Tool Tip Research Articles

Experimental–Analytical Method for Determining the Dynamic Coefficients of Turning Tools

The article presents an analytical and experimental method for determining the dynamic coefficients of cutting tools, with particular emphasis on turning tools. The method involves aligning the acceleration profile obtained from empirical investigations with a mathematical model describing the oscillations of the cutting tool tip. The stiffness (k) and damping (c) coefficients determined using this approach enable the design of tools with desired dynamic characteristics, tailored to specific machining processes, such as machining with long overhangs. From the perspective of mechanical dynamics, selecting appropriate stiffness and damping values allows for the design of tools with optimal dynamic properties. High stiffness reduces the occurrence of deformations under external forces, while adequate damping facilitates the rapid attenuation of vibrations, thereby minimising their adverse effects on the machining process. The developed method could serve as a practical tool for identifying the dynamic parameters applicable to a wide variety of cutting tools. The analysis includes three types of turning tools: one with a steel shank, another with a carbide-core steel shank, and a third with a carbon fibre-core steel shank. The results of the tests indicate that the E-A20Q SDUCL 11 tool is best suited for operations requiring high stability and minimal vibration, owing to its favourable damping and stiffness properties.

Ultrasonic vibration-assisted scribing of sapphire: effects of ultrasonic vibration and tool geometry

In recent years, semiconductors, electronics, optics, and various other industries have seen a significant surge in the use of sapphire materials, driven by their exceptional mechanical and chemical properties. The machining of sapphire surfaces plays a crucial role in all these applications. However, due to sapphires’ exceptionally high hardness (Mohs hardness of 9, Vickers hardness of 2300) and brittleness, machining them often presents challenges such as microcracking and chipping of the workpiece, as well as significant tool wear, making sapphires difficult to cut. To enhance the machining efficiency and machined surface integrity, ultrasonic vibration-assisted (UV-A) machining of sapphire has already been studied, showing improved performance with lower cutting force, better surface finish, and extended tool life. Scribing tests using a single-diamond tool not only are an effective method to understand the material removal mechanism and deformation characteristics during such UV-A machining processes but also can be used as a potential process for separating IC chips from wafers. This paper presents a comprehensive study of the UV-A scribing process, aiming to develop an understanding of sapphire’s material removal mechanism under varying ultrasonic power levels and cutting tool geometries. In this experimental investigation, the effect of five different levels of ultrasonic power and three different cutting tool tip angles at various feeding depths on the scribe-induced features of the sapphire surface has been presented with a quantitative and qualitative comparison. The findings indicate that at feeding depths less than 6 μm, UV-A scribing with 40–80% ultrasonic power can reduce cutting force up to 50% and thus improve scribe quality. However, between feeding depths of 6 to 10 μm, this advantage of using ultrasonic vibration gradually diminishes. Additionally, UV-A scribing with a smaller tool tip angle (60°) was found to lower cutting force by 65% and improve scribe quality, effectively inhibiting residual stress formation and microcrack propagation. Furthermore, UV-A scribing also facilitated higher critical feeding depths at around 10 μm, compared to 6 μm in conventional scribing.

Multifractal Spectrum Analysis for Assessing Pulmonary Nodule Malignancy.

Non-invasive assessment of pulmonary nodule malignancy remains a critical challenge in lung cancer diagnosis. Traditional methods often lack precision in differentiating benign from malignant nodules, particularly in the early stages. This study introduces an approach using multifractal spectrum analysis to quantitatively evaluate pulmonary nodule characteristics. A fractal-based protocol was developed to process computed tomography (CT)-digital imaging and communications in medicine (DICOM) data, enabling three-dimensional (3D) visualization and analysis of pulmonary nodule's multifractal spectrum. The method involves 3D volume reconstruction, precise ROI delineation, and calculation of fractal dimensions across multiple scales. Multifractal spectra were computed for both early-stage and late-stage lung adenocarcinoma nodules, with comparative analysis performed using data tip tool quantification. Analysis revealed that the fractal dimension of a pulmonary nodule's 3D digital matrix varies continuously with different voxel scales, forming a distinctive multifractal spectrum. Significant differences were observed between early-stage and late-stage nodules. Late-stage nodules demonstrated a wider scale range (longer X-axis) and higher extreme points in their multifractal spectra. These distinctions were quantitatively confirmed, indicating the method's potential for precise staging. The multifractal spectrum analysis provides a highly significant and precise quantitative method for staging pulmonary nodules, effectively differentiating between benign and malignant cases. This non-invasive technique shows promise for improving early diagnosis and accurate staging of lung cancer, potentially enhancing clinical decision-making in pulmonary oncology.

