Influence of laser cutting parameters on the cutting quality of inconel 718 - Mohd Halim, Nurhaliana Shazwani (2022)
The AISI 1045 steel is one of the most researched steel in the machining field due to its versatility. It is commonly used in fabrications of gears, connecting rods, bolts, spindles, rams and core inserts for mould and die. Even though many researchers focus on the turning process, however, this project is covered more wider range of cutting parameters in turning AISI 1045 to fulfil the gap that exists in the currently available literature. Hence, this project focuses on optimizing cutting parameters for material removal rate and surface roughness in dry turning of AISI 1045 carbon steel using the Response Surface Method (RSM). The cutting tool that has been selected was CVD coated carbide insert and AISI 1045 steel with 100 mm length and 25 mm diameter as a workpiece. LEADWELL LTC-20B CNC lathe machine was utilised in this project. The main controllable turning parameters investigated in this project were cutting speed, Vc (100 m/min – 500 m/min), feed rate, f (0.1 mm/rev – 0.5 mm/rev) and depth of cut, ap (0.5 mm – 1.5 mm). In this experiment, a total of 17 experimental runs with 50 mm turning were conducted according to the experimental design layout proposed by Box-Behnken Design. The analysis of variance (ANOVA) was used to determine the most significant effect of the cutting parameters and Box-Behnken Response Surface Method was employed to analyze the interactions between the cutting parameters on the responses, develop mathematical models and predict optimum cutting parameters in turning operation which been validated by the confirmation experiments. From the results, the most influential cutting parameter for material removal rate and surface roughness are depth of cut and feed rate, respectively. Furthermore, the interaction of cutting speed and depth of cut contributes significantly to the material removal rate, where increasing both parameters resulted in increment of material removal rate. Meanwhile, the effects of cutting speed and depth of cut, and cutting speed and feed rate appeared to have significant statistical influences towards the surface roughness. The minimum value of surface roughness is obtained with the combination of the highest cutting speed and the lowest depth of cut. In contrast, the combination of low cutting speed and high feed rate contribute to high surface roughness. Further, response surface optimization for multiple responses shows the optimum cutting parameters that lead to the lowest surface roughness and highest material removal rate are cutting speed of 269.697 m/min, feed rate of 0.1808 mm/rev and depth of cut of 1.50 mm with composite desirability of 0.80 and the predicted value of surface roughness and material removal rate is equal to 1.7888 µm and 4185.64 mm3/min respectively. The confirmation experiments indicate the average error between experimental and predicted values are 3.27% for material removal rate and 9.06% for surface roughness, which shows good agreement with minimum errors. Thus, the developed quadratic response surface models are reasonably accurate for predicting the surface roughness and material removal rate in turning of AISI 1045 steel within the ranges of cutting parameters studied.