Effect Of Tool Wear Research Articles

Effect of chip thickness and tool wear on surface roughness and cutting power during up-milling wood of different density

The aim of this study was to determine the effect of average chip thickness and blade wear on the cutting power consumption and surface quality obtained in up-milling wood of different densities. The surface roughness was investigated using the contact method, recording the roughness parameters Ra and Rz, and the cutting power was determined using a wattmeter. The research was conducted for two variants of blade wear, i.e., sharp and blunt, and three variants of chip thickness (0.10, 0.06, and 0.02 mm). Four wood species with very different densities were tested, i.e., balsa (Ochroma pyramidale (Cav. ex Lam.) Urb.), obeche (Triplochiton scleroxylon K. Schum.), alder (Alnus glutinosa L. Gaertn.) and beech (Fagus sylvatica L.) For the lowest density woods, a better surface quality was found when cutting with a blunt knife compared to a sharp knife, while for the higher density woods (alder and beech) an inverse relationship was observed, i.e., a blunt knife resulted in increased surface roughness. For obeche wood, the surface roughness was dependent on the chip thickness. In addition, for low-density woods (balsa and obeche), no differences in cutting power were shown as a function of blade condition. It was shown that both an increase in wood density and chip thickness resulted in an increase in cutting power.

FSW of AA2024: effects of tool wear on energy consumption

ABSTRACT This study shows that the progressive adhesion of weld material to the tool in friction stir welding AA 2024-T3, up to tool saturation, brings about a decrease in power consumption until a plateau is reached. The cause of this behavior is the hindering of the stirring action of the tool due to the material accumulated on it. The built-up material changes the nature of the tool/material interaction and then the friction condition at their interface. The direct consequence is a decrease in the shearing strain and therefore in the heat generated by friction. Bits of this adhering material break off from the tool at intervals. Macro and micro detachments are identified. Micro-detachments happen continuously at small periodic intervals and produce vibrations. The amplitude of these vibrations increases in all their characteristic spectral components up to tool saturation. Macro-detachments generate oscillations in power consumption and leave galling on the weld bead.

Modelling the influence of tool wear on shape errors in milling using a hybrid soft-sensor

AbstractThe wear of cutting tools during milling processes not only constrains the volume of material that can be removed by a tool but also results in a progressive deterioration of the quality of the workpiece. Although there are established methodologies for predicting tool wear, there is a paucity of knowledge regarding the impact of tool wear on shape error. The authors present a data-driven soft sensor to model the effect of tool wear on shape error, obviating the need for direct tool wear measurement. To evaluate this approach, a milling experiment was conducted, wherein process forces, spindle current, and resulting shape error were measured. Furthermore, a geometrical cutting simulation was conducted in order to obtain cutting conditions, including the volume of material removed. This study examines the contribution of these features to the prediction performance of the proposed soft sensor. Additionally, the transferability from models trained on different tools is investigated to ascertain the impact of tool wear variance on prediction performance. Prediction experiments demonstrate that a soft-sensor based on a combination of simulation and process monitoring data enables a model trained on data from multiple milling tools to account for wear and predict shape error well under varying wear scenarios. The approach presented here has been demonstrated to result in a reduction of the prediction error of up to 60% compared to an average baseline prediction.

Tool wear induced multimode vibration and multiscale patterns in precision turning NAK80

Cubic boron nitride (CBN), with a hardness second only to diamond and an excellent chemical stability, is used to replace the role of diamond and machine precision/ultra-precision components in ferrous materials. However, the wear mechanisms of CBN tools and their wear-induced effects on machining system vibration seriously affect the machined surface quality. Therefore, this research focus on the wear characteristics of CBN tools in machining of NAK80. Based on the wear characteristics, the change in surface morphology and finish of the machined surface with tool wear was investigated. Meanwhile, the transformation of chip morphology at different wear stages was observed. Also, the effect of tool wear on the machining system vibration is analyzed by Butterworth filtering and Fourier transforming the cutting force signal. Research results show that the wear mechanisms of CBN cutting NAK80 are abrasive wear, oxidative wear and diffusive wear. Further, when the width of the flank wear of the CBN tool reaches 53 μm it causes multimodal vibration of the machining system, resulting in chattering patterns on the machined surface. As the width of the flank wear increased from 56.64 μm to 70.80 μm, the vibration frequency increased by 13.3 %. However, by reducing the feed rate from 5 μm/rev to 2 μm/rev, the vibration frequency can be reduced by 66.8 %. This study provides theoretical help in the research of wear of CBN cutting NAK80.

