Authors: Ruben Phipon; B.B. Pradhan
Addresses: Department of Mechanical Engineering, Sikkim Manipal Institute of Technology, P.O. Majitar, Rangpo, Sikkim, 737136, India. ' Department of Mechanical Engineering, Sikkim Manipal Institute of Technology, P.O. Majitar, Rangpo, Sikkim, 737136, India
Abstract: Drilling is an important operation in sheet metal shop. Mathematically correlating the input control variables with responses and subsequently optimising them will lead to better machining performance. The efficiency of machining processes can be improved by process parameters optimisation which identifies and determines the regions of critical process control factors leading to desired responses. Genetic algorithm (GA) is a global optimisation technique and can be applied without recourse to domain-specific heuristics. Considering the multifacet advantages of genetic algorithm, the optimisation of CNC drilling operation has been carried out in this research using this technique. Through genetic algorithm, minimum axial force obtained is 17.48 N which is 2.52 N less in magnitude than response surface methodology (RSM) predicted result. Also, the minimum torque obtained through genetic algorithm-based search is 0.208 Nm which is far less than the RSM predicted result. This clearly shows the advantages of using GA-based approach over other techniques.
Keywords: CNC drilling; parameter optimisation; response surface methodology; RSM; genetic algorithms; GAs; process parameters; CNC machining.
International Journal of Machining and Machinability of Materials, 2012 Vol.12 No.1/2, pp.54 - 65
Published online: 16 Aug 2012 *Full-text access for editors Access for subscribers Purchase this article Comment on this article