@inproceedings{e8d8e6634c1a4f4fbb16e6a296b4c6a2,
title = "Big data based analysis framework for product manufacturing and maintenance process",
abstract = "With the widely use of smart sensor devices in the product lifecycle management (PLM), it creates amount of real-time and muti-source lifecycle big data. These data allow decision makers to make better-informed PLM decisions. In this article, an overview framework of big data based analysis for product lifecycle (BDA-PL) was presented to provide a new paradigm by extending the techniques of Internet of Things (IoT) and big data analysis to manufacturing field. Under this framework, the real-time lifecycle data of products can be active perception and collection. Considering the challenges of processing the lifecycle big data into useful information and exchange it among various life- cycle phase, a graphical model of big data mining was designed to achieve knowledge discovery. Finally, a case has been used to illustrate the proof-of-concept application of the proposed BDA-PL.",
keywords = "Big data analysis, Data mining, Maintenance, Manufacturing, Product lifecycle",
author = "Yingfeng Zhang and Shan Ren",
note = "Publisher Copyright: {\textcopyright} IFIP International Federation for Information Processing 2015.; IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2015 ; Conference date: 07-09-2015 Through 09-09-2015",
year = "2015",
doi = "10.1007/978-3-319-22759-7_50",
language = "英语",
isbn = "9783319227580",
series = "IFIP Advances in Information and Communication Technology",
publisher = "Springer New York LLC",
pages = "427--435",
editor = "Hajime Mizuyama and Hironori Hibino and {von Cieminski}, Gregor and Shigeki Umeda and Masaru Nakano and Dimitris Kiritsis",
booktitle = "Advances in Production Management Systems",
}