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 lifecycle 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.
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Shigeki Umeda; Masaru Nakano; Hajime Mizuyama; Hironori Hibino; Dimitris Kiritsis; Gregor von Cieminski. IFIP International Conference on Advances in Production Management Systems (APMS), Sep 2015, Tokyo, Japan. IFIP Advances in Information and Communication Technology, AICT-460 (Part II), pp.427-435, 2015, Advances in Production Management Systems: Innovative Production Management Towards Sustainable Growth. 〈10.1007/978-3-319-22759-7_50〉
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Yingfeng Zhang, Shan Ren. Big Data Based Analysis Framework for Product Manufacturing and Maintenance Process. Shigeki Umeda; Masaru Nakano; Hajime Mizuyama; Hironori Hibino; Dimitris Kiritsis; Gregor von Cieminski. IFIP International Conference on Advances in Production Management Systems (APMS), Sep 2015, Tokyo, Japan. IFIP Advances in Information and Communication Technology, AICT-460 (Part II), pp.427-435, 2015, Advances in Production Management Systems: Innovative Production Management Towards Sustainable Growth. 〈10.1007/978-3-319-22759-7_50〉. 〈hal-01431128〉

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