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Identification Process Variables and Process Improvement Using Data Mining  

Jeong, Young-Soo (Dept. of Industrial Engineering, Hanyang University)
Gang, Chang-Uk (Dept. of Information & Industrial Engineering, Hanyang University)
Byeon, Seong-Kyu (Domestic Logistics Team, Samsung Electronics Logitech Co. LTD)
Publication Information
Journal of Korean Society of Industrial and Systems Engineering / v.28, no.3, 2005 , pp. 166-171 More about this Journal
Abstract
With development of the database, there are too many data on process variables and the manufacturing process for the traditional statistical process control methods to identify the process variables related with assignable causes. Data mining is useful in this situation and provides variety of approaches for improving the process. In this paper, we applied control charts to monitor the process and if assignable causes are detected, then we applied the SVM technique and the sequence pattern analysis to find out the process variables suspected. These techniques made possible to predict the behavior of process variables. We illustrated our proposed methods with real manufacturing process data.
Keywords
Data mining; Process Variables; Process Improvement;
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