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Fused deposition modeling (FDM) is one of the most popular additive manufacturing technologies for various engineering applications. FDM process has been introduced commercially in early 1990s by Stratasys Inc., USA. The quality of FDM processed parts mainly depends on careful selection of process variables. Thus, identification of the FDM process parameters that significantly affect the quality of FDM processed parts is important. In recent years, researchers have explored a number of ways to improve the mechanical properties and part quality using various experimental design techniques and concepts. This article aims to review the research carried out so far in determining and optimizing the process parameters of the FDM process. Several statistical designs of experiments and optimization techniques used for the determination of optimum process parameters have been examined. The trends for future FDM research in this area are described.

Defect formation is a common problem in selective laser melting （SLM）. This paper provides a review of defect formation mechanisms in SLM. It sum- marizes the recent research outcomes on defect findings and classification, analyzes formation mechanisms of the common defects, such as porosities, incomplete fusion holes, and cracks. The paper discusses the effect of the process parameters on defect formation and the impact of defect formation on the mechanical properties of a fabri- cated part. Based on the discussion, the paper proposes strategies for defect suppression and control in SLM.

Submerged arc welding（SAW）is one of the main welding processes with high deposition rate and high welding quality.This welding method is extensively used in welding large-diameter gas transmission pipelines and high-pressure vessels.In welding of such structures,the selection process parameters has great influence on the weld bead geometry and consequently affects the weld quality.Based on Fuzzy logic and NSGA-II（Non-dominated Sorting Genetic Algorithm-II）algorithm,a new approach was proposed for weld bead geometry prediction and for process parameters optimization.First,different welding parameters including welding voltage,current and speed were set to perform SAW under different conditions on API X65 steel plates.Next,the designed Fuzzy model was used for predicting the weld bead geometry and modeling of the process.The obtained mean percentage error of penetration depth,weld bead width and height from the proposed Fuzzy model was 6.06%,6.40% and 5.82%,respectively.The process parameters were then optimized to achieve the desired values of convexity and penetration indexes simultaneously using NSGA-II algorithm.As a result,a set of optimum vectors（each vector contains current,voltage and speed within their selected experimental domains）was presented for desirable values of convexity and penetration indexes in the ranges of（0.106,0.168）and（0.354,0.561）respectively,which was more applicable in real conditions.

The smelting-separation process for metallized pellets of vanadium-bearing titanomagnetite concentrates was studied.The influences of smelting temperature,smelting time,and the basicity of the metallized pellet on vanadium and iron recovery were investigated.The characteristics of titanium slag were analyzed using X-ray diffraction,energy dispersive spectroscopy,and mineralographic microscopic analysis.The results demonstrate that appropriate increases in smelting temperature and smelting time can improve the vanadium and iron recovery from metallized pellets and are beneficial for the slag-iron separation.Although increasing the basicity of the metallized pellet can considerably improve the vanadium and iron recovery,the TiO_2 grade of titanium slag was decreased.Under the optimal conditions,90.17% of vanadium and 92.98% of iron in the metallized pellet were recovered,and the TiO_2 grade of titanium slag was 55.01%.It was found that anosovite,augite,spinel,glassiness,and metallic iron were the main mineral phases of the titanium slag.

In this paper, simulations of deep drawing tests at elevated temperatures were carried out with experimental validation. The aim of this work was to study the effect of process parameters on formability and mechanical properties of aluminum alloy 7075 in hot stamping process.Process parameters, including blank temperature, stamping speed, blank holder force and friction coefficient, were studied. Stamping tests were conducted at temperatures between 350 and 500 ℃, blank holder force between 0 and 10 kN, stamping speed between 50 and 150 mm·s^-1, and friction coefficient between 0.1 and 0.3. Based on the analysis, it is shown that thickness homogeneity could be improved when the blank is formed at lower temperature,lower blank holder force and lower friction coefficient.Formability could be improved when the blank was well lubricated at about 400 ℃. Formability at stamping speed 50 mm·s^-1 is far better than those at other speeds. The mechanical property analysis shows that the hot stamping process could make the formed part to obtain high quality.

