Title :
Fuzzy rule-based for predicting machining performance for SNTR carbide in milling titanium alloy (Ti-6Al-4v)
Author :
Adnan, M. R H Mohd ; Zain, Azlan Mohd ; Haron, Habibollah
Author_Institution :
Soft Comput. Res. Group, Univ. Teknol. Malaysia, Skudai, Malaysia
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.
Keywords :
cutting; fuzzy logic; fuzzy reasoning; fuzzy set theory; knowledge based systems; milling; production engineering computing; surface roughness; titanium alloys; IF-THEN rules; MATLAB fuzzy logic toolbox; SNTR carbide; cutting speed; estimation error value; feed rate; fuzzy rule-based model; linguistic values; machining performance prediction; milling process; radial rake angle; rule-based reasoning; surface roughness value; titanium alloy milling; Fuzzy logic; Milling; Pragmatics; Predictive models; Rough surfaces; Surface roughness; fuzzy rule-based; linguistic values; surface roughness;
Conference_Titel :
Data Mining and Optimization (DMO), 2012 4th Conference on
Conference_Location :
Langkawi
Print_ISBN :
978-1-4673-2717-6
DOI :
10.1109/DMO.2012.6329803