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Development of Prediction Model using PCA for the Failure Rate at the Client's Manufacturing Process  

Jang, Youn-Hee (Department of Industrial Engineering, Ajou University)
Son, Ji-Uk (Quality Center, LG display)
Lee, Dong-Hyuk (Quality Center, LG display)
Oh, Chang-Suk (Quality Center, LG display)
Lee, Duek-Jung (Quality Center, LG display)
Jang, Joongsoon (Department of Industrial Engineering, Ajou University)
Publication Information
Journal of Applied Reliability / v.16, no.2, 2016 , pp. 98-103 More about this Journal
Abstract
Purpose: The purpose of this paper is to get a meaningful information for improving manufacturing quality of the products before they are produced in client's manufacturing process. Methods: A variety of data mining techniques have been being used for wide range of industries from process data in manufacturing factories for quality improvement. One application of those is to get meaningful information from process data in manufacturing factories for quality improvement. In this paper, the failure rate at client's manufacturing process is predicted by using the parameters of the characteristics of the product based on PCA (Principle Component Analysis) and regression analysis. Results: Through a case study, we proposed the predicting methodology and regression model. The proposed model is verified through comparing the failure rates of actual data and the estimated value. Conclusion: This study can provide the guidance for predicting the failure rate on the manufacturing process. And the manufacturers can prevent the defects by confirming the factor which affects the failure rate.
Keywords
Failure Rate Prediction; PCA(Principle Component Analysis); Regression Analysis;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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