Measurement-based modelling of cutting forces in micro-milling of Inconel 718

This paper presents a modeling and simulation of micro-milling process with finite element modeling (FEM) analysis to predict cutting forces. The micro-milling of Inconel 718 is conducted using high-speed steel (HSS) micro-end mill cutter of 1mm diameter. The machining parameters considered for simulation are feed rate, cutting speed and depth of cut which are varied at three levels. The FEM analysis of machining process is divided into three parts, i.e., pre-processer, simulation and post-processor. In pre-processor, the input data are provided for simulation. The machining process is further simulated with the pre-processor data. For data extraction and viewing the simulated results, post-processor is used. A set of experiments are conducted for validation of simulated process. The simulated and experimental results are compared and the results are found to be having a good agreement.

Download Full-text

The flank wear prediction in micro-milling Inconel 718

Industrial Lubrication and Tribology ◽

10.1108/ilt-01-2018-0031 ◽

2018 ◽

Vol 70 (8) ◽

pp. 1374-1380 ◽

Cited By ~ 2

Author(s):

Xiaohong Lu ◽

FuRui Wang ◽

Zhenyuan Jia ◽

Steven Y. Liang

Keyword(s):

Finite Element ◽

Tool Wear ◽

Cutting Forces ◽

Inconel 718 ◽

Flank Wear ◽

Milling Process ◽

Micro Milling ◽

Wear Prediction ◽

Content Type ◽

Micro Tool

Purpose Cutting tool wear is known to affect tool life, surface quality, cutting forces and production time. Micro-milling of difficult-to-cut materials like Inconel 718 leads to significant flank wear on the cutting tool. To ensure the respect of final part specifications and to study cutting forces and tool catastrophic failure, flank wear (VB) has to be controlled. This paper aims to achieve flank wear prediction during micro-milling process, which fills the void of the commercial finite element software. Design/methodology/approach Based on tool geometry structure and DEFORM finite element simulation, flank wear of the micro tool during micro-milling process is obtained. Finally, experiments of micro-milling Inconel 718 validate the accuracy of the proposed method for predicting flank wear of the micro tool during micro-milling Inconel 718. Findings A new prediction method for flank wear of the micro tool during micro-milling Inconel 718 based on the assumption that the wear volume can be assumed as a cone-shaped body is proposed. Compared with the existing experiment techniques for predicting tool wear during micro-milling process, the proposed method is simple to operate and is cost-effective. The existing finite element investigations on micro tool wear prediction mainly focus on micro tool axial wear depth, which affects size accuracy of machined workpiece seriously. Originality/value The research can provide significant knowledge on the usage of finite element method in predicting tool wear condition during micro-milling process. In addition, the method presented in this paper can provide support for studying the effect of tool flank wear on cutting forces during micro-milling process.

Download Full-text

Optimization of machining parameters during micro-milling of Ti6Al4V titanium alloy and Inconel 718 materials using Taguchi method

Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture ◽

10.1177/0954405415572662 ◽

2016 ◽

Vol 231 (2) ◽

pp. 228-242 ◽

Cited By ~ 34

Author(s):

Emel Kuram ◽

Babur Ozcelik

Keyword(s):

Surface Roughness ◽

Titanium Alloy ◽

Tool Wear ◽

Wear Surface ◽

Cutting Forces ◽

Inconel 718 ◽

Regression Models ◽

Micro Milling ◽

Depth Of Cut ◽

Ti6al4v Titanium Alloy

This study focused on the optimization of micro-milling parameters for two extensively used aerospace materials (titanium and nickel-based superalloy). The experiments were planned using Taguchi experimental design method, and the influences of spindle speed, feed rate and depth of cut on machining outputs, namely, tool wear, surface roughness and cutting forces, were determined. Tool wear, surface roughness and cutting forces measured in micro-milling of Ti6Al4V titanium alloy and Inconel 718 workpiece materials were optimized by employing Taguchi’s signal-to-noise ratio. The percentage contribution of micro-milling parameters, namely, spindle speed, feed rate and depth of cut, on tool wear, surface roughness and cutting forces was indicated by analysis of variance. The regression models identifying the relationship between the input variables and the output responses were also fitted using experimental data to predict output responses without conducting the experiments. Efficiency of regression models was determined using correlation coefficients, and the predicted values were compared with experimental results. From results, it was concluded that the established regression models could be employed for predicting tool wear, surface roughness and cutting forces in micro-milling of Ti6Al4V titanium alloy and Inconel 718 workpiece materials.

Download Full-text

Deflection prediction of micro-milling Inconel 718 thin-walled parts

Journal of Materials Processing Technology ◽

10.1016/j.jmatprotec.2020.117003 ◽

2021 ◽

Vol 291 ◽

pp. 117003

Author(s):

Zhenyuan Jia ◽

Xiaohong Lu ◽

Han Gu ◽

Feixiang Ruan ◽

Steven Y. Liang

Keyword(s):

Inconel 718 ◽

Micro Milling ◽

Thin Walled

Download Full-text

Improved dynamic cutting force modelling in micro milling of metal matrix composites part II: Experimental validation and prediction

Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science ◽

10.1177/0954406219893725 ◽

2019 ◽

Vol 234 (8) ◽

pp. 1500-1515

Author(s):

Zhichao Niu ◽

Kai Cheng

Keyword(s):

Cutting Force ◽

Metal Matrix Composites ◽

Cutting Forces ◽

Metal Matrix ◽

Micro Milling ◽

Force Model ◽

Matrix Composites ◽

Cutting Force Model ◽

Side Milling ◽

Dynamic Cutting Force

The effects of cutting dynamics and the particles' size and density cannot be ignored in micro milling of metal matrix composites. This article presents the improved dynamic cutting force modelling for micro milling of metal matrix composites based on the previous analytical model. This comprehensive improved cutting force model, taking the influence of the tool run-out, actual chip thickness and resultant tool tip trajectory into account, is evaluated and validated through well-designed machining trials. A series of side milling experiments using straight flutes polycrystalline diamond end mills are carried out on the metal matrix composite workpiece under various cutting conditions. Subsequently, the measured cutting forces are compensated by a Kalman filter to achieve the accurate cutting forces. These are further compared with the predicted cutting forces to validate the proposed dynamic cutting force model. The experimental results indicate that the predicted and measured cutting forces in micro milling of metal matrix composites are in good agreement.

Download Full-text