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    A virtual milling machine model to generate machine-monitoring data for predictive analytics

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    Date
    2016
    Author
    Lechevalier, David
    Shin, Seung-Jun
    Woo, Jungyub
    Rachuri, Sudarsan
    Foufou, Sebti
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    Abstract
    Real data from manufacturing processes are essential to create useful insights for decision-making. However, acquiring real manufacturing data can be expensive and time consuming. To address this issue, we implement a virtual milling machine model to generate machine monitoring data from process plans. MTConnect is used to report the monitoring data. This paper presents (1) the characteristics and specification of milling machine tools, (2) the architecture for implementing the virtual milling machine model, and (3) the integration with a simulation environment for extending to a virtual shop floor model. This paper also includes a case study to explain how to use the virtual milling machine model for predictive analytics modeling. IFIP International Federation for Information Processing 2016.
    DOI/handle
    http://dx.doi.org/10.1007/978-3-319-33111-9_76
    http://hdl.handle.net/10576/22805
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    • Computer Science & Engineering [‎2429‎ items ]

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