Arif, Fahmi and Suryana, Nanna and Hussin, Burairah (2013) Cascade Quality Prediction Method Using Multiple PCA+ID3 for Multi-Stage Manufacturing System. In: 13 International Conference on Electronic Engineering and Computer Science (EECS 2013). Elsevier, IERI Procedia, 201 -207.
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Abstract
Quality prediction model, as the key to realize the real-time online quality monitoring process, has been developed using various data mining techniques. However, most of quality prediction models are developed in single-stage manufacturing system, where the relationship between manufacturing operation and quality variables is straightforward. Previous studies show that single-stage quality system cannot solve quality problem in multi-stage manufacturing system due to the complex variable relationships. This study is intended to propose a data mining method to develop quality prediction model which is able to deal with the complex variable relationships in multi-stage manufacturing system. This method, named Cascade Quality Prediction Method (CQPM), is developed by considering the complex variables relationships in multi-stage manufacturing system. CQPM employs the combination of multiple Principal Component Analysis and Iterative Dichotomiser 3 algorithm. A case study in semiconductor manufacturing shows that the prediction model that has been developed using CQPM is performed better in predicting both positive and negative classes compared to others.
| Item Type: | Book Section |
|---|---|
| Subjects: | T Technology > T Technology (General) |
| Divisions: | Karya Tulis Ilmiah |
| Depositing User: | Asep Kamaludin |
| Date Deposited: | 07 Nov 2018 09:06 |
| Last Modified: | 07 Nov 2018 09:06 |
| URI: | http://eprints.itenas.ac.id/id/eprint/190 |
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