Enhancing surface quality and tool life in SLM-machined components with Dual-MQL approach

Selective laser melting (SLM) can produce complex metal components with high densities, thereby surpassing the limitations of traditional machining methods. However, achieving accurate dimensions, geometries, and acceptable surface states in parts fabricated through SLM remains a concern as they often fall short compared to traditionally machined components. As a solution, a hybrid additive-subtractive manufacturing (HASM) method was developed to effectively utilize the advantages of both techniques. In this study, SLM-made 316 L stainless steel was machined under distinct cooling conditions to investigate the effects of roughness and tool wear. After a thorough investigation, the dual-MQL strategy was evaluated and compared with dry and MQL cutting strategies. The findings showed that the dual-MQL condition led to a significant reduction in flank wear by 54–56% and 29–34%, respectively, associated with dry and MQL cutting techniques, making it a highly promising key for machining SLM-made steel components. Machine learning techniques are potential tools for prediction and classification capabilities in machining processes. For milling SLM-made 316 L SS, multilayer perceptron (MLP) proved to be the most effective prediction model and for classification MLP and Random forest performed better.

Cylinder accuracy analysis of tangential turning of disk-like workpieces with increased cutting speed

Tangential turning, a precision high-speed finishing procedure, is crucial for achieving superior surface quality and dimensional accuracy in cylindrical workpieces. This advanced machining technique leverages tangentially applied cutting forces to minimize tool deflection and vibration, thereby enhancing the surface integrity of the final product. Despite its advantages, tangential turning poses challenges in maintaining cylindrical accuracy, necessitating a thorough investigation of cylindrical error. Cylindrical error, the deviation of the machined surface from a perfect cylinder, significantly impacts the functional performance of precision components. Factors such as tool wear, machine dynamics, and thermal effects can induce these errors, demanding comprehensive studies to optimize process parameters and tool paths. By thoroughly analyzing cylindrical error, manufacturers can refine tangential turning processes, ensuring high precision and consistency in high-speed finishing operations. This research underscores the importance of precision error analysis in advancing manufacturing capabilities and achieving stringent quality standards. Cylindrical accuracy is analyzed using the full factorial experimental design methodology to carry out practical cutting experiments, where the cutting speed, feed, and depth of cut were the altered variables. The cylindricity error, peak maximum departure, their ratio, and coaxiality are measured and analyzed. The main effect analysis and detailed study are elaborated using the determined equation. It is found that decreasing the studied parameters is advisable if increasing cylinder accuracy is needed.

FEM and experimental analysis to study the effect of tool wear on the surface integrity of finish hard turned EN31 steel

FEM and experimental analysis to study the effect of tool wear on the surface integrity of finish hard turned EN31 steel

Modelling cutting force for turning AISI 304 stainless steel with PVD-AlTiN coated, PVD-AlTiN coated-microblasted, and MTCVD-TiCN/Al2O3 coated tools

