Optimization of friction stir welding parameters using multiple response surface methodology

Improving quality in today’s complicated industrial systems is gaining more and more importance every day. Since applying these systems costs a lot, companies should try to offer the best outcomes and processes possible. One of the products most applied is Tailor Welding Blanks, which is widely used in automobile, aerospace, and other industries. One of the best methods of producing Tailor Welding Blanks is Friction Stir Welding. Using this technology, sheets dissimilar in material and thickness can be joined. In this paper, the possibility of welding thin sheets of 5083-H12 and 6061-T6 aluminum alloy by Friction Stir Welding with the thickness of 1.5 mm is examined. To detect the impact of Friction Stir Welding parameters, i.e. rotational speed (r/min), linear speed (mm/ min), shoulder diameter (mm), and tilt angle (°), a Box-Behnken design was used and using multiple Response Surface Methodology values of robust optimization of tensile strength and elongation were derived. The optimization and experiment results were then compared. The results of the comparison showed a good correspondence.

Optimization of Input Variables in Ultrasonic Vibration-Assisted Pelleting of Cellulosic Biomass Using Multiple Response Surface Methodology

Cellulosic ethanol is an attractive alternative to petroleum-based liquid transportation fuels. However, low density of cellulosic biomass (the feedstock for cellulosic ethanol) causes high costs in biomass logistics and hinders large-scale and cost-effective manufacturing of cellulosic ethanol. Ultrasonic vibration-assisted (UV-A) pelleting can significantly increase the density of cellulosic biomass by compressing raw cellulosic biomass into pellets. Pellet density and durability are two important physical properties of a pellet. In this study, a multiple response surface methodology was employed to optimize the input variables (pelleting time, pressure, and ultrasonic power) in UV-A pelleting of sorghum stalks for simultaneously maximized pellet density and durability. Second-order polynomial models were used to fit the experimental results. Main and interaction effects of the input variables on pellet density and durability were also investigated.