Experimental Investigation of Machining Time and Optimization of Machining Parameters Using RSM and Genetic Algorithm (GA) on 2205-Duplex Stainless Steel

Abstract

Duplex stainless steel has become one of the fastest-growing materials in the stainless steel family due to pitting resistance, stress-corrosion cracking, the combination of excellent mechanical properties, production features, and the area of applications such as oil and gas, nuclear and thermal power plants, chemical processing industries, saltwater processing industries, and pipeline systems. However, it is more difficult to machine due to its high toughness, low thermal conductivity, and ductility. The experiment has conducted using 2205- Duplex Stainless steel round bar material considering carbide cutting tools using Computer Numerical Control lathe to estimate machining time to address and meet the industrial need. Using Central Composite Designed by using Response Surface Methodology technique develops a second-order mathematical model based on the machining parameters. The Analysis of Variance technique was used to investigate the material's performance characteristics, and the impact of cutting parameters on the work piece was analyzed using the Design Expert-V12 software. Cutting speed is the most crucial determining factor compared to other factors. The Genetic Algorithm is trained and tested in MATLAB to evaluate the best possible solutions. The genetic Algorithm recommends the most outstanding lowest predicted value of 1.2204 mm. The confirmatory analysis shows the experimental values, and their error percentage is within ±2%; these shows indicated predicted values are very close to the Genetic Algorithm results. The conclusions were in good agreement with the experimental machining time values.