Multi-Objective Optimization of Metal Removal Rate, Dimensional and Profile Accuracy during Drilling of ASTM A516 (Grade70) Steel

Abstract:

The aim of this research work is identification of optimum drilling parameters to increase material removal rate, dimensional and profile accuracy during drilling. ASTM A516 (Grade70) which is a boiler quality plate of 12 mm thickness was considered as the specimen for conducting the experiments. The experiment was done based on full factorial design using 18 experiments generated using Minitab Software. Two levels for tool material and three levels for feed-speed combination and cutting environment were considered. Two runs were carried out for each trial. The metal removal rate was calculated for each hole drilled. The mean result of the two runs of a trial was taken as the result of the trial. The drilled holes were then tested for their dimensional, profile accuracies. With these results in hand the Artificial Neural Network software was trained to predict the optimized input parameters for drilling a hole of required dimensional and profile accuracies and with required metal removal rate.

• Periodical: Key Engineering Materials (Volume 933)
• Pages: 97-106
• DOI: https://doi.org/10.4028/p-19hm0h
• Online since: October 2022
• Authors: S. Vinoth Kumar, R. Rekha*, M. Gokula Rajan, C. Adhinathan, E. Jessinth Blesso, B. Karthik
• Keywords: Artificial Neural Network, Dimensional Accuracy, Drilling, Full Factorial Method, Metal Removal Rate, Profile Accuracy

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