Modeling and Experimental Investigation of the Impact of the Hemispherical Tool on Heat Generation and Tensile Properties of Dissimilar Friction Stir Welded AA5083 and AA7075 Al Alloys

This study investigated the effect of a hemispherical friction stir welding (FSW) tool on the heat generation and mechanical properties of dissimilar butt welded AA5083 and AA7075 alloys. FSW was performed on the dissimilar aluminum alloys AA5083-H111 and AA7075-T6 using welding speeds of 25, 50, and 75 mm/min. The tool rotation rate was kept constant at 500 rpm. An analytical model was developed to calculate heat generation and temperature distribution during the FSW process utilizing a hemispherical tool. The experimental results were compared to the calculated data. The latter confirms the accuracy of the analytical model, demonstrating a high degree of agreement. Sound FSW dissimilar joints were achieved at welding speeds of 50 and 25 mm/min. Meanwhile, joints created at a welding speed of 75 mm/min exhibited a tunnel-like defect, which can be attributed to the minimal heat generated at this particular welding speed. At a lower welding speed of 25 mm/min, a higher tensile strength of the dissimilar FSWed joints AA5083 and AA7075 was achieved with a joint efficiency of over 97%.

An intelligent fuzzy-particle swarm optimization supervisory-based control of robot manipulator for industrial welding applications

The propensity of manufacturers to produce goods at affordable cost, with more accuracy, and at a faster rate force them to search for novel solutions, such as deploying robots in place of people in a sector that can accommodate their needs. Welding is one of the most crucial processes in the automotive industry. This process is time-consuming, subject to error, and demands skilled professionals. The robotic application can improve this area of production and quality. Other industries, such as painting and material handling, can also profit from the use of robots. This work describes the fuzzy DC linear servo controller, which functions as a robotic arm actuator. Robots have been widely employed in most productive sectors in recent years, including assembly plates, welding, tasks at higher temperatures, etc. Controlling a robot accurately is a difficult undertaking as a robot is very nonlinear with many joints that are often organized and unstructured. To carry out the effective task, an effective PID control based on fuzzy logic has been employed together with the method of Particle Swarm Optimization (PSO) approach for the estimate of the parameter. This offline technique determines the lowest number of optimal robotic arm control parameters. To verify the controller design with computer simulation, a comparative assessment of controllers is given by means of a fuzzy surveillance controller with PSO which improves the parameter gain to provide a rapid climb, a smaller overflow, no steady condition error signal, and effective torque control of the robot arm.

Optimization of Bobbin Tool Friction Stir Processing Parameters of AA1050 Using Response Surface Methodology

The current research designed a statistical model for the bobbin tool friction stir processing (BT-FSP) of AA1050 aluminum alloy using the Response Surface Method (RSM). The analysis studied the influence of tool travel speeds of 100, 200, and 300 mm/min and different pin geometries (triangle, square, and cylindrical) at a constant tool rotation speed (RS) of 600 rpm on processing 8 mm thickness AA1050. The developed mathematical model optimizes the effect of the applied BT-FSP parameters on machine torque, processing zone (PZ) temperature, surface roughness, hardness values, and ultimate tensile strength (UTS). The experimental design is based on the Face Central Composite Design (FCCD), using linear and quadratic polynomial equations to develop the mathematical models. The results show that the proposed model adequately predicts the responses within the processing parameters, and the pin geometry is the most influential parameter during the BT-FSP of AA1050. The analysis of variance exhibit that the developed mathematical models can effectively predict the values of the machine torque, PZ temperature, surface roughness, hardness, and UTS with a confidence level of over 95% for the AA1050 BT-FSP. The optimization process shows that the optimum parameters to attain the highest mechanical properties in terms of hardness and tensile strength at the lowest surface roughness and machine torque are travel speed (TS) of 200 mm/min using cylindrical (Cy) pin geometry at the constant RS of 600 rpm. The PZ temperature of the processed specimens decreased with increasing TS at different pin geometries. Meanwhile, the surface roughness of the processed passes and machine torque increased with increasing the TS at different pin geometries. Increasing TS from 100 to 300 mm/min increases the hardness values of the processed materials using different pin geometries. The highest UTS of 79 MPa for the processed specimens was attained at the TS of 200 mm/min and RS of 600 rpm using the Cy pin geometry.