ABSTRACT Stainless steel is challenging to machine, and to avoid any negative consequences, it is essential to comprehend the cutting forces. With this view, this study has developed a cutting force model for turning AISI 304 stainless steel with the most preferred PVD-AlTiN coated (C-type), PVD-AlTiN coated-microblasted (CMB), and MTCVD-TiCN/Al2O3 coated carbide tools (MTCVD). Empirical models are developed to predict the chip thickness ratio, the normal shear angle, and sharp tool cutting forces. Studies showed the reduction in forces with the cutting speed for C-type, CMB, and MTCVD tools was 12–20%, 11–32%, and 6–29%, respectively. However, the corresponding increases with the feed and depth of cut were 60–134%, 125–146%, and 97–178%; 76–186%, 55–384%, and 14–274%, respectively. Additionally, a cutting force model considering the tool wear effect is developed for MTCVD tools, which exhibited lower tool wear compared to other tools. The study accurately predicted sharp tool and worn tool cutting forces, showing good quantitative agreement with experimental results with an average error of less than 10%. However, some discrepancies were observed beyond the flank wear length of 0.2 mm. It was due to the chipping of the coating layers and the pitting of the substrate from the nose area.

Micro-machining of glassy polymers: effect of tool wear and process parameters on the cutting-induced shape defects

Micro-machining of glassy polymers: effect of tool wear and process parameters on the cutting-induced shape defects

Determination and prediction of surface and kerf properties in abrasive water jet machining of Fe-Cr-C based hardfacing wear plates

Improving and maintaining the sustainability, profitability and efficiency of sectors such as manufacturing, mining and agriculture are the most important goals for industries. It is therefore quite common to apply hardfacing method to products and equipment created to achieve these goals. However, machining of the workpiece is necessary to ensure dimensional accuracy as a result of hardfacing production. In the processing of hardfacing materials with traditional machining methods, negative factors such as tool wear and thermal effects occur. For this reason, the cutting performance of hardfacing wear plate with abrasive water jet, which is one of the unconventional manufacturing processes, was investigated in this study. Tests were realized in regard to the full factorial experimental design, which includes the changes in the levels of material alignment direction, abrasive mass flow rate and traverse speed parameters. The influences of the test parameters on the surface roughness and kerf taper angle constituting the cutting performance were determined by analysis of variance (ANOVA). In addition, the effects of changes in parameter levels were investigated. Material alignment direction was found to be the most effective test parameter for surface roughness and kerf taper angle. The influences of parameter and parameter levels on the formation of surface conditions were determined with surface images. Thus, machining mechanisms and surface morphologies were explained by scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS). Optimal levels of test parameters were achieved by performing multiple-response optimization with equal importance. Finally, the estimated results of cutting performances were found by general linear model, and all results were confirmed by regression analysis.

Multi-objective optimization of machining parameters in complete peripheral milling process with variable curvature workpieces

The mechanism of peripheral milling with variable curvature has yet to be revealed. There is an urgent need to develop a composite optimization approach for the full milling process, including rough and fine machining. The influence of curvature on the energy consumption mechanism in peripheral milling is investigated in this paper. Firstly, the geometric parameters of peripheral milling are analyzed, and the material removal rate calculation method with variable curvature is proposed. The effects of workpiece curvature, machining parameters, and tool wear on energy consumption and surface quality are revealed. Secondly, prediction models for machine tool specific energy and surface roughness are developed in accordance with the examined material removal mechanism. Then, the carbon emission calculation method for the complete peripheral milling process is put forward based on the developed energy consumption mechanism. Finally, a genetic algorithm with elite strategy is used to optimize the multi-dimensional and multi-objective machining parameters. The objective is to achieve the maximum machining efficiency, minimize carbon emissions, and attain excellent surface quality during the complete milling process. The research aims to concurrently optimize machining parameters for rough and fine machining processes, thereby enabling effective and environmentally friendly peripheral milling while maintaining machining quality. The determination coefficient R2 for the proposed model exceeds 0.97, while the average accuracy of predictions surpasses 96 %. The research holds particular importance in providing guidance for peripheral milling operations involving workpieces with variable curvature.

