Fuzzy rule-based for predicting machining performance for SNTR carbide in milling titanium alloy (ti-6al-4v)
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 us...
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| Format: | Article |
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2012
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| _version_ | 1796859069815848960 |
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| author | Adnan, M. R. H. M. Mohd. Zain, Azlan Haron, Habibollah |
| author_facet | Adnan, M. R. H. M. Mohd. Zain, Azlan Haron, Habibollah |
| author_sort | Adnan, M. R. H. M. |
| collection | ePrints |
| description | 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. |
| first_indexed | 2024-03-05T19:21:44Z |
| format | Article |
| id | utm.eprints-47016 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T19:21:44Z |
| publishDate | 2012 |
| record_format | dspace |
| spelling | utm.eprints-470162017-09-28T07:29:11Z http://eprints.utm.my/47016/ Fuzzy rule-based for predicting machining performance for SNTR carbide in milling titanium alloy (ti-6al-4v) Adnan, M. R. H. M. Mohd. Zain, Azlan Haron, Habibollah QA76 Computer software 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. 2012 Article PeerReviewed 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 |
| spellingShingle | QA76 Computer software Adnan, M. R. H. M. Mohd. Zain, Azlan Haron, Habibollah Fuzzy rule-based for predicting machining performance for SNTR carbide in milling titanium alloy (ti-6al-4v) |
| title | Fuzzy rule-based for predicting machining performance for SNTR carbide in milling titanium alloy (ti-6al-4v) |
| title_full | Fuzzy rule-based for predicting machining performance for SNTR carbide in milling titanium alloy (ti-6al-4v) |
| title_fullStr | Fuzzy rule-based for predicting machining performance for SNTR carbide in milling titanium alloy (ti-6al-4v) |
| title_full_unstemmed | Fuzzy rule-based for predicting machining performance for SNTR carbide in milling titanium alloy (ti-6al-4v) |
| title_short | Fuzzy rule-based for predicting machining performance for SNTR carbide in milling titanium alloy (ti-6al-4v) |
| title_sort | fuzzy rule based for predicting machining performance for sntr carbide in milling titanium alloy ti 6al 4v |
| topic | QA76 Computer software |
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