A Cloud Based Feature Recognition System to Support Collaborative and Adaptive Process Planning

Arivazhagan Anbalagan, Sheng Wang, Weidong Li

    Research output: Chapter in Book/Report/Conference proceedingConference proceedingpeer-review

    4 Citations (Scopus)

    Abstract

    This paper presents a Cloud Based Feature Recognition Module (CB-FRM) developed to support Collaborative and Adaptive Process Planning for Sustainable Manufacturing Environments. In the work, the CB-FRM is developed for a Cloud-based environment and based on an innovative ‘pattern-strings’ feature recognition concept. The Cloud system is designed in a light client and heavy server architecture, where the ‘pattern-strings’-based feature recognition approach is developed and deployed. Through recognized ‘pattern-strings’, the feature recognition process is able to extract the complete information of features with its location in the plane. The detailed information of the features is then shared in a developed Cloud environment for the downstream process planning activities. The implementation aspect is explained with the help of a sample industrial part by emphasizing the importance of Cloud manufacturing environment with process planning activities.
    Original languageEnglish
    Title of host publicationSME 2014 International Manufacturing Science and Engineering Conference collocated with the JSME 2014 International Conference on Materials and Processing and the 42nd North American Manufacturing Research Conference
    PublisherASME
    PagesV001T04A024
    Volume1: Materials; Micro and Nano Technologies; Properties, Applications and Systems; Sustainable Manufacturing
    ISBN (Print)978-0-7918-4580-6
    DOIs
    Publication statusPublished - 2014

    Bibliographical note

    This conference paper is not available on the repository. The paper was given at the ASME 2014 International Manufacturing Science and Engineering Conference, MSEC 2014 Collocated with the JSME 2014 International Conference on Materials and Processing and the 42nd North American Manufacturing Research Conference; Detroit; United States; 9 June 2014 through 13 June 2014

    Keywords

    • Adaptive process
    • Cloud-based
    • Feature recognition

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