STATISTICAL MODEL BASED OPTIMAL PREDICTION ON DRILLING PARAMETERS - Saravanan, M.; Kathirvel, C. (JOURNAL OF ADVANCES IN CHEMISTRY, 2016)
The drilling is an imperative machining practice in the mechanical field for fitting or cutting the materials devoid of any disturbance. Various elements are basically employed within the automobile applications on account of the light weight, exceptional firmness and the moderate cheapness. The effectiveness of the drilled opening for the material shields is expanded by minimizing the eccentricity factor. The eccentricity is a degree of the nature of a drilled hole, and the process is based on input parameters. The significant intention of the suggested procedure is to built a mathematical modeling with the support of the optimization techniques. The mathematical modeling is done by minimizing the time consumed in the case of extension of the real time experiment. It is utilized to predict the diameter of the drill whole entry and exit, material removal rate and the eccentricity factor for the drilling process. Different optimization algorithms are utilized to find the optimal weights α and β of the mathematical modeling. All the optimum results demonstrate that the attained error values between the output of the experimental values and the predicted values are near equal to zero in the designed model. From the results, the minimum error 97.2% is determined by the mathematical modeling attained in the Artificial Fish Swarm Optimization (AFSO) process.