In this paper, the effects of the deposition speed and thermal cycles in gas-metal arc-welding (GMAW) additive manufacturing on the quality of as-built 308L stainless steel thin walls were investigated. The results exhibit that the deposition speed and thermal cycles play a crucial role in the quality of produced parts. An increase in deposition speed results in an improvement in the surface waviness. The surface waviness (Sa) decreases from 286 to 138 µm as the deposition speed increases from 0.2 to 0.4 m/min. On the other hand, the growth of microstructures in the walls fabricated with different deposition speeds shows a similar trend. The microstructure of as-built 308L-stainless-steel walls consists of dominant columnar/equiaxed dendrites of austenite and small amount of ferrite remaining in grain boundaries. The deposition speed mainly influences the grain size in microstructures. In the middle part of the walls, an augmentation in the deposition speed leads to a decrease of the secondary dendrite arm spacing, which results in an enhancement in mechanical properties of the walls. The microhardness and ultimate tensile strength increase from 153 ± 7.16 to 164 ± 8.96 HV0.1 and from 483 ± 4.24 to 518 ± 2.83 MPa, respectively, when the deposition speed increases from 0.2 to 0.4 m/min.
The goal of this work is to validate the existing plasma spray mathematical models, using a calculation method and the comparison with experimental data, in order to determine their validity. A preliminary evaluation of the adhesion based on the velocity and temperature of the particles is useful to be calculated by using the mathematical model. Given the thermal-physical properties and chemical composition of a Fe-based amorphous X-5 powder, a modified model was suggested. For comparison, a series of experiments using plasma spraying of the X-5 powder were conducted. The significance of the current study consists of the model validation by using the data of the plasma spraying of the Fe-based amorphous material as a potential substitution for saving production costs by using ordinary air as the plasma generation gas. The findings show the discrepancy between the models and the experimental results. The prediction of adhesion using the mathematical models does not cover essential parameters such as the enthalpy of the particle stream. It is necessary to improve the mathematical models, including the modified one, based on the experiment results, with different pairs of particles and substrate materials. The proposed formula is applicable during the preliminary design of the spray process and the development of a new torch construction.
Multi-criteria decision making to choose the best option is a complicated task but a required activity in all fields. The problem will be more complicated if, after making a decision, one/several options are added to the list of options to be ranked. In this case, if only a certain multi-criteria decision making method is used, the decision-making shall be required to be started over again. This study recommends a simple solution to overcome this situation. The recommended solution is a combination between the Design Of Experiments method and a certain multi-criteria decision making method. Simple Additive Weighting method was selected in this study as one of the multi-criteria decision making methods for testing. Use the Design Of Experiments method to design an experiment matrix with the main input parameters being the criteria of options. The Simple Additive Weighting method is applied to calculate the output value of each experiment, called the score of the experiment. Develop a mathematical relation between the scores of the experiments and the criteria. This relation is used to recalculate the scores for options to be ranked. Three different cases were performed to evaluate the effectiveness of the new method. The results of ranking alternatives by new method have been compared with when using other methods. Sensitivity analysis was also performed in each case. The generation of different scenarios is done using different methods to determine the weights for the criteria. The best alternative determined when using the new method is always similar to when using other methods. In addition, when using the new method, the best alternative is determined regardless of the method of determining the weights for the criteria. The obtained results have proved the accuracy of the methodology and the advantages of the recommended method. Future work is also mentioned in the last part of this article
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