A Data Mining Approach For Developing Quality Prediction Model In Multi-Stage Manufacturing

Arif, Fahmi and Suryana, Nanna and Hussin, Burairah (2013) A Data Mining Approach For Developing Quality Prediction Model In Multi-Stage Manufacturing. International Journal Of Computer Applications , 69 (22). pp. 35-40. ISSN 0975-8887

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Abstract

Quality prediction model has been developed in various industries to realize the faultless manufacturing. However, most of quality prediction model is developed in single-stage manufacturing. Previous studies show that single-stage quality system cannot solve quality problem in multi-stage manufacturing effectively. This study is intended to propose combination of multiple PCA+ID3 algorithm to develop quality prediction model in MMS. This technique is applied to a semiconductor manufacturing dataset using the cascade prediction approach. The result shows that the combination of multiple PCA+ID3 is manage to produce the more accurate prediction model in term of classifying both positive and negative classes.

Item Type:	Article
Uncontrolled Keywords:	Principal Component Analysis, ID3, Quality Prediction, Data Mining, Multi-stage Manufacturing.
Subjects:	Q Science > Q Science (General) Q Science > QA Mathematics
Divisions:	Faculty of Information and Communication Technology
Depositing User:	Mohd Hannif Jamaludin
Date Deposited:	09 Aug 2019 02:38
Last Modified:	06 Jul 2021 21:31
URI:	http://eprints.utem.edu.my/id/eprint/23044
Statistic Details:	View Download Statistic

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