Likun Si

Model of the instantaneous undeformed chip thickness in micro-milling based on tooth trajectory:

Instantaneous undeformed chip thickness is one of the key parameters in modeling of micro-milling process. Most of the existing instantaneous undeformed chip thickness models in meso-scale cutting process are based on the trochoidal trajectory of the cutting edge, which neglect the influences of cutter installation errors, cutter-holder manufacturing errors, radial runout of the spindle and so forth on the instantaneous undeformed chip thickness. This article investigates the tooth trajectory in micro-milling process. A prediction model of radial runout of cutting edge is built, with consideration of the effects of the extended length of micro-milling cutter and the spindle speed. Considering the effects of cutting-edge trochoidal trajectory, radial runout of cutting edge and the minimum cutting thickness, a novel instantaneous undeformed chip thickness model is proposed, and the phenomenon of single-tooth cutting in micro-milling process is analyzed. Comparisons of cutting forces under different chip thickness models and experimental data indicate that this new model can be used to predict cutting forces.

Research on the prediction model of micro-milling surface roughness of Inconel718 based on SVM

Purpose – The purpose of this paper is to establish a roughness prediction model of micro-milling Inconel718 with high precision. Design/methodology/approach – A prediction model of micro-milling surface roughness of Inconel718 is established by SVM (support vector machine) in this paper. Three cutting parameters are involved in the model (spindle speed, cutting depth and feed speed). Experiments are carried out to verify the accuracy of the model. Findings – The results show that the built SVM prediction model has high prediction accuracy and can predict the surface roughness value and variation law of micro-milling Inconel718. Practical implication – Inconel718 with high strength and high hardness under high temperature is the suitable material for manufacturing micro parts which need a high strength at high temperature. Surface roughness is an important performance indication for micro-milling processing. Establishing a roughness prediction model with high precision is helpful to select the cutting par...

Tool wear appearance and failure mechanism of coated carbide tools in micro-milling of Inconel 718 super alloy

Purpose – The paper aims to study the wear and breakage characteristics of coated carbide cutting tools through micro-milling slot experiments on superalloy Inconel 718. Design/methodology/approach – During the micro-milling process, the wear and breakage appearance on the rake face and flank face of the cutting tools, as well as the failure mechanism, have been studied. Furthermore, the wear and breakage characteristics of the micro-cutting tools have been compared with the traditional milling on Inconel 718. Findings – The main failure forms of the micro tool when micro-milling Inconel 718 were tool tip breakage and coating shed on the rake and flank faces of the cutting tool and micro-crack blade. The main causes of tool wear were synthetic action of adhesive abrasion, diffusion wear and oxidation wear, while the causes of abrasive wear were not obvious. Practical implications – The changing trend in tool wear during the micro-milling process and the main reasons of the tool wear are studied. The findi...

Research on surface residual stress of micro-milling nickel-based superalloy Inconel 718

Nowadays, there are urgent demands of micro structure/parts which have high strength in high temperature environment in the fields such as aerospace, energy, power, bio-medical, etc. Nickel-based superalloy Inconel 718 is the suitable material for manufacturing the kind of micro parts. Micro-milling can be applied to manufacture Inconel 718 micro components. Different processing conditions lead to different residual stress on workpiece surface, which has a significant effect on reliability and working life of product. To study the residual stress problem in micro-milling of Inconel 718, the investigation of micro-milling Inconel 718 process was implemented based on ABAQUS simulation. The model based on the input of cutting parameters and the output of surface residual stress was developed. At last, the experiments of micro-milling Inconel 718 were conducted to verify the validity of model. The work offers reference for selecting cutting parameters in micro-milling of Inconel 718.

Surface roughness prediction model of micro-milling Inconel 718 with consideration of tool wear

During micro-milling Inconel 718, relationship between surface roughness and cutting parameters is studied. Taking the spindle speed, feed per tooth, axial depth of cut and cutting time into consideration, a prediction model, based on the orthogonal test, has been established to predict the surface roughness of nickel-base superalloy Inconel 718 by micro-milling. Neural network method is used to build surface roughness prediction model. As the cutting time changes, the surface roughness value of Inconel 718 under different cutting parameters changes, and the variation trend is able to provide reference for changing tools in time to ensure the surface quality of parts. The research on nickel-base superalloy micro milling, which could help us figure out the change regulation between micro groove surface roughness along with the cutting parameters and machining time, provides significant guidance for deep research on surface quality of micro-milling nickel-base superalloy Inconel 718 machining mechanism.