The Role of Al-10%Si Coating in the Manufacture and Use of Aluminized Open-Joint Steel Tubes

The paper presents the results of laboratory and industrial tests on the role of Al-10%Si coatings in the manufacture and use of welded aluminized steel tubes. The tubes were fabricated from DX53D + AS120 steel tubes coated with Al-10%Si coating. Investigations were carried out on individual processes in the manufacture of welded tubes aimed at determining the effect of the coating properties on the conditions of the forming process and vice versa. In the next step, a quality assessment has been conducted on the finished tubes. Then, selected tests simulating the operating conditions of tubes used for the elements of exhaust systems are presented. Analyses of the susceptibility of strips to plastic deformation and evaluation of the adhesion of the Al-10%Si coating to the steel base metal were carried out using bending tests. From the results, it was proved that the Al-10%Si coating determines the technical features of the workpiece material, affects the manufacturing process, and determines the quality of aluminized steel tubes. The quality of the coating surface depended on the annealing temperature and annealing time. The higher the temperature, the shorter the time needed to produce a change in the coating properties. A p-value reported from a tests is less than 0.05.

A Novel Study of Synthesis and Experimental Investigation on Hybrid Biocomposites for Biomedical Orthopedic Application

In recent years the biocomposites are highly utilized in the biomedical applications, due to excellent strength as well as weight ratio. A lot of natural fibers, namely, flax, hemp, jute, kenaf, and sisal are cheaply available in colossal amount. Aim of this study, a novel approach, is executed for construction of biomedical orthopedic parts by using mixture of natural fibers. This work handled biocomposites such as flax fiber (FX), chicken feather fiber (CF), kenaf fiber (KF), and rice husk fiber (RH) effectively. From all these composites, four sets of mixed fibers with reinforcement of polylactic acid polymer used for creating orthopedic parts. The hand-lay-based methodology is undertaken for preparation of hybrid biocomposites. Parameters involved for this study are fiber types (KF + RH, RH + FX, FX + CF, and CF + KF), laminate count (2, 4, 6 and 8) infill density (30%, 60%, 90%, and 120%), and raster angle (0/60, 30/120, 50/140, and 70/160). Finding of this work is dimensional accuracy, flexural strength, and shore hardness that are analyzed by L16 orthogonal array. ANOVA statistical analysis is enhanced and enlightens the results of flexural strength and source hardness of the biocomposites. Amongst in four parameters, the fiber type parameter extremely contributes such as 40.50% in the flexural analysis. Similarly, laminate count parameter highly contributes such as 31.01% in the shore hardness analysis.

Variable Neighborhood Strategy Adaptive Search for Optimal Parameters of SSM-ADC 12 Aluminum Friction Stir Welding

In this study, we present a new algorithm for finding the optimal friction stir welding parameters to maximize the tensile strength of a butt joint made of the semisolid material (SSM) ADC 12 aluminum. The welding parameters were rotational speed, welding speed, tool tilt, tool pin profile, and rotational direction. The method presented is a variable neighborhood strategy adaptive search (VaNSAS) approach. The process of finding the optimal friction stir welding parameters comprises five steps: (1) identifying the type and range of friction stir parameters using a literature survey; (2) performing experiments according to (1); (3) constructing a regression model using the response surface method optimizer (RSM optimizer); (4) using VaNSAS to find the optimal parameters for the model obtained from (3); and (5) confirming the results from (4) using the parameter levels obtained from (4) to perform real experiments. The computational results revealed that the tensile strength generated from VaNSAS was 3.67% higher than the tensile strength obtained from the RSM optimizer parameters. The optimal parameters obtained from VaNSAS were a rotation speed of 2200 rpm, a welding speed of 108.34 mm/min, a tool tilt of 1.23 Deg, a tool pin profile of a hexagon, and a rotational direction of clockwise.