Prediction Temperature for Al 6061 Turning using Neuro Fuzzy System and Experimental Study

This paper proposes the mathematical modelling using Neuro-fuzzy (ANFIS) system for prediction temperature occurring on Al 6061 turning together with experimental study using temperature measurement. The comparison is discussed. Neuro fuzzy system is developed based on the machinist expert opinion rules for a particular material of Al6061on turning process. The experiment study is also created using DOE and tested by thermal image camera modelled IC125LV. The comparison is discussed by the both methodologies. It is found that the cutting parameters of cutting Al6061 related mainly on feed rate. When the feed rate increases, the temperature will increase simultaneously. Therefore, the control temperature of the turning Al6061 can be controlled by the feed rate. The paper presents only on the single cut turning process. It may extend the study on multiple cutting processes to investigate the cumulative heat of temperature and compare to the ANFIS training data. The research study benefits to academic and practitioners to use for setting and control temperature on turning of the Al6061 which is widely used in the auto part industry. The ANFIS system is developed to fit with the cutting conditions on Al6061 and obtain data prediction of the temperature that occurs on the various different conditions. It is found that the cutting temperature of the Al6061 is mainly depended on the feed rate.