Genetic Algorithm Based Optimization of Cutting Parameters in CO2 Laser Beam Cutting of Cow Leather

Author(s):  
Thangaraj Muthuramalingam ◽  
Swaminathan Vasanth ◽  
Sanjeev Gupta ◽  
Vu Ngoc Pi
2020 ◽  
Vol 38 (10A) ◽  
pp. 1489-1503
Author(s):  
Marwa Q. Ibraheem

In this present work use a genetic algorithm for the selection of cutting conditions in milling operation such as cutting speed, feed and depth of cut to investigate the optimal value and the effects of it on the material removal rate and tool wear. The material selected for this work was Ti-6Al-4V Alloy using H13A carbide as a cutting tool. Two objective functions have been adopted gives minimum tool wear and maximum material removal rate that is simultaneously optimized. Finally, it does conclude from the results that the optimal value of cutting speed is (1992.601m/min), depth of cut is (1.55mm) and feed is (148.203mm/rev) for the present work.


2012 ◽  
Vol 424-425 ◽  
pp. 1102-1106
Author(s):  
Hao Jin Yang ◽  
Xu Hong Guo ◽  
Dong Dong Wan ◽  
Ting Ting Chen

Data timeliness of cutting process data is so intenser under the new situation than ever .It’s especially necessary to propose the physical model on which the optimization of cutting parameters is based. In this paper the mathematical model is established by the analysis of the data measured from the cast iron experiments, then use MATLAB genetic algorithm analysis to calculate the optimum combination of cutting parameters. The results show that the optimum combination of cutting parameters could improve the production efficiency in practice.


2011 ◽  
Vol 121-126 ◽  
pp. 4640-4645 ◽  
Author(s):  
Shu Ren Zhang ◽  
Xue Guang Li ◽  
Jun Wang ◽  
Hui Wei Wang

Three elements of Cutting dosages have a great effect on parts surface quality and working efficiency, the best organization of cutting three elements for parts surface quality must be found before machining, in order to surface roughness and machining cost of parts, multi-objective optimization model is established in this paper, model is solved by using genetic algorithm. Based on the BP neural network of three layers, forecasting model of surface roughness is established. According to existing experiment data and optimized cutting dosages, analysis and prediction of surface roughness is done. Machining experiment is done by using optimized data. The experiment result verifies feasibility of this optimistic method and prediction method of surface roughness.


Author(s):  
Constantin Cristinel Girdu ◽  
Badea Lepădătescu

he laser beam is a source of radiation with concentrated energy. The characteristics of the laser beam (spot energy, focal spot diameter, spot temperature) are aspects theoretically researched in this paper. The intensity of the laser beam transmitted to the surface of the part has a Gaussian shape. A CO2 laser was used in the processing of parts from a HARDOX400 steel sheet with a thickness g = 8mm. The values of the cutting parameters were established by sample tests. An experimental design with 27 observations was analyzed. The width of the cutting slot at the straight profile was measured. Physical quantities derived from the cutting parameters and working parameters used were calculated. Spot energy, cost and interaction time were determined and evaluated using the mathematical model given by GRAPH. The research findings show that the best values of the factors studied converge to average values in minimizing Kerf.


Sign in / Sign up

Export Citation Format

Share Document