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- W2116964908 abstract "To improve and optimize the responses of a Laser Beam machining process, the various input machining control parameters are to be set at an optimal value. As such one has to adopt 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 it provides a cost effective method for solution of such complex problems. Unlike traditional optimization techniques, GA is a robust and performs well in multimodal optimization problems. Considering these advantages of GA, optimization of Nd:Yag Laser beam machining process is done using this technique. In this research work, the desired responses are minimum kerf taper and surface roughness. The process control parameters considered are Oxygen pressure, pulse width, pulse frequency and cutting speed. Experiments are designed and the mathematical models correlating the desired responses and the control parameters are established using Response Surface Methodology (RSM). Finally, GA is applied to search the optimal parametric values for the optimal responses. Using Genetic Algorithm, minimum Kerf taper obtained is 0.14695° which is 0.313° less in magnitude than experimentally measured value. Also, minimum surface roughness predicted using GA is 1.2625µm which is 0.3375µm better in value compared to the experimental measured value. The average percentage prediction error of GA is found to be 3.35% for kerf taper and 4.02% for surface roughness. Thus, the results prove GA to be a novel optimization technique which can be used to optimize Laser beam machining processes." @default.
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- W2116964908 date "2012-01-01" @default.
- W2116964908 modified "2023-09-26" @default.
- W2116964908 title "Control Parameters Optimization of Laser Beam Machining Using Genetic Algorithm" @default.
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