Influence of spindle speed on tool wear in high-speed milling of Inconel 718 curved surface parts:

High-speed milling, which provides an efficient approach for high-quality machining, is widely adopted for machining difficult-to-machine materials such as Inconel 718. For high-speed milling of Inconel 718 curved surface parts, the spindle speed which determines cutting speed directly is regarded as an important cutting parameter related to tool wear and machining efficiency. Meanwhile, because of the changing geometric features of curved surface, cutting force is changing all the time with the variation of geometric features, which influences not only tool wear but also machining quality significantly. In this study, the influence of spindle speed on coated tool wear in high-speed milling of Inconel 718 curved surface parts is studied through a series of experiments on considering tool life, cutting force, cutting force fluctuation, and machining efficiency. According to the experimental results, the appropriate spindle speed that can balance both the tool life and the machining efficiency is selected as 10,000 r/min for high-speed milling of Inconel 718 curved surface parts. In addition, the coated tool wear mechanism is investigated through scanning electron microscopy–energy dispersive x-ray spectroscopy analysis. The results show that at the beginning wear stage and the stable wear stage, the coated tool wear is mainly caused by mechanical wear. Then, with the increasing cutting temperature due to the blunt tool edge, the tool wear becomes compound wear which contains more than one wear form so as to cause a severe tool wear.

Modelling and optimisation of cutting parameters on surface roughness in micro-milling Inconel 718 using response surface methodology and genetic algorithm

In recent years, micro-milling techniques have attracted great attention and interest from academia and industry. Inconel 718 is a nickel-based superalloy with good tensile, fatigue, creep and rupture strength and can find great application in nuclear and aerospace industry. In this paper, the response surface methodology (RSM) was applied to develop the model for predicting surface roughness in micro-milling Inconel 718. The magnitudes of cutting parameters affecting the surface roughness, which were depth of cut, spindle speed, and feed rate, were analysed by the analysis of variance (ANOVA). The validity of the surface roughness prediction model was proved due to the tiny error between the measured values and the prediction results. Then, genetic algorithm (GA) was used to determine the optimal cutting parameters achieving minimum surface roughness in micro-milling Inconel 718 process. All experiments show that the optimised results agree well with the test ones.

Machining error reduction by combining of feed-speed optimization and toolpath modification in high-speed machining for parts with rapidly varied geometric features

Parts with rapidly varied geometric features are usually crucial parts in high-end equipment and widely applied in the fields of aerospace, energy and power, which are difficult or inefficient to process because of the more special structure and the higher requirement of machining precision. High-speed machining technology provides an effective method for parts with rapidly varied geometric features to solve the contradiction between high demand and low machining efficiency. However, as the existence of rapidly varied geometric features, the machining toolpath for such parts is always complex free-form curve and the actual moving speed of the workbench of the NC machine tool cannot reach the feed-speed set in the NC program timely due to the drive constraint of NC machine tool. Furthermore, the machine tool would vibrate violently when machining the rapidly varied geometric features. In this way, the big machining error will be formed. A machining error reduction method by combining of feed-speed optimization and toolpath modification in high-speed machining for such parts is proposed. First, considering that the actual feed-speed cannot reach the programmed value when the toolpath curvature is too large, the feed-speed is optimized with the constraints of jerk and acceleration limitations of the feed shafts, and a feed-rate smoothing algorithm is applied. Then, the compensated cutter locations are calculated via machining-error estimation. Finally, the modified NC codes are acquired according to the optimized feed-speed and the compensated toolpath. By combining the feed-speed optimization and toolpath modification, the high precision and high efficiency machining can be realized. The experimental results demonstrate the feasibility of the proposed approach. This study provides an effective approach to reduce the machining error in high-speed machining, and is significant for improving the processing precision and efficiency of parts with rapidly varied geometric features.

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

Due to its superior properties, nickel-based superalloy Inconel 718 can meet the requirements of micro parts with the high strength at high temperatures which have three-dimensional geometry structure like stepped surface, deep-hole, thin wall and so on. However, Inconel 718 is difficult to cut. Now, there are few researches on the cutting forces in micro-milling of Inconel 718, and the micro-milling mechanism of nickel-based superalloy is almost blank, while the prediction and control of micro-milling forces is important to reveal the micro-milling mechanism of nickel-based superalloy, to realise processing parameter optimisation, to reduce the tool wear, etc... To predict the cutting forces during micro-milling Inconel 718 process, coated carbide tools are used to micro-milling micro groove on Inconel 718, and the orthogonal type experiments are adopted. The influences of cutting parameters on cutting forces are studied. The micro-milling forces prediction model is built based on the experimental results, which can be used to predict the cutting forces during micro-milling of Inconel 718 nickel-based superalloy. To prove the validity of the built model, the significance test and fitting degree test are conducted.

A surface roughness prediction model using response surface methodology in micro-milling Inconel 718

In this paper, a surface roughness prediction model of micro-milling Inconel 718 by applying response surface methodology (RSM) is presented. The experiments based on centre composite rotatable design (CCRD) are designed to conduct the experiments. The cutting parameters considered are depth of cut, spindle speed and feed rate. Statistical methods, analysis of variance (ANOVA), are used to analyse the adequacy of the predictive model. The influence of each micro-milling parameter on surface roughness is analysed; also the magnitude order of parameters is determined. Depth of cut is found to be the critical influence factor. At last, the parameters interaction on surface roughness of micro-milling Inconel 718 is discussed by graphical means through MATLAB.