UNSPECIFIED (2013) A Data Mining Approach for Developing Quality Prediction Model in Multi-Stage Manufacturing. International Journal of Computer Applications, 69 (22). 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
Divisions:	Karya Tulis Ilmiah
Depositing User:	Asep Kamaludin
Date Deposited:	06 Nov 2018 09:16
Last Modified:	06 Nov 2018 09:16
URI:	http://eprints.itenas.ac.id/id/eprint/176

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