Optimization of machining parameters for ultrasonic assisted vibration-grinding (UAVG) of ultra-low expansion (ULE) optical glass using taguchi method

K. Mulenga*, B. Guo, Q. Zhao, X. Fu

*Corresponding author for this work

    Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

    1 Citation (Scopus)

    Abstract

    Glass materials possess properties that are highly needed in various areas of today's and future innovation applications. In this study, we concentrated on optimization of Ultrasonic Assisted Vibration Grinding parameters for Ultra-Low Expansion (ULE) optical glass using the Taguchi method. This material is of interest as it finds its applications in the space industry such as Hubble telescope. A hybrid process of grinding; Ultrasonic Assisted Vibration Grinding (UAVG) has been used in this work, an alternative to solving the current problems with machining glass materials. We investigated the effects of control parameters; Feedrate, Depth of cut, Spindle speed, and Diamond grit size, on response variables; surface roughness and cutting force. Using Signal to Noise ratios (S/N) and Analysis of Variance (ANOVA), the machining parameters were optimized revealing that for Surface roughness had was more influenced by the spindle speed while diamond grit size influenced the cutting force.
    Original languageEnglish
    Title of host publication2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)
    PublisherIEEE
    Pages2375-2379
    ISBN (Electronic)9781538609484
    ISBN (Print)9781538609491
    DOIs
    Publication statusPublished - Dec 2017
    Event2017 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2017 - Suntec Singapore, Singapore, Singapore
    Duration: 10 Dec 201713 Dec 2017
    http://ieem2017.org/public.asp?page=home.htm
    http://ieem2017.org/public.asp?page=home.htm

    Publication series

    NameIEEE International Conference on Industrial Engineering and Engineering Management
    Volume2017
    ISSN (Print)2157-3611
    ISSN (Electronic)2157-362X

    Conference

    Conference2017 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2017
    Abbreviated titleIEEM 2017
    PlaceSingapore
    CitySingapore
    Period10/12/1713/12/17
    Internet address

    Research Keywords

    • ANOVA
    • Grinding
    • Optimization

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