Adnan, M. R. H. M. and Mohd. Zain, Azlan and Haron, Habibollah (2012) Fuzzy rule-based for predicting machining performance for SNTR carbide in milling titanium alloy (ti-6al-4v). Conference on Data Mining and Optimization . pp. 86-90. ISSN 2155-6938
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Abstract
Rule-based reasoning and fuzzy logic are used to develop a model to predict the surface roughness value of milling process. The process parameters considered in this study are cutting speed, feed rate, and radial rake angle, each has five linguistic values. The fuzzy rule-based model is developed using MATLAB fuzzy logic toolbox. Nine linguistic values and twenty four IF-THEN rules are created for model development. Predicted result of the proposed model has been compared to the experimental result, and it gave a good agreement with the correlation 0.9845. The differences between experimental result and predicted result have been proven with estimation error value 0.0008. The best predicted value of surface roughness using the fuzzy rule-based is located at combination of High cutting speed, VeryLow feed rate, and High radial rake angle.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Data mining, optimization |
| Subjects: | Q Science > QA Mathematics > QA76 Computer software |
| Divisions: | Computer Science and Information System |
| ID Code: | 47016 |
| Deposited By: | Haliza Zainal |
| Deposited On: | 22 Jun 2015 05:56 |
| Last Modified: | 28 Sep 2017 07:29 |
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