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In plasma cutting, a noble gas at high speed is blown from the nozzle and ionized with the help of a frequency spark at high voltage and an electric arc is created which cause the gas changes to the plasma state. Plasma cutting is an ideal process for cutting of the hard metals. In this research, the effect of the input parameters and their optimization in plasma cutting of AISI 309 stainless steel were studied. By conducting the different experimental tests, the effect of input parameters including amperage, gas pressure and the cutting speed of torch on the three output parameters of the width of cut (Kerf), heat-affected zone (HAZ) and surface roughness (Ra) were investigated. Analysis of the results showed that the amperage, cutting speed and gas pressure have the highest impact on the output parameters, respectively. The artificial neural network (ANN)-genetic algorithm was used to predict and optimize the output parameters. The results indicate that the artificial neural networks model trained by the genetic algorithm are able to predict the output parameters accurately. Finally, the optimization of output parameters to achieve the best cutting conditions was carried out using the genetic algorithm. The artificial neural network models were considered as the objective function and also, the parameters of the heat-affected zone, surface roughness, and the width of cut were introduced as inputs of the algorithm. According to results, a combination of the neural network and genetic algorithm is an efficient method for optimization of the plasma cutting process. This method can be easily modified and utilized for other advanced cutting methods.

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Kerf width (cutting width) is an important quality parameter in the laser cutting process, and if it is less, means higher cutting accuracy and lower cost of materials. In this study, using a fiber laser-cutting machine, which is one of the new generation lasers, the effect of all parameters affecting the kerf width has been investigated. These parameters include laser power (450 to 750 watts), cutting speed (30 to 130 mm/s), focal point position (5 to +5 mm), nozzle standoff (0.6 to 2.5 mm) and gas pressure (1.2 to 1.8 bar), for the cut of stainless steel 316L sheet with a thickness of 0.8 mm. After measuring the kerf width with a special imaging system and analyzing the results with ANOVA, it was found that laser power and gas pressure were directly related to the kerf width and the cutting speed and nozzle standoff were inversely related to the kerf width. Laser focal point position was also determined as the most effective parameter in the formation of the kerf width, which should be on the surface to minimize the kerf width. In this study, it was shown that with the correct adjustment of the parameters, material consumption and cutting accuracy are improved up to 70%. In addition, by using linear regression, the model of kerf width changes with respect to various parameters has been obtained and by comparing its response with the experimental results, acceptable model accuracy has been observed.

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abrasive water jet is one of the most popular cutting methods today due to its ability and unique features such as the ability to cut complex shapes as well as the wide range of materials and non - creation of thermal distortion at the cutting site. The accuracy of the process is mainly due to selecting the cutting parameters. The sheet used in this study is aluminum 7075 with a thickness of 25 mm. In this research, for water jet pressure, forward speed and nozzle distance to the surface of the workpiece, three surfaces and for the impingement angle of two surfaces were considered. In order to investigate the quality of the cut - off area, the effect of process parameters on the high and low width of the cut section and also the cut - surface slope is investigated. Finally, the cut gap created by this process has special geometrical features that in some cases is the limitation of the process. The results showed that the change in the direction of the water jet from the perpendicular to the surface of the work piece, although the width of the cutting crack cannot be changed, the surface quality decreases and the cutting surface slope increases.
 

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Achieving optimal parameters in production processes is crucial in the military industry, as the products are highly complicated and resistant. Because there is no heat generation in the cutting area, abrasive water jet machining is a particularly popular procedure. This study looked into how input variables affected the abrasive water jet machining of rolled homogenous armour steel. The material removal rate, surface roughness, and Kerf angle regression equations were analyzed using the E-fast method of statistical sensitivity analysis. The findings demonstrated that the standoff distance, with a 74% impact, is the most effective parameter on the kerf angle, and the jet traversal speed, with a 95% and 50% impact on the material removal rate and surface roughness, respectively. In addition, pressure had the least effect on three variables of material removal rate, surface roughness and kerf angle.