This paper presents an approach for the optimization of laser cutting process of aluminium alloy with multi-response outputs based on the Grey relational analysis (GRA). For experimental design, tests are planned based on Taguchi's L9 orthogonal array. The laser cutting parameters such as laser power and cutting speed are optimized with consideration of multi-response outputs such as top kerf width and surface roughness. It is observed that the laser power has stronger effect on multi-response outputs than cutting speed. According to multi-response optimization results, which are obtained from the highest value of the grey relational grade (GRG), the optimum combination is 2500 W laser power and 2.4 m/min cutting speed to simultaneously minimize the kerf width and surface roughness.

In this paper was analyzed and experimentally investigated two additive technologies: Stereolithography -SLA i Fused Deposition Modeling -FDM. The dimensional accuracy (deviation from the given dimensions in relation to the previously defined 3D CAD model as well as the surface roughness of the printed samples by the additive technologies FDM and SLA) was analyzed. The process parameters of these additive technologies were optimized in order to achieve better dimensional accuracy and less surface roughness on the products. Additionally, a comparison of FDM and SLA additive technologies was performed.

This paper presents the use of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to determine the optimum process parameters in plasma arc cutting of stainless steel. Two input process parameters, cutting speed and plasma gas pressure are considered and experiments are conducted based on Taguchi L9 orthogonal array. After performing the experiments, the surface roughness, cut perpendicularity and kerf width are measured. The analysis of variance (ANOVA) are performed in order to identify the effect of each input process parameters on the output responses. The results indicate that TOPSIS method is appropriate for solving multi-criteria optimization of process parameters. Results also showed that cutting speed of 2500 mm/min and plasma gas pressure of 6 bar are the optimum combination of process parameters.

For increase of industrial competitiveness and rapid market entry with new products, various additive technologies are increasingly being used today. This paper presents the experimental results of the study the impact of the Fused Deposit Modeling (FDM) process parameters on product quality using different materials. The work is primarily focused on optimizing the important process parameters for the FDM process using the new unexplored material. The making of test samples for dimensional accuracy and mechanical properties tests was carried out on two devices, Flashforge Finder and Ultimaker 3 with two different materials: standard PLA and new composite wood (polymer + wood) material. The obtained results show that new materials that can be produced from wood waste with a certain percentage of adhesives can be used, but before that, process parameters must be precisely defined in order to achieve satisfactory quality of the final products. In this way it has a positive impact on the environment, because wood is a natural and ecologically pure material (CO2 neutral).

This paper presents the use of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to determine the optimum process parameters in plasma arc cutting of stainless steel. Two input process parameters, cutting speed and plasma gas pressure are considered and experiments are conducted based on Taguchi L9 orthogonal array. After performing the experiments, the surface roughness, cut perpendicularity and kerf width are measured. The analysis of variance (ANOVA) are performed in order to identify the effect of each input process parameters on the output responses. The results indicate that TOPSIS method is appropriate for solving multi-criteria optimization of process parameters. Results also showed that cutting speed of 2500 mm/min and plasma gas pressure of 6 bar are the optimum combination of process parameters.

In the modern industry the use of lasers has proven to be very useful due to the high precision and quality of cut. Important indicators of the cutting surface quality are roughness of the cutting surface and . In this research experiment is performed to analyse the influence of laser power , cutting speed and assist gas pressure as independent variables on dependent variables and during HSG fiber laser cutting of 1.4307 DIN stainless steel plates, 1 mm thick, using nitrogen as assist gas. During the experiment 75 samples are cut and 225 values of each cutting surface roughness and are measured. Data obtained during the experiment are analysed using regression analysis. Mathematical model is developed for each independent variable and depending on the significant independent variables. Surface roughness values are compared and analysed according to the quality categories defined by ISO 9013: 2002 (E). It can be seen that regression analysis is good tool in modelling cutting surface quality and .

Original scientific paper The paper presents analysis of the influence of cutting parameters on surface roughness during CO2 laser cutting process of tungsten alloy by using nitrogen as assist gas, based on control charts made by statistical process control (SPC) approach. Dependent variable is surface roughness, while independent variables are laser power and cutting speed. The control chart used within this paper is a variation of the moving means chart of experimental data samples, that calculates mean and range values using the three consecutive individual values. Applying the criteria often used in the SPC methods for the assessment of "out of control" situations, it may be inferred that increasing the cutting speed leads to worsening of control status for the process with lower laser power used.

Laser cutting is a popular manufacturing process utilized to cut various types of materials. There are many non-linear interaction factors responsible for the performance of the laser cutting process. Identification of dominant factors that significantly affect cut quality is important. In this paper, the effect of the process parameters is analysed on the laser cut quality of an uncommon alloy, the tungsten alloy sheet with thickness of 1 mm. The experiments are conducted at three levels of the selected process parameters such as assist gas type (oxygen, air and nitrogen) and assist gas pressure. Taguchi design of experiments is used to obtain the optimum conditions through the study of signal to noise ratio for three quality characteristics such as kerf width, heat affected zone and surface roughness. Results of this study indicate that the optimal assist gas pressure is entirely different for kerf width, heat affected zone and surface roughness. The nitrogen as assist gas is suggested as the optimal assist gas for all of three quality characteristics.