A Data Mining Approach For Developing Quality Prediction Model In Multi-Stage Manufacturing
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 manufactu...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Foundation Of Computer Science (FCS)
2013
|
| Subjects: | |
| Online Access: | http://eprints.utem.edu.my/id/eprint/23044/2/ADataMiningApproachIJCA2013.pdf http://eprints.utem.edu.my/id/eprint/23044/ https://research.ijcaonline.org/volume69/number22/pxc3888375.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | 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. |
|---|