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Authors
Affiliations
1 Department of Industrial & Production Engineering, B V B College of Engineering & Technology, Hubli 580 031, IN
2 Department of Electrical & Electronics, B V B College of Engineering & Technology, Hubli 580 031, IN
3 Department of Mechanical Engineering, G M Institute of Technology, Davangere 577 006, IN
4 Department of Industrial & Production, UBDT College of Engineering, Davangere 577 004, IN
Source
Manufacturing Technology Today, Vol 4, No 5 (2005), Pagination: 3-6
Abstract
This paper describes the procedure of Genetic Algorithm (GA) optimization for reduction of burr geometry in drilling process, modeled using Response Surface Methodology (RSM). Since debarring processes are not yet well automated, it is essential to understand the mechanism of burr formation in drilling and affecting variables to control burr geometry at the production stage itself Second order mathematical models of burr geometry viz. burr height and burr thickness are developed using central composite rotatable design of experiments for drilling of EN8 work pieces. In this work, the effect of cutting speed, feed, drill diameter, point angle and clearance angle on burr height and thickness have been investigated. The RSM models are then employed with GA, which is a search algorithm based on the mechanics of natural selection and natural genetics, to minimize the burr geometry.
