A real time process management system using RFID data mining
- Authors
- Kwon, Kyunglag; Kang, Daehyun; Yoon, Yeochang; Sohn, Jong-Soo; Chung, In-Jeong
- Issue Date
- 5월-2014
- Publisher
- ELSEVIER
- Keywords
- Process management; RFID; Data mining; Procedure Tree; Enterprise Resource Planning; Real time system
- Citation
- COMPUTERS IN INDUSTRY, v.65, no.4, pp.721 - 732
- Indexed
- SCIE
SCOPUS
- Journal Title
- COMPUTERS IN INDUSTRY
- Volume
- 65
- Number
- 4
- Start Page
- 721
- End Page
- 732
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/98576
- DOI
- 10.1016/j.compind.2014.02.007
- ISSN
- 0166-3615
- Abstract
- Recently, there have been numerous efforts to fuse the latest Radio Frequency Identification (RFID) technology with the Enterprise Information System (EIS). However, in most cases these attempts are centered mainly on the simultaneous multiple reading capability of RFID technology, and thus neglect the management of massive data generated from the RFID reader. As a result, it is difficult to obtain flow information for RFID data mining related to real time process control. In this paper, we propose an advanced process management method, called 'Procedure Tree' (PT), for RFID data mining. Using the suggested PT, we are able to manage massive RFID data effectively, and perform real time process management efficiently. Then we evaluate the efficiency of the proposed method, after applying it to a real time process control system connected to the RFID-based EIS. For the verification of the suggested system, we collect an enormous amount of data in the Enterprise Resource Planning (ERP) database, analyze characteristics of the collected data, and then compute the elapsed time on each stage in process control. The suggested system was able to perform what the traditional RFID-based process control systems failed to do, such as predicting and tracking of real time process and inventory control. (C) 2014 Elsevier B.V. All rights reserved.
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Collections - College of Science and Technology > Department of Computer Convergence Software > 1. Journal Articles
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