Affiliation:
1. P.S.R. Engineering College
2. Lord Jeganath College of Engineering and Technology
3. SCAD College of Engineering and Technology
4. Ramco Institute of Technology
Abstract
A mechanical work piece created industrially frequently contains more than one machining process. Furthermore, it is a common activity of programmers, who make this selection every time a milling and drilling operation is conducted. Tool wear and borehole quality are two essential challenges for high precision drilling procedures, with Al 356 alloy being employed in experimental planning. Drilling specifications will be assessed in this work to get optimal parameters in minimizing the influence of drilling damage on alloy using a swarm-based optimization model. The drilling parameters are optimized using the Bacterial Foraging Optimization (BFO) method, which includes three control factors: depth, feed rate, and spindle speed. Each parameter is designed in three levels, with multiple performance characteristics such as thrust force, surface roughness, and delamination factor. This investigation was carried out in order to obtain the proper optimization. The feed rate, next to the spindle speed, was discovered to be the essential element inducing lamination in drilling, with this phenomenon occurring in each diameter of the drill bit. The results reveal that the feed rate and drill type are the most important parameters influencing the drilling process, and that employing this strategy can successfully improve drilling process outcomes.
Publisher
Trans Tech Publications, Ltd.
Reference20 articles.
1. Optimization of machining parameters in drilling hybrid aluminium metal matrix composites;RAJMOHAN;Transactions of Nonferrous Metals Society of China
2. Multi objective optimisation of machining parameters during high speed drilling of Ti6Al4V alloy under dry condition;Krishnaraj;International Journal of Materials Engineering Innovation
3. Machinability analysis in drilling woven GFR/epoxy composites: Part I – Effect of machining parameters;Khashaba;Composites Part A: Applied Science and Manufacturing
4. Patwari, Md Anayet U., SM Tawfiq Ullah, Ragib Ishraq Khan, Md Mahfujur Rahman, Prediction and optimization of surface roughness by coupled statistical and desirability analysis in drilling of mild steel, Ann. Fac. Eng. Hunedoara. Int. J. Eng. 11 (2) (2013): 161-166.
5. Influence of rotation speed, transverse speed, and pin length during underwater friction stir welding (UW-FSW) on aluminum AA6063: A novel criterion for parametric control;Kumar;International Journal of Lightweight Materials and Manufacture