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Analysis and prediction cost of manufacturing process based on process mining

Author(s)
Tu, Thi Bich HongSong, Minseok
Issued Date
2016-05-23
DOI
10.1109/ICIMSA.2016.7503993
URI
https://scholarworks.unist.ac.kr/handle/201301/35411
Fulltext
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7503993
Citation
3rd International Conference on Industrial Engineering, Management Science and Applications, ICIMSA 2016
Abstract
Analysis and prediction of manufacturing cost play a decisive role in manufacturing process management; however, they face a challenge to be conducted due to the complexity of manufacturing process. Process mining has demonstrated to be a valuable tool for observing and diagnosing inefficiencies of a business process based on event logs. Nevertheless, significantly less attention has been done on investigating cost perspective. Therefore, this paper suggests a framework to analyze and predict manufacturing cost by utilizing and extending existing process mining techniques. In this study, new techniques such as process model-enhanced cost, and cost prediction based on production volume and time prediction using working progress of manufacturing processes are presented.
Publisher
Institute of Electrical and Electronics Engineers Inc.

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