Prediction of Cutting Force for Milling of Inconel 718 under Cryogenic Condition by Response Surface Methodology

Abstract

In order to identify the influence of different cutting parameters on cutting force under cryogenic cooling assistance, this paper presents an experimental investigation on the influence by high-speed milling Inconel 718 using carbide coated ball nose milling inserts. For Design of Experiment (DOE), Box-Behnken Response Surface Methodology (RSM) with 29 experiments was applied to accommodate 4 factors; cutting speed: 120-140 m/min, feed rate: 0.15-0.25 mm/tooth, axial depth of cut: 0.3-0.7 mm, and radial depth of cut: 0.2-0.6 mm at three levels each. The milling process was performed under a CO2 cryogenic environment using a new design of cryogenic controlling system for consistent and efficient cooling effect at the cutting zone. The experimental results found the forces varied from as low as 112 N up to a maximum of 452 N. The analysis of variance (ANOVA) confirmed the axial depth of cut as the dominant factor influencing the cutting forces followed by the interaction between feed rate and radial depth of cut. The forces were significantly increased with the axial depth of cut due to the increase of the size of cut by the insert. Meanwhile, the developed statistical equation model reported an average error of 4.72% between the predicted and actual cutting forces. With 95.28% of confidence level, this confirms the adequacy of the predictive model to be used within the range of the investigated parameters. Thereby, the numerical optimization suggested parameters of Vc: 140 m/min, fz: 0.25 mm/tooth, ap: 0.3 mm, and ae: 0.21 mm to be applied to achieve a cutting force as low as 117.72 N. The correlation between the cutting forces along with tool wear progress and pattern was also discussed.

Optimization of microencapsulation of polyaspartic acid ester into UV curable epoxy‐acrylate resin using Taguchi method of experimental design

“…Different parameters can be varied in obtaining both characteristics. Usually, such parameters as agitation speed, surfactant type and concentration, reaction time, reaction temperature, and core to shell ratio are chosen as affecting loading and size of microcapsules 28,34–38 …”

Optimization of Machining Parameters in Turning for Different Hardness using Multi-Objective Genetic Algorithm

“…This must be controlled in order to enhance machined product quality, reduce machining costs, and increase production rates [8]. According to Halim et al [9], excessive heat would develop in the cutting zone, raising the cutting temperature. As a result of this circumstance, cutting force and tool wear rates increased rapidly, and the surface quality deteriorated [9].…”

“…According to Halim et al [9], excessive heat would develop in the cutting zone, raising the cutting temperature. As a result of this circumstance, cutting force and tool wear rates increased rapidly, and the surface quality deteriorated [9]. So, the optimization of this process is required to improve the efficiency of the process.…”