Analysis of high temperature and mixed tool wear effects on UD-CFRP cutting mechanism in stacks drilling

Analysis of high temperature and mixed tool wear effects on UD-CFRP cutting mechanism in stacks drilling

Laser-assisted surface grinding of innovative superhard SiC-bonded diamond (DSiC) materials

Silicon carbide (SiC)-bonded diamond materials, comprising approximately 50% diamond by volume, represent innovative composites with exceptional mechanical and thermal properties, including high hardness, wear and corrosion resistance, and elevated thermal conductivity. Despite these advantageous properties, the machining of these composites presents formidable challenges due to their extremely high hardness. Grinding with diamond tools is commonly employed among the limited viable machining methods. However, the efficiency of this process is hindered by high grinding forces, elevated temperatures, and significantly high tool wear. Additionally, the surface integrity, form, and dimensional accuracy of the workpiece are compromised by the effects of tool wear and high cutting forces. To address these technological constraints in the grinding of SiC-bonded diamond materials, a laser-assisted grinding process has been developed. Ultra-short pulsed laser radiations were effectively utilized to induce material ablation with controlled structural damages, enhancing the productivity and efficiency of the grinding process through reduced grinding forces, temperatures, and tool wear. Furthermore, this study investigated the influence of grinding tools' specifications, design variations, and parameters on key aspects such as grinding forces, surface quality, and tool wear. Substantial reductions of up to 70% in tangential grinding forces, 83% in normal grinding forces, and a modest improvement in surface roughness achieved. The surface integrity analysis revealed a damage-free ground surface when utilizing laser assistance. Furthermore, there was a substantial enhancement in the grinding ratio (G-ratio), achieving an increase of up to 247%, concurrently with a noteworthy improvement in the actual removal depth, reaching up to 99%, when compared to conventional grinding processes. Compared to the utilized segmented metal bonded diamond grinding wheel, the vitrified bonded diamond grinding wheel induced lower grinding forces and higher actual removal rates.

Temperature prediction model of bone drilling considering the effect of tool wear

Biomass bone is biologically active and sensitive to heat; excessive temperatures would destroy the biological activity of the bone tissue or even cause bone necrosis. Therefore, it is vital to control the drilling temperature in clinical surgery for internal fixation of fractures. This paper focused on the influence of tool wear on the drilling temperature during the bone drilling process. The effect of three drilling parameters, the tool diameter, machine spindle speed and tool feed speed, on three dynamic characteristics, the drilling force, drilling temperature and tool wear, was investigated through bone drilling experiments. A prediction model of the bone drilling temperature considering the effect of the amount of wear was established based on Archard wear theory and the heat source method, and was in good agreement with the experimental results. The predicted results showed that worn bits produced drilling temperatures up to 3.4°C higher than those of new bits, and the maximum error in the prediction of the drilling temperature was 11.04%. The temperature model better extended the applicability of the existing temperature models.

Effect of PCD tool wear on surface morphology and material removal mechanisms in the micro-drilling of Cf/SiC composites: Experiment and simulation

This study investigates the polycrystalline diamond (PCD) tool's wear mechanism and the effect of tool wear on hole morphology in the micro-drilling of Cf/SiC composites. A 2D woven material model and tool wear model are created for the drilling simulation. The findings indicate that the wear mechanisms of the tools are mainly abrasive and adhesive. As the tool is worn, the quality of the hole entrance/exit and the shape accuracy deteriorate, and the surface roughness of the hole wall increases. Furthermore, a blunt cutting-edge radius shifts material removal from a shear effect to a compressive effect, transitioning from micro-brittle to macro-brittle removal. Notably, the simulation results approximately agree with the experimental results.

Effect of tool wear and variable friction coefficient on cutting force

Effect of tool wear and variable friction coefficient on cutting force

Effect of tool wear on machining quality in milling Cf/SiC composites with PCD tool

