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A Data Mining Approach for Developing Quality Prediction Model in Multi-Stage Manufacturing

by Fahmi Arif, Nanna Suryana, Burairah Hussin
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 69 - Number 22
Year of Publication: 2013
Authors: Fahmi Arif, Nanna Suryana, Burairah Hussin
10.5120/12106-8375

Fahmi Arif, Nanna Suryana, Burairah Hussin . A Data Mining Approach for Developing Quality Prediction Model in Multi-Stage Manufacturing. International Journal of Computer Applications. 69, 22 ( May 2013), 35-40. DOI=10.5120/12106-8375

@article{ 10.5120/12106-8375,
author = { Fahmi Arif, Nanna Suryana, Burairah Hussin },
title = { A Data Mining Approach for Developing Quality Prediction Model in Multi-Stage Manufacturing },
journal = { International Journal of Computer Applications },
issue_date = { May 2013 },
volume = { 69 },
number = { 22 },
month = { May },
year = { 2013 },
issn = { 0975-8887 },
pages = { 35-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume69/number22/12106-8375/ },
doi = { 10.5120/12106-8375 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:31:03.515617+05:30
%A Fahmi Arif
%A Nanna Suryana
%A Burairah Hussin
%T A Data Mining Approach for Developing Quality Prediction Model in Multi-Stage Manufacturing
%J International Journal of Computer Applications
%@ 0975-8887
%V 69
%N 22
%P 35-40
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
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.

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Index Terms

Computer Science
Information Sciences

Keywords

Principal Component Analysis ID3 Quality Prediction Data Mining Multi-stage Manufacturing

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