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    Data Mining in Manufacturing: A Review

    Source: Journal of Manufacturing Science and Engineering:;2006:;volume( 128 ):;issue: 004::page 969
    Author:
    J. A. Harding
    ,
    A. Kusiak
    ,
    M. Shahbaz
    ,
    Srinivas
    DOI: 10.1115/1.2194554
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The paper reviews applications of data mining in manufacturing engineering, in particular production processes, operations, fault detection, maintenance, decision support, and product quality improvement. Customer relationship management, information integration aspects, and standardization are also briefly discussed. This review is focused on demonstrating the relevancy of data mining to manufacturing industry, rather than discussing the data mining domain in general. The volume of general data mining literature makes it difficult to gain a precise view of a target area such as manufacturing engineering, which has its own particular needs and requirements for mining applications. This review reveals progressive applications in addition to existing gaps and less considered areas such as manufacturing planning and shop floor control.
    keyword(s): Manufacturing AND Data mining ,
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      Data Mining in Manufacturing: A Review

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/134120
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    contributor authorJ. A. Harding
    contributor authorA. Kusiak
    contributor authorM. Shahbaz
    contributor authorSrinivas
    date accessioned2017-05-09T00:20:41Z
    date available2017-05-09T00:20:41Z
    date copyrightNovember, 2006
    date issued2006
    identifier issn1087-1357
    identifier otherJMSEFK-27958#969_1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/134120
    description abstractThe paper reviews applications of data mining in manufacturing engineering, in particular production processes, operations, fault detection, maintenance, decision support, and product quality improvement. Customer relationship management, information integration aspects, and standardization are also briefly discussed. This review is focused on demonstrating the relevancy of data mining to manufacturing industry, rather than discussing the data mining domain in general. The volume of general data mining literature makes it difficult to gain a precise view of a target area such as manufacturing engineering, which has its own particular needs and requirements for mining applications. This review reveals progressive applications in addition to existing gaps and less considered areas such as manufacturing planning and shop floor control.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleData Mining in Manufacturing: A Review
    typeJournal Paper
    journal volume128
    journal issue4
    journal titleJournal of Manufacturing Science and Engineering
    identifier doi10.1115/1.2194554
    journal fristpage969
    journal lastpage976
    identifier eissn1528-8935
    keywordsManufacturing AND Data mining
    treeJournal of Manufacturing Science and Engineering:;2006:;volume( 128 ):;issue: 004
    contenttypeFulltext
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