## 1 Introduction  
In a conventional welding process, the joining of dissimilar materials, such as different grades of aluminum (Al) and copper (Cu), is considered to be a major challenge. This is due to the variations in the mechanical, chemical, and thermal properties of Al and Cu. However, FSW is one of the most promising solid-state joining processes, which can join the same or different base materials [1]. During this welding process, the generated temperature is below the melting point of the base materials, which helps the base materials to attain an elastic phase and be fused to each other [2]. The formation of a joint without using additional filler materials, alloying elements, and arc, reduces the chances of welding defects that occur in fusion welding. Moreover, during the FSW process, the energy consumption is low and there are no hazards related to radiation and fumes. Thus, the FSW process is superior to all conventional fusion welding processes [3]. A schematic diagram of the FSW process is presented in Figure 1.  
Al and Cu joints are widely used for various applications, such as for electric conductors and the tubes of heat exchangers, a transformer's foil conductor, and so on, due to their extensive properties, such as their high thermal and electrical conductivity, excellent corrosion resistance, and mechanical properties [5]. Therefore, many researchers have investigated the feasibility of using FSW to join Al-alloy and Cu-alloy. These researchers analyzed the dissimilar weld joints of aluminum and cooper and achieved flawless joints and they also observed defect free joints at low weld speeds and with high rotational speeds [6; 7; 8; 9; 10]. Experimental design tools play a key role in the engineering world for improving the manufacturing processes and decreasing variability. The design of experiments (DoE) is an efficient procedure for planning and designing experiments and for analyzing obtained experimental results. Based on the results, a statistical model for the experimental work can be established. This model helps in building a connection between the process variables and outcomes [11]. In some of studies, researchers used several DoE techniques, such as the Taguchi methodology, RSM, factorial design, 'R' programming, etc., to conduct experiments. Researchers have used the Taguchi method and ANOVA for their analyses and they developed mathematical models from the statistical analyses and noted that the weld speed had a more significant effect compared to other process parameters. From ANOVA analysis, they found that the probe offset had a notable effect on YS and UTS [12; 13; 14; 15]. Apart from process variables such as tool rotation speed and weld speed, the position of the welded base plates (advancing side (AS) and retreating side (RS)) and probe offset (tool offset) also play important roles in achieving a sound defect-free joint and weld surface for the friction stir welding of joints of dissimilar materials [16]. Researchers found satisfactory results by maintaining Cu on the AS and soft materials on the RS [7; 17]. Many researchers have investigated the effect of tool offset on the weld quality of the FSW of dissimilar materials. They performed FSW on Al alloy and Cu with varying tool offset of 0-2 mm and found the limiting value of the tool offset to be 1.2 mm on Cu side, beyond which irregular joints were observed [16; 18]. In addition, the tilt angle of a tool plays a significant role in the friction stir welding of dissimilar materials. Many researchers have studied the effect of the tilt angle of a tool on the weld quality of the FSW of various dissimilar materials. They observed that a proper tool tilt angle helps in achieving (i) a defect-free joint and proper fusion of the base material, (ii) a better material flow during the FSW process, and (iii) good plastic deformation at the weld zone.