Optimization of Hard Turning Machining Parameters Using Swarm Intelligence Technique

Abdul Syukor, Mohd Jaya and Yogan, Kumar and Ruzaidi, Zamri (2009) Optimization of Hard Turning Machining Parameters Using Swarm Intelligence Technique. Project Report. UTeM, Melaka, Malaysia. (Submitted)

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Abstract

Using the Machining Data Handbook for choosing cutting condition for material hardness that lie at the middle of the group is simple and clear. However, there exists a degree of vagueness with the boundary cases, where two choices of cutting speeds are applicable for one choice of materi al hardness. ln th is situ ation, the skilled operator takes a decision for using the appropriate cutting speed, based on their experience. However, this method of choosing data by the individual operator is not very desirable, because it may vary fi·om operator to operator. Therefore it is desirable to have an operatorindependent data selection system for choosing machining operation. Thus, the prediction of cutting speed parameter in turning process by using fuzzy logic technique with triangular and Gaussian membership functions were developed. The cutting speed is predicted fro m three input parameters whereby material hardness, depth of cut and feed rate that is taken from Cutting Data for Turn ing of Steels book. Performance of the results for the both membership functions are compared to the recommended machining parameters from handbook. Fuzzy Logic Toolbox in MA TLAB with fuzzy-Mamdani technique ware selected as a software and technique to develop the fuzzy rules. Comparison of the both membership func tions shows that fuzzy with triangular membership function perform better result and nearer with recommended machining parameter compared to fuzzy with Gaussian membership function.

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