@inproceedings{dfa27600c4b24b75a26cc3d76fe60286,
title = "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.",
keywords = "Data analytics, Data generator, MTConnect, Milling, STEP",
author = "David Lechevalier and Shin, {Seung Jun} and Jungyub Woo and Sudarsan Rachuri and Sebti Foufou",
note = "Publisher Copyright: {\textcopyright} IFIP International Federation for Information Processing 2016.; 12th IFIP WG 5.1 International Conference on Product Lifecycle Management in the Era of Internet of Things, PLM 2015 ; Conference date: 19-10-2015 Through 21-10-2015",
year = "2016",
doi = "10.1007/978-3-319-33111-9_76",
language = "English (US)",
isbn = "9783319331102",
series = "IFIP Advances in Information and Communication Technology",
publisher = "Springer New York LLC",
pages = "835--845",
editor = "Abdelaziz Bouras and Sebti Foufou and Klaus-Dieter Thoben and Benoit Eynard",
booktitle = "Product Lifecycle Management in the Era of Internet of Things - 12th IFIP WG 5.1 International Conference, PLM 2015, Revised Selected Papers",
}