Enhancing surface roughness of material extrusion additive manufacturing components via an innovative ironing process

ABSTRACT Extrusion-based 3D printing is widely used in various industries, enabling the rapid creation of prototypes and functional parts at a lower cost compared to traditional technologies. However, one limitation of this technology is the surface finish of the components, where the roughness is not optimal. This paper presents a solution to improve the surface finish of components by leveraging the principles of ironing and ball burnishing. The tool, appropriately heated and passed over the component, smooths out imperfections by uniforming the surface profile. Unlike the traditional ironing method, the use of this tool reduces processing times and enhances surface roughness with a simpler construction and control mechanism compared to a conventional hot-end. The average surface roughness obtained is Ra = 0.796 μm; these values are comparable to those obtained by grinding. The geometry of the tool tips can vary significantly based on specific applications.

INCREASING THE EFFICIENCY OF MECHANICAL PROCESSING OF PARTS VEHICLES

The work theoretically substantiates the conditions for reducing the conditional cutting stress (energy intensity of processing) during grinding and blade processing of parts of transport machines, taking into account the angle of entry of the cutting tool into the processed material. It is shown that under the conditions of grinding, they consist in the change of the shape of microsections by cutting grains: the transition from counter grinding by the periphery of the wheel to the kinematic schemes of end and parallel grinding by the periphery of the wheel, the reduction of the intensity of friction of the cutting grain with the processed material and the negative front angle of the cutting material. In terms of blade processing, they consist in the application of tangential turning, parallel milling, especially with an end mill. The existence of the extremum (maximum) of the conditional cutting stress from the sum of the conditional friction angle of the cutting grain with the processed material and the negative front angle of the cutting grain has been proved. The ranges of change of this amount are determined, at which the conditional cutting stress becomes the smallest. It is shown that the nature of the change in the conditional cutting stress is determined by the change in the conditional shear angle of the processed material. It was established that infinite values of conditional cutting stress are achieved under the condition of equality of the conditional shear angle of the processed material and the angle of entry of the cutting tool into the processed material. Therefore, it is necessary to increase the conditional shear angle of the processed material by reducing the intensity of friction in the cutting zone and the negative front angle of the cutting tool. The conditions for increasing the efficiency of blade processing by increasing the ratio of the tangential and radial components of the cutting force, as well as the ratio of the slice thickness to the radius of rounding of the cutting tool tip, which consist in reducing the friction in the cutting zone and the front angle of the cutting tool, have been theoretically determined. The introduction at the machine-building enterprise of high-speed cutting technologies with progressive cutting carbide tools with wear-resistant coatings of the TaeguTec company with the use of high-speed CNC metal cutting machines of the "machining center" type made it possible to increase the efficiency of processing the complex profile surfaces of the "Cup of the wheel differential".

Investigation on the effect of probe stiffness on surface roughness in single crystal copper nanomachining process

Surface roughness is one of the most important features in nanoscale machining. In this paper, molecular dynamics simulations have been performed to investigate the combination effect of the tool stiffness, machining parameters and the tool tip geometry on the surface roughness of the single-crystal copper workpiece in the nano machining process by diamond tool. To consider the effects of probe beam dynamics in calculating the workpiece surface roughness, the probe cantilever is modeled as an equivalent spring-mass system that the tip mass is added to its end. The differential equation of the probe motion is solved simultaneously with the molecular dynamics equations for the tool tip and the workpiece and the effect of probe stiffness on the surface roughness is obtained. The result shows that a higher cutting speed and depth of cut and lower tool radius lead to a larger effect of probe stiffness on the surface roughness of the workpiece. Also, for the negative rake angles, considering the tool as rigid creates a large error in determining the surface roughness.

Research on Force-Saving Mechanism of Cutting Tool with Variable Curvature Directrix Rake Face Configuration

Optimizing the geometric configuration of the tool cutting surface, reducing the resistance in the cutting process and energy consumption, are always a concern. Through the method of bionic design, the directrix function of the longitudinal section of the beaver tooth rake face is extracted, and its variable curvature characteristics are analyzed. Based on this, a turning tool with variable curvature directrix configuration rake face is designed. The cutting force experiment and machining surface quality analysis experiment were carried out with the designed tool and the linear directrix configuration rake face tool respectively. The measured data of the variable curvature directrix configuration rake face tool is better than the linear directrix configuration rake face tool and its drag reduction performance of the tool is verified by experiments. Through the analysis of the working rake angle and shear angle of the tool with variable curvature directrix configuration rake