date accessioned2017-05-09T01:20:42Z
    date available2017-05-09T01:20:42Z
    date issued2015
    identifier issn1087-1357
    identifier othermanu_137_06_061009.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/158762
    description abstractService provider (SP) knowhows are essential in machining service (MS) encapsulation in the cloud. However, since the acquisition of the knowhows for complex parts machining requires investing considerable manpower and resources in R&D, this kind of machining knowhows is usually considered as one of the core competences of the SP who makes them unshareable. Targeting the problem, this paper presents a new cloud manufacturing (CM) architecture in which MSs are encapsulated within each SP with standardized machining task description strategies (SMTDS). Only the capability information about what the SP can do is provided to the cloud. During service matching, SMTDS is also applied for user request formulation to improve the matching efficiency and quality. For complex parts in large size, high machining requirements, high value, short delivery cycle, and complex structures, e.g., aircraft structural parts, unacceptable machining quality or delivery delay may cause a much greater loss not only in economy. In the proposed CM architecture, to guarantee the feasibility of the MSs for complex structural parts, machining operations for the user preferred services could be generated by mapping the corresponding typical machining plans (TMP) to the part based on the dynamic feature concept to support accurate evaluations of the MSs. The machining of an aircraft structural part is then applied as a test user request to demonstrate how the proposed method works for finding MS for complex parts.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleA Cloud Manufacturing Architecture for Complex Parts Machining
    typeJournal Paper
    journal volume137
    journal issue6
    journal titleJournal of Manufacturing Science and Engineering
    identifier doi10.1115/1.4029856
    journal fristpage61009
    journal lastpage61009
    identifier eissn1528-8935
    treeJournal of Manufacturing Science and Engineering:;2015:;volume( 137 ):;issue: 006
    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