YaBeSH Engineering and Technology Library

    • Journals
    • PaperQuest
    • YSE Standards
    • YaBeSH
    • Login
    View Item 
    •   YE&T Library
    • ASME
    • Journal of Manufacturing Science and Engineering
    • View Item
    •   YE&T Library
    • ASME
    • Journal of Manufacturing Science and Engineering
    • View Item
    • All Fields
    • Source Title
    • Year
    • Publisher
    • Title
    • Subject
    • Author
    • DOI
    • ISBN
    Advanced Search
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Archive

    A Neural Network/Expert System Approach for Design Improvement of Products Manufactured by EDM

    Source: Journal of Manufacturing Science and Engineering:;1999:;volume( 121 ):;issue: 004::page 733
    Author:
    Z. Katz
    ,
    J. Naude
    DOI: 10.1115/1.2833127
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The stochastic nature of the electro discharge machining (EDM) process does not allow for a precise prediction of its effect on the machined features. However, there is a direct interrelation between feature design and the process results. The objective of this work is to suggest a neural network based system to facilitate and optimize the design process of products to be machined by EDM. A comprehensive analysis by a neural network and expert system is presented. Aspects of features coding and relations with the process parameters are discussed. Experimental results confirm design improvements and a practical system is described.
    keyword(s): Design , Expert systems , Artificial neural networks AND Electrical discharge machining ,
    • Download: (1.156Mb)
    • Show Full MetaData Hide Full MetaData
    • Get RIS
    • Item Order
    • Go To Publisher
    • Price: 5000 Rial
    • Statistics

      A Neural Network/Expert System Approach for Design Improvement of Products Manufactured by EDM

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/122447
    Collections
    • Journal of Manufacturing Science and Engineering

    Show full item record

    contributor authorZ. Katz
    contributor authorJ. Naude
    date accessioned2017-05-09T00:00:11Z
    date available2017-05-09T00:00:11Z
    date copyrightNovember, 1999
    date issued1999
    identifier issn1087-1357
    identifier otherJMSEFK-27351#733_1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/122447
    description abstractThe stochastic nature of the electro discharge machining (EDM) process does not allow for a precise prediction of its effect on the machined features. However, there is a direct interrelation between feature design and the process results. The objective of this work is to suggest a neural network based system to facilitate and optimize the design process of products to be machined by EDM. A comprehensive analysis by a neural network and expert system is presented. Aspects of features coding and relations with the process parameters are discussed. Experimental results confirm design improvements and a practical system is described.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleA Neural Network/Expert System Approach for Design Improvement of Products Manufactured by EDM
    typeJournal Paper
    journal volume121
    journal issue4
    journal titleJournal of Manufacturing Science and Engineering
    identifier doi10.1115/1.2833127
    journal fristpage733
    journal lastpage738
    identifier eissn1528-8935
    keywordsDesign
    keywordsExpert systems
    keywordsArtificial neural networks AND Electrical discharge machining
    treeJournal of Manufacturing Science and Engineering:;1999:;volume( 121 ):;issue: 004
    contenttypeFulltext
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian
     
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian