High-speed Milling Process Research Articles

Online Vibration Detection in High-Speed Robotic Milling Process Based on Wavelet Energy Entropy of Acoustic Emission

Online Vibration Detection in High-Speed Robotic Milling Process Based on Wavelet Energy Entropy of Acoustic Emission

Surface integrity and modification of SA508Gr.3Cl.2 RPV steel induced by high-speed face milling process

Surface integrity and modification of SA508Gr.3Cl.2 RPV steel induced by high-speed face milling process

Surface morphology, burr formation, and spindle axial drift in high-speed robotic milling of complex features

Industrial robots are garnering increased attention in the manufacturing sector, their application in high-precision tasks such as milling is however hindered by inherent limitations, notably low stiffness and instability. This study aims to investigate the influence of cutting parameters within segmented curve trajectories on surface quality during high-speed robotic milling process. The investigation covers surface morphology, the mechanism of burr formation, and the underlying causes of tool axial runout. The findings reveal that as spindle speed increases and feed speed decreases, the surface topography of the machined workpiece gradually improves and the quantity and dimensions of burrs on both sides of the slot have been decreased. Axial runout occurs during robotic milling due to insufficient robot stiffness, leading to vibrations that cannot effectively resist the reaction forces of cutting forces.

Formation mechanism of surface defect during high-speed ball-end milling process of hardened die steel Cr12MoV

Formation mechanism of surface defect during high-speed ball-end milling process of hardened die steel Cr12MoV

Experimental Study of Surface Roughness of Pine Wood by High-Speed Milling

The surface roughness of wood has a great influence on its performance and is a very important indicator in processing and manufacturing. In this paper, we use the central composite design experiment (CCD experiment) and artificial neural network (ANN) model to study the changing pattern of surface roughness during the high-speed milling process of pine wood. In the CCD experiments, the spindle speed, feed speed, and depth of cut are used as the influencing factors, and the surface roughness is used as the index to analyze the variation law and fit the surface roughness parameter equation. By measuring the chip size in each group in the CCD experiment, the ANN model is used to predict the surface roughness under this machining parameter by measuring the chip size in each test group. The experimental results showed that the mean error of the surface roughness prediction values in the CCD experiment (12.2%) was larger than that of the ANN model (7.8%), and the mean squared error (MSE) of the ANN model was 0.025, the mean absolute percentage error(MAPE) was 0.01, and the coefficient of determination R2 was 0.95. Compared with the CCD experiment, the ANN model had a higher prediction accuracy. The results of this paper can provide some guidance for the prediction of surface roughness during wood processing.

Optimization of High-speed Dry Milling Process Parameters Based on Improved ELM and Genetic Algorithm

High-speed dry grinding has the characteristics of high processing efficiency and clean environment. The high-speed dry grinding method meets the requirements of the green and efficient development of the national manufacturing industry. However, inappropriate cutting parameters seriously affect the surface quality of the workpiece and cause the workpiece to be scrapped. Therefore, this paper proposed an optimization method based on the combination of the improved extreme learning machine neural network (ELM) for high-speed dry milling surface roughness prediction model and genetic algorithm (GA). The Taguchi orthogonal experiment results show that the surface roughness of high-speed dry milling can be accurately predicted by the improved ELM and thereafter the optimal cutting parameter combination can be determined by GA.

Incipient chatter fast and reliable detection method in high-speed milling process based on cumulative strategy

This paper proposes an incipient chatter detection method to meet high dynamic applications’ time and reliability constraints, such as high-speed milling involving heavy noise. The herein introduced method relies on a multiple sampling per revolution (MSPR) technique, coupled with two data preprocessing techniques, a modified adaptive cumulative chatter indicator, and a two-risk levels-based threshold. The MSPR technique enables collecting information-rich enough data to characterize the chatter dynamics thanks to a significant amount of data collected in each revolution. Therefore, the MSPR technique allows for acquiring the data using a short-time window, thus reducing the detection delay. Two data preprocessing techniques, i.e., Z-score normalization and mean-centered, are implemented for data integration and chatter information consolidation. The modified adaptive cumulative chatter indicator has three advantages: (a) it accumulates the information on the chatter feature and highlights the appearance of an incipient chatter; (b) it adapts to the variation of the environmental disturbance noises, resulting in enhanced detection reliability; (c) it is faster than the adaptive cumulative log-likelihood ratio (ACLLR) for decision-making statistically. The two-risk levels-based threshold overcomes the limitations of a unique threshold, and allows simultaneously assessing the two risk levels, thus improving detection reliability. We successfully applied the proposed method to detect incipient chatter in a digital high-speed milling process and assessed its effectiveness by comparing it with several existing chatter detection methods.

Surface Finish Comparison of Dry and Coolant Fluid High-Speed Milling of JIS SDK61 Mould Steel

This paper investigates the influence of dry high-speed milling on the surface quality of JIS SKD61 hard steel, compared to the conventional coolant fluid method. This research was conducted in a Super MC 500 high-speed CNC milling machine with a Hitachi coated carbide 20mm in diameter. High-speed cutting parameters such as cutting speed V, cutting depth t, and spindle speed S were considered as variants. The experiment was designed based on Taguchi's L9. Surface quality, including Ra and Rq, was measured using the Mitutoyo Surftest SV-210. A mathematical regression model was found for the average values of surface roughness through regression analysis for dry and coolant fluid conditions. The chosen high-speed milling parameters and the respective Ra and Rq values were obtained by ANOVA. The grey relation scores for wet and dry milling surface quality for cut depth, feed rate, and cutting speed were 0.7527, 0.7869, 0.6302, and 0.8167, 0.7199, 0.6040, respectively. The results showed that the feed rate had the greatest influence on the surface quality during the high-speed coolant milling of hardened steel, while the depth of the cut had the greatest influence on the surface quality during the high-speed dry milling process.

Optimization of Machining Parameters in High Speed Milling Process of Woven CFRP

Optimization of Machining Parameters in High Speed Milling Process of Woven CFRP

Numerical investigation on serrated chip formation during high-speed milling of Ti-6Al-4V alloy

Due to several inherent properties, Ti-6Al-4V alloy is a kind of typical difficult-to-machine material, especially during high-speed milling processes. The combined action of translation and rotation motion, as well as the short and variable undeformed chip thickness generation, make the milling process different from the turning process. Hence, it is essential to investigate the thermo-mechanical effect on serrated chip formation mechanism during the high-speed milling of Ti-6Al-4V alloy. The present paper investigates numerical methodology (i.e., the combined action of material constitutive with an energy-based ductile failure mechanism) for serrated chip formation in high-speed milling of Ti-6Al-4V alloy. First, a simplified 2D milling model was adopted based on the J-C constitutive equation combined with the energy density-based failure material model. Secondly, the proposed model was corroborated through experimentally obtained results. A good correlation was found between the numerically adopted model and experimentally obtained results. Thirdly, the physical phenomenon of the serrated chip formation and the effect of friction coefficient on shear stress is highlighted and discussed. Finally, the chip back surface's microstructural changes and phase transformation were investigated. The present investigation is beneficial to well understanding the serrated chips formation during high-speed milling of Ti-6Al-4V alloy as well as to optimizing process parameters and maintaining desirable machined surface integrity.

Three-dimensional transient cutting tool temperature field model based on periodic heat transfer for high-speed milling of compacted graphite iron

The new material, compacted graphite iron, plays a key role in the reliability of engine and the realization of high emission standard, but it is a difficult-to-machine material. In high-speed milling process of compacted graphite iron, thermal crack induced by thermal stress is the main reason for tool breakage and chipping. In order to reveal the initiation and propagation mechanisms of thermal cracks, and improve tool life by controlling the formation of thermal crack, it is necessary to study the three-dimensional transient cutting tool temperature field under the condition of periodic heat transfer in intermittent cutting. In this paper, the three-dimensional transient FEM cutting tool temperature field model for high-speed milling of compacted graphite iron was established by using the heat source method. The uneven spatial distribution of the heat flux on the rake face of the tool, and the changes of heat flux density due to the transient cutting thickness and tool-chip contact length over time were considered, and the influence of boundary conditions in the cutting stage and the non-cutting stage were also all taken into account. The heat flux action time and the ratio of cutting time and non-cutting time in the model were set according to the experimental conditions of actual milling process. The established three-dimensional transient cutting tool temperature field model was finally verified by measuring the real temperature in high-speed orthogonal turning experiment. The results showed that the predicted value of the model was consistent with the experimental value, and the predicted error was less than 6.0%, indicating that the model has high accuracy for simulation. This model has great theoretical significance for the development of new tool materials for compacted graphite iron processing, studying the mechanism of thermal crack, controlling and preventing tool failure caused by thermal crack.

EVOLUTION MECHANISM AND CONTROL STRATEGY OF WORKPIECE MACHINING DEFORMATION IN BLANK SLOTTING METHOD

Residual stresses can be generated in aluminum alloy thick plates used widely as the blank of aeronautical thin-walled monolithic components because of the non-homogeneity of plastic deformation induced in the blank manufacturing process. The release of residual stress in high-speed milling process causes the machining deformation of aeronautical thin-walled monolithic component which can severely influence its machining quality. Therefore, the finite element simulation method of milling process is established for the thin-walled workpiece in the deformation-released blank. The finite element simulation values, as well as the calculation values obtained by the deflection analytical method, are verified to be highly agreed with the experimental measurement results in both trend and magnitude. The influence of slotting mode on the blank releasing deformation is revealed by the finite element method so that the relationship between the blank releasing deformation and the workpiece machining deformation is obtained. The result shows that the reduced workpiece machining deformation is the same as the blank releasing deformation. Based on the prediction model of blank releasing deformation, a genetic algorithm optimization method is proposed for the blank slotting mode. The random test set shows that the prediction accuracy of the neural network is about as high as 95% whereas the machining deformation of the three-frame workpiece can be reduced by 34.5% in the optimal slotting mode.

Chatter stability prediction and detection during high-speed robotic milling process based on acoustic emission technique

Chatter stability prediction and detection during high-speed robotic milling process based on acoustic emission technique

A force model of high-speed dry milling CF/PEEK considering fiber distribution characteristics

Carbon fiber reinforced polyetheretherketone (CF/PEEK) is an emerging material that is widely used in the automotive and aviation industry due to its high shock resistance, thermostability, and recyclability. However, its dry-machining requirement with an unclear dynamic material removal process limits the machining efficiency and surface quality. To this end, we firstly established a two-dimensional joint probability distribution model of cutting carbon fibers based on the microstructure of CF/PEEK. Compared with previous brittle models, the plastic model is verified to be more consistent with experimental results. A high-speed dry (HSD) milling force model considering carbon fiber distribution is then developed and is proofed with a high prediction accuracy of about 92.6%. With the proposed model, the milling force can be separated into forces of cutting carbon fibers and PEEK matrix, by which the influences of high-speed dry milling process on carbon fibers and PEEK matrix can be analyzed. The results show that carbon fiber distribution exhibits a significant impact on milling force and is more easily affected by milling parameters compared with the PEEK matrix. It is also verified feasible to HSD milling CF/PEEK, and the work gives the guidance of breaking the low-speed machining limits by improving the machining process.

Determining rotating tool-tip FRFs by measuring holder-point FRFs based on a robust frequency-based substructure method

Obtaining milling tool-tip frequency function responses (FRFs) under rotating conditions is required for accurate milling stability analysis in the high-speed milling process. However, measuring the rotating tool-tip FRFs is challenging because of the sharp and fluted tool-tip geometry. This paper introduces an in-situ measurement strategy that determines the rotating tool-tip FRFs from the holder-point FRFs based on a robust Frequency-based Substructure (FBS) method. According to the classical FBS in beam-like structures, tool-tip FRFs could be directly calculated from another point FRFs on the same assembly. After theoretically establishing the substructure between the tip and tested points, the tool-tip FRFs could be analytically calculated from the tested point FRFs. One outstanding advantage is that the calculation avoids inverting the experimentally measured receptance matrix, thereby improving robustness against measurement noises in rotating structures. Generally, the cylindrical tool holder has enough smooth regions, so the holder point is well-suited for measurement. Under this circumstance, the substructure contains the complex coupling of the holder, tool and holder-tool connection sections. Here, a parametric substructure model, which is computationally efficient for model updating, is introduced. Uncertain model parameters are determined by minimizing the difference between the model-calculated and experiment-measured outputs under static conditions. The proposed measurement methodology is validated in simulations and practical cases. Both results show that the proposed method could obtain rotating tool-tip FRFs with high accuracy.

Surface roughness and chip morphology of wood-plastic composites manufactured via high-speed milling

Wood-plastic composites have attracted extensive attention throughout the world because of their advantages. However, the manufacturing mechanism of the wood-plastic composites, i.e., high-speed milling technology, is not perfect and needs further study. The effects of the cutting parameters, i.e., the spindle speed, feed rate, axial milling depth, and radial milling depth, on the surface roughness and chip morphology were studied; the surface roughness values, Ra and Rz of high-speed milling wood-plastic composites samples were measured via high precision surface roughness measuring instrument, and their regression equations were calculated. The chips produced via a high-speed milling process were collected and studied. The results showed that the surface roughness of the wood-plastic composites increases with an increase in the axial depth, feed rate, or radial depth, but decreases with an increase in the spindle speed. In addition, the axial milling depth, feed rate, and spindle speed had a significant effect on the morphology of the chips. However, the effect of the radial milling depth on the morphology of the chips was not obvious. The results can provide a scientific basis for the optimization of high-speed milling processing of wood-plastic composites.

Analysis of tool wear and surface roughness in high-speed milling process of aluminum alloy Al6061

In this study, the influence of cutting parameters and machining time on the tool wear and surface roughness was investigated in high-speed milling process of Al6061 using face carbide inserts. Taguchi experimental matrix (L9) was chosen to design and conduct the experimental research with three input parameters (feed rate, cutting speed, and axial depth of cut). Tool wear (VB) and surface roughness (Ra) after different machining strokes (after 10, 30, and 50 machining strokes) were selected as the output parameters. In almost cases of high-speed face milling process, the most significant factor that influenced on the tool wear was cutting speed (84.94 % after 10 machining strokes, 52.13 % after 30 machining strokes, and 68.58 % after 50 machining strokes), and the most significant factors that influenced on the surface roughness were depth of cut and feed rate (70.54 % after 10 machining strokes, 43.28 % after 30 machining strokes, and 30.97 % after 50 machining strokes for depth of cut. And 22.01 % after 10 machining strokes, 44.39 % after 30 machining strokes, and 66.58 % after 50 machining strokes for feed rate). Linear regression was the most suitable regression of VB and Ra with the determination coefficients (R2) from 88.00 % to 91.99 % for VB, and from 90.24 % to 96.84 % for Ra. These regression models were successfully verified by comparison between predicted and measured results of VB and Ra. Besides, the relationship of VB, Ra, and different machining strokes was also investigated and evaluated. Tool wear, surface roughness models, and their relationship that were found in this study can be used to improve the surface quality and reduce the tool wear in the high-speed face milling of aluminum alloy Al6061

Optimization of Milling Aluminum Alloy 6061-T6 using Modified Johnson-Cook Model

Finite element (FE) simulation is an efficient and time-saving method to optimize the high-speed machining process of aluminum (Al) alloy. The constitutive model accurately described the dynamic mechanical behavior of materials at cutting conditions is the premise of obtaining high-precision simulation results. In this study, the flow stress-strain relationship of AA 6061-T6 is obtained at a high temperature (up to 400 °C) and a high strain rate (up to 1 × 104 s−1). Temperature-dependent Johnson-Cook (J-C) model is proposed by considering dynamic recrystallization effect. By the modified J-C model, a two-dimensional simplified FE model is established to optimize the high-speed milling process of AA 6061-T6 hard drive head (HDH) access arm. The results show that the modified J-C constitutive model has a good prediction accuracy, and the predicted cutting forces are in good agreement with the experimental results. By the finite element simulations, the influences of both cutting parameters and tool geometric parameters on cutting force, chip morphology, cutting temperature, effective stress and effective strain are analyzed during cutting processes of AA 6061-T6. Optimized range of cutting parameters and tool geometric parameters are obtained, which provides a theoretical guidance for the optimization of the cutting processes of Al alloy precision parts.

Effect of High Speed Milling Cutting Parameters to Mould Steel DF2 Surface Roughness Employing Carbide End Mill

The aim of this research is to analyze the effect of high speed milling cutting parameters on to the Mould Steel DF2 surface finish. Deckel Maho Evolution 50 High Speed Milling with pair controlled parameters (spindle speed and feed rate) is employed. Then, the Mould Steel DF2 was tested in order to explore the relationship between the controlled parameters. Within aided from application of Minitab was used to design and analyze the results. As a result, from the ANOVA table it been able to conclude that factor of spindle speed and feed rate does give significant value to the surface roughness (Ra). Its mean this to factor gives the influence of surface. The optimal machining conditions occur at the when the spindle speed is at 16000 rpm and feed rate 200 mm/min. Result of the study can be used by industries as a guide to choose best parameter for the High Speed Milling process.

MICRONIZED CONCRETE POWDER AS MIRCOFILLER IN CEMENT PASTE: INFLUENCE ON HYDRATION AND STRUCTURE

The reuse of old concrete as a coarse and fine recycled aggregate in cement composites is relatively well researched, and therefore a very fine fraction of recycled concrete was used in this paper. When using a very fine fraction of recycled concrete, it is appropriate to focus primarily on less technologically demanding treatment processes with minimal costs and environmental impact. Therefore this paper focus on using the fine fraction of recycled concrete as a microfiller. For this purpose, the material is treated by high-speed milling process and micronized concrete powder (MCP) is produced. Using several micronized concrete powder types that differ by origin, separation process and fineness of grinding should help understand how MCP influences the hydration process and cement paste structure. The samples with 0, 10, 20, 30, 40 and 50 wt. % of MCP were made to determine proper dosage in cement paste. Specific surface, matrix density and DTG analysis of micronized concrete powder were carried out. The calorimetric measurement was used to confirm how microfiller affects the hydration process. Finally, bulk density and porosity measurements were performed to determine the effect of MCP and its amount on the cement paste structure.