AN INTERDISCIPLINARY OPTIMIZATION APPROACH FOR CUTTING ATTRIBUTES OF LASER BEAM MACHINING
To improve and optimize the responses of a machining process, the choice of input machining control parameters is to be set at an optimal value. As such one has to take up experimental methods, which are cumbersome, time-consuming, costly, and at times not feasible. During such situations, optimization techniques like Genetic Algorithm (GA) can be used as they provide a cost-effective method for solving such complex problems. Laser beam cutting is a non-traditional machining process that can be successfully used for the cutting of conductive and nonconductive difficult-to-cut advanced engineering materials such as reﬂective metals and composites. Al7075 aluminum alloy as matrix and silicon carbide (SiC) as reinforcement is a widely used material having potential applications in aircraft and space industries because of its lower weight-to-strength ratio. Considering these, an attempt is made for the optimization of Nd: YAG Laser beam cutting of Al7075/10%/SiCp metal matrix composite. In this research work, the desired responses are minimum kerf width and kerf deviation. The process parameters considered are pulse power, pulse frequency, assist gas pressure and pulse width. Experiments are conducted using a central composite design and the mathematical models correlating the desired responses and the control parameters are established using Response Surface Methodology (RSM). These models give the factor effects of the individual process parameters. Finally, GA is applied to search the optimal machining parameters.
Laser cutting, Nd: YAG, kerf width, kerf deviation, Response Surface Methodology, Genetic Algorithm.