Carbon fiber reinforced silicon carbide ceramic matrix (Cf/SiC) composites have great application potential in aerospace. But their high hardness and anisotropy cause rapid tool wear during machining, which affects machining quality and efficiency. However, tool wear mechanisms in milling Cf/SiC composites are still unclear. There is a lack of research on the relationship between tool wear and cutting performance. In this paper, milling experiments on 2.5D Cf/SiC composites were conducted using polycrystalline diamond (PCD) cutters. The tool wear mechanisms and effect of tool wear on surface roughness, milling force, burr damage, surface microstructure and chips were explored. The results show that abrasive wear caused by chips continuously scraping tool material and diamond particle fragmentation and falling off caused by sprouting and expansion of cracks inside grain were primary causes of tool failure. The formation mechanism of burr damage was analyzed. It was proved that the peak radius of cutting edge Rpeak and flank wear VB could reflect cutting capabilities. It was found that increasing flank wear had regrinding effects on the cutting edge, which affects the peak radius. The degree of burr damage was related to these two parameters. Tool wear changed the surface formation mechanism. Before tool wear, carbon fibers were primarily removed through the micro-brittle fracture, with low surface roughness. The flank face and chips scratched the workpiece like abrasive grains after tool wear, leaving scratches on the surface and increasing surface roughness from 1.27 μm to 2.25 μm.

Performance assessment of different cooling conditions in the sustainable machining of Hastelloy X alloy

The primary goal of this study is to explore techniques that can enhance the machinability of Hastelloy X under different cooling conditions. L27 orthogonal turning experiments were performed with process parameters such as cutting speed ( vc), feed rate ( f) and depth of cut ( ap) to study the effect of tool wear and machining cost. The control parameters of a procedure were evaluated through a multiple linear regression model (MLRM) derived from the correlation between the output responses and the input parameters. A multi-verse optimisation algorithm (MVO) was proposed for optimisation studies. It achieves this by minimising the tool wear and machining cost. The proposed algorithm was evaluated against the techniques used for particle swarm and salp swarm optimisations. According to the study, the MVO algorithm outperformed other methods to identify the optimal control parameters for a given process. Based on the analysis, the anticipated tool wear duration is 17.57 min, and the machining cost is estimated at 0.934 $/cm3 under cryogenic conditions. Cryogenic cooling reduces chipping and adhesion in cutting by minimising workpiece softening and improving cutting tool hardness.

Analysis of tool wear and surface roughness in machining of AISI 4462 duplex stainless steel

Abstract Machining is one of the most precise manufacturing methods used in the manufacturing of machine parts. In machining, significant tool wear is observed due to cutting tool-to-workpiece contact. Controlling tool wear and minimizing the effect of tool wear in this method is an important research topic. In this study, machinability tests were carried out on AISI 4462 duplex stainless steel materials, which are in the hard-to-cut material class. In the experiments, the changes in tool life and surface roughness were analyzed by using 150, 180, and 210 m/min cutting speeds; 0.1 mm feed; and 0.8 mm depth of cut. Increasing cutting speed significantly increased wear and reduced tool life. However, experiments with cutting speeds of 180 m/min and 210 m/min had the same tool life values. In addition, significant notch wear and BUE formation were observed on the tool surface. Besides, it was determined that the surface roughness deteriorated due to tool wear. In addition, surface deterioration due to chip wrapping was also observed in many passes.

The effect of tool wear on the damaged layer thickness and tool wear rate in ultra-precision turning of quartz glass

Quartz glasses have been extensively used for many fields, such as semiconductor technology, optical instruments, inertial navigation and others. Ultra-precision turning with diamond tools can achieve high surface accuracy when processing non-ferrous materials. In recent years, ultra-precision turning has also been tried to be applied to process brittle materials, but there are constraints including small removal amount and tool wear. When diamond tools are used to cut quartz glass, tool wear occurs under the combined action of thermal effect and mechanical friction, which will affect the damaged layer thickness of the processed quartz glass. In this paper, the tool wear factor is led into the calculation of the extrusion volume, and the damaged layer thickness is calculated by the extrusion volume. Combined with the results of quartz glass turning experiments and the calculated results by simulation, the effect of tool wear factor on the damaged layer thickness and the tool wear rate is analyzed. The analysis shows that tool wear will lead to chip fracture thickness decrease and extrusion volume increase. Combined action of these two aspects, the damage layer thickness keeps unchanged at first and then rises with the increase of tool wear. In addition, the experimental results show that the tool wear rate rises with the increase of tool wear.