A Virtual Milling Machine Model to Generate Machine-Monitoring Data for Predictive Analytics - Product Lifecycle Management in the Era of Internet of Things Access content directly
Conference Papers Year : 2016

A Virtual Milling Machine Model to Generate Machine-Monitoring Data for Predictive Analytics

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.
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hal-01377514 , version 1 (07-10-2016)

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David Lechevalier, Seung-Jun Shin, Jungyub Woo, Sudarsan Rachuri, Sebti Foufou. A Virtual Milling Machine Model to Generate Machine-Monitoring Data for Predictive Analytics. 12th IFIP International Conference on Product Lifecycle Management (PLM), Oct 2015, Doha, Qatar. pp.835-845, ⟨10.1007/978-3-319-33111-9_76⟩. ⟨hal-01377514⟩
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