This article deals with the optimization of process parameters for friction welding of Incoloy 800 H rod and compares the results obtained by response surface methodology（RSM） and artificial neural network（ANN）.The experiments were carried out on the basis of a five-level,four-variable central composite design.The output parameters were the tensile strength and burn-off length（BOL）.They were considered as a function of four independent input variables,namely heating pressure（HP）,heating time,upsetting pressure（UP）,and upsetting time.The RSM results showed that the quadratic polynomial model depicted the interconnection between individual element and response.For optimizing the process parameters,ANN analysis was used,and the optimal configuration of the ANN model was found to be 4–9–2.For modeling aspect,a requisite trained multilayer perceptron neural network was rooted,and a quick propagation training algorithm was used to train ANN.The purpose of optimization was to decide the maximum tensile strength and minimum burn-off length of the welded joint which was done by varying the friction welding process variables.The order of importance of input parameters for friction welding of Incoloy 800 H was HP〉 UP〉 N〉BOL.After predicting the model using RSM and ANN,a comparison was made for predicting the effectiveness of two methodologies.By analyzing the results,it was observed that as compared to RSM,ANN model was more specific.

To achieve high efficiency utilization of Panzhihua vanadium titano-magnetite, a new process of metalizing reduction and magnetic separation based on hot briquetting is proposed, and factors that affect the cold strength of the hot-briquetting products and the efficiency of reduction and magnetic separation are successively investigated through laboratory experiments. The relevant mechanisms are elucidated on the basis of microstructural observations. Experimental results show that the optimal process parameters for hot briquetting include a hot briquetting temperature of 475°C, a carbon ratio of 1.2, ore and coal particle sizes of less than 74 μm. Additionally, with respect to metalizing reduction and magnetic separation, the rational parameters include a magnetic field intensity of 50 mT, a reduction temperature of 1350°C, a reduction time of 60 min, and a carbon ratio of 1.2. Under these above conditions, the crushing strength of the hot-briquetting agglomerates is 1480 N, and the recovery ratios of iron, vanadium, and titanium are as high as 91.19%, 61.82%, and 85.31%, respectively. The new process of metalizing reduction and magnetic separation based on hot briquetting demonstrates the evident technological advantages of high efficiency separation of iron from other valuable elements in the vanadium titano-magnetite.

According to different energy utilization in different regions, blast furnace is divided into raceway zone, bottom heat exchange zone （BHZ）, thermal reserve zone （TRZ）, and top heat exchange zone （THZ）, and a mathe- matical model of nitrogen free blast furnace （NF-BF） is established. The optimum process parameters of two kinds of nitrogen free blast furnaces are calculated by the new mathematical model. The results show that for the nitrogen free blast furnace with a single row of tuyeres, the optimum process parameters are coke ratio of 220 kg/t, coal ratio of 193 kg/t, and volume of recycling top gas of 577 m3/t; for two rows of tuyeres, the process parameters are coke ratio of 202 kg/t, coal ratio of 211 kg/t, volume of recycling top gas in upper area of 296 m3/t, and volume of recy- cling top gas in lower area of 295 ma/t. Energy balances are reached in different regions. Theoretical combustion temperature （TCT） in raceway zone is largely affected by different processes, and a lower TCT should be adopted for the single row of tuyeres, but for two rows of tuyeres, a higher TCT should be maintained. Compared with tradi- tional blast furnace, in NF-BF, the emission of CO2 would be reduced by 45.91% and 49.02G for a single row of tuyeres and two rows of tuyeres, respectively, and combined with CO2 sequestration technology, zero emission of CO2 could be realized.

The optimum friction welding (FW) parameters of duplex stainless steel (DSS) UNS S32205 joint was determined. The experiment was carried out as the central composite array of 30 experiments. The selected input parameters were friction pressure (F), upset pressure (U), speed (S) and burn-off length (B), and responses were hardness and ultimate tensile strength. To achieve the quality of the welded joint, the ultimate tensile strength and hardness were maximized, and response surface methodology (RSM) was applied to create separate regression equations of tensile strength and hardness. Intelligent optimization technique such as genetic algorithm was used to predict the Pareto optimal solutions. Depending upon the application, preferred suitable welding parameters were selected. It was inferred that the changing hardness and tensile strength of the friction welded joint influenced the upset pressure, friction pressure and speed of rotation.

Thermomechanical experiments were carried out to reproduce the hot stamping process and to investigate the effects of process parameters on the microstructure and mechanical properties of stamped parts. The process parameters, such as austenitizing temperature, soaking time, initial deformation temperature and cooling rate, are studied. The resulting microstructures of specimens were observed and analyzed. To evaluate the mechanical properties of specimens, tensile and hardness tests were also performed at room temperature. The op-timum parameters to achieve the highest tensile strength and the desired microstructure were acquired by comparing and analyzing the results. It is indicated that hot deformation changes the transformation characteristics of 22MnB5 steel. Austenite deformation promotes the austen-ite-to-ferrite transformation and elevates the critical cooling rate to induce a fully martensitic transformation.