In the present work, predictive modelling and optimization with the adaptive network based fuzzy inference system (ANFIS) modelling of the mechanical properties of laser-coated NB/SiC/Ni welds was studied based on the Taguchi design by laser cladding. An ANFIS model based on a Sugeno type fuzzy inference system was developed for predicting the hardness properties of SiC/BN/Ni welds by laser cladding with experimental data required for network training and prediction. Based on analysis of variance, three important factors were taken as inputs for the fuzzy logic inferences, while the hardness properties were taken as the output of the ANFIS. The microstructure of welds was analysed using scanning electron microscopy with an energy-dispersive X-Ray spectrometer. Highly developed leaf-like dendrites and eutectic crystals were found in some areas of the melting zone for the BN/SiC/Ni weld, which was significantly hardened. The ANFIS model based on Taguchi’s design provides a better pattern of response because the predicted and experimental values were highly similar. As a result, a satisfactory result was achieved between the predicted and experimental values of hardness in laser-coated NB/SiC/Ni welds, whereby the success and validity of the method was verified.

In the present work, the optimization of ceramic-based composite WC(Co,Ni) welds by laser cladding was carried out using response surface methodology based on finite element analysis. The heat distribution and temperature field of laser-melted WC(Co,Ni) ceramic coatings were simulated using ANSYS software, which allowed the computation of the distribution of residual stresses. The results show that the isotherms in the simulation of the temperature field are elliptical in shape, and that the isotherms in front of the moving heat source are dense with a larger temperature gradient, while the isotherms behind the heat source are sparse with a smaller temperature gradient. In addition, the observed microstructural evolution shows that the melting zone domains of WC(Co,Ni) are mainly composed of unmelted carbides. These carbides are dendritic, rod-like, leaf-like, or net-like, and are agglomerated into smaller groups. The W content of these unmelted carbides exceeds 80%, while the C content is around 1.5–3.0%. The grey areas are composed of WC, Co and Ni compounds. Based on the regression model, a quadratic model was successfully constructed. A three-dimensional profile model of the residual stress behaviour was further explored. The estimated values of the RSM-based FEA model for residual stress are very similar to the actual results, which shows that the model is effective in reducing residual stress by laser cladding.

This report investigates the thermal performance of light-emitting diodes (LEDs) using a heat sink structure based on an optimized design and a sprayed cuprous oxide (Cu ₂ O) coating. An orthogonal array of 18 aluminum plates with various heat-dissipated structures was created. The optimal junction temperature of the LED package is determined by using the signal-to-noise ratio (S/N) of the heat-dissipated structure based on Taguchi’s method as well as the heat dissipation coating. According to the analysis of variance, the most important factors that influence the junction temperature can be obtained as the depth of groove, the layout of holes, the layout of LEDs, and the number of Cu block. These significant factors constituted approximately 91.06% of the variation in the experiment. The results show that by optimizing the structure of the LED heat sink based on the heat-dissipated coating, the efficiency of the junction temperature is increased by 23.88%. Also, a gain of 1.30 dB corresponds to a 9.67% reduction in variance, which indicates the improvement through the optimal setting by 1.162 times of variance, showing good reproducibility. Overall, the coating is based on the optimized design of the structure of the heat sink that has good heat transfer capability, which can provide a good solution to the heat-dissipated problem of LED and further give guidance to the future development of LED.

In this study, we investigated ceramic-matrix composite coatings created by laser cladding on 45 steel using tungsten carbide (WC) powder with varying weight percentages of Co or Ni additives. Our analysis focused on the influence of Co additives in WC powders on the key properties of the coatings, including the microstructural evolution, hardness, wear, and residual stress behaviors. High residual stresses led to significant cracking in coatings comprising 100% WC. The addition of Co at a concentration of 20% to WC reduces the cracking activity. The microhardness of the coating exceeded that of the substrate by a factor of more than five. The microstructural evolution revealed a typical intergranular fracture in the molten zone, with cracks propagating through the interior of the unmelted WC at 100% WC. In addition, by adding Ni alloys, the composite coatings were extended to three mixtures: WC-Co, WC-Ni, and WC-Co-Ni. The relationship between the three-component mixtures and wear volume of the laser cladding was established, and the ratios of the three-component mixtures were optimized. A reduced quadratic model for three-component mixtures, which provided a better mixture ratio pattern, showed an excellent fit. Based on the experimental results, the developed three-component mixture with better mixture ratios can enhance anti-wear behavior. A satisfactory agreement was obtained between the predicted and experimental values of the wear volume of the laser-coated welds. Overall, our study accomplishes the optimization of the mixture ratio of the three components, which ensured a reduction in the wear of the welds, thereby improving the performance of laser-coated welds.

This work involves the preparation of WC/Co/Ni blends using different mixing ratios to form Co/Ni/WC composite-based coatings by laser cladding. The effect of each component and their mixtures on the mechanical properties was evaluated using a mixture design approach. The morphologies and microstructures of the laser clads were characterized using a scanning electron microscope and X-ray diffraction techniques. Cracking behavior and fracture based on residual stresses are explored. In addition, the mathematical models between the three-component mixtures and the mechanical properties of the laser clad were established. The results showed that the welds containing 50 % WC-50 % Ni alloys were successfully deposited by laser cladding with favorable mechanical properties. These welds reduced the remarkable fracture crack activities and did not cause delamination in the laser clads. An increase in WC content significantly enhances wear resistance and microhardness, except for the crack susceptibilities in all mixtures. Additionally, when increased Co/Ni on WC, the reduction of adhesive wear is more significant than that of abrasive wear. Wear resistance is improved by the high content of WC particles in the laser-clad joints. Based on the mixture models, better mixed ratios for the blends that were developed using a multi-objective superimposed optimization technique make these blended materials promising candidates and can ensure the quality of laser clads. The findings from this study will greatly contribute to optimizing the blend ratio of the three-ingredient mixture based on mixture design to enhance structural evolution and mechanical properties, and also obtain better quality laser-clad coatings.

The purpose of this paper is to construct an evaluation system for AI painting software based on generative adversarial network (GAN) technology, which optimizes the performance of the related software in terms of functionality, ease of use, system performance, and safety. The results of the questionnaires are statistically analyzed. In addition, an exploratory factor analysis was conducted to extract the data of the study, which were ultimately used to calculate the weight and importance of each index using the fuzzy hierarchical analysis method. This study constructed an evaluation system for AI painting software based on GAN technology, including 16 indicators of functionality, 16 indicators of ease of use, 7 indicators of system performance, and 8 indicators of safety, respectively, whose alpha coefficients were 0.882, 0.962, 0.932, 0.932, and 0.932, respectively. In addition, the accumulated explanatory variances of their coefficients were 84.405%, 84.897%, 84.013%, 72.606%, 73.013%, and 72.606%, respectively. It is clear that the items included in each of the indicators are homogeneous, with a high degree of internal consistency. This paper suggests that the development of AI painting software focusing on functionality, ease of use, system performance, and safety can enhance the market competitiveness of the software.