Abstract
In this study, we constructed a new algorithm to determine the optimal parameters for friction stir welding including rotational speed, welding speed, axial force, tool pin profile, and tool material. The objective of welding is to maximize the ultimate tensile strength of the welded aluminum. The proposed method combines the response surface method and the modified differential evolution algorithm (RSM-MDE). RSM-MDE is a method that involves both experimental and simulation procedures. It is composed of four steps: (1) finding the number of parameters and their levels that affect the efficiency of the friction stir welding, (2) using RSM to formulate the regression model, (3) using the MDE algorithm to find the optimal parameter of the regression model obtained from (2), and (4) verifying the results obtained from step (3). The optimal parameters generated by the RSM-MDE method were a rotation speed of 1417.68 rpm, a welding speed of 60.21 mm/min, an axial force of 8.44 kN, a hexagon-tapered tool pin profile, and the SKD 11 tool material. The ultimate tensile strength obtained from this set of parameters was 294.84 MPa, which was better than that of the RSM by 1.48%.
Highlights
Aluminum is widely used to produce products in many industries, such as the automotive, shipyard, aviation, and electric train industries, due to its high strength, light weight, high toughness, resistance to breakage, good corrosion resistance, and ability to reduce product damage without decreasing product quality [1]
Algorithm is illustrated in Figure 3, showing its four steps: (1) finding the number of parameters and their levels that affect the efficiency of friction stir welding (FSW), (2) using the response surface method (RSM) to formulate the regression model to predict the suitable parameters of the welding, (3) using the modified differential evolution algorithm (MDE) algorithm to find the optimal parameters of the regression model obtained from step (2), and (4) verifying the results obtained from step (3)
RSM and MDE (RSM-MDE), which was used centralfrom processing unit (CPU), 3.70 GHz random accessproblem memory (RAM)
Summary
Aluminum is widely used to produce products in many industries, such as the automotive, shipyard, aviation, and electric train industries, due to its high strength, light weight, high toughness, resistance to breakage, good corrosion resistance, and ability to reduce product damage without decreasing product quality [1]. Producing large sheets of aluminum can be expensive and sometimes impossible using the current machine technology. Welding methods are often used to join small sheets of aluminum into bigger parts to produce the part needed. Welding is a process in which metals are joined using high heat to melt parts together, and the metal is allowed to cool to normal temperature. Numerous welding methods exist, including gas metal arc welding using metal inert gas or tungsten inert gas, arc welding, gas welding, spot welding [2,3], and friction stir welding (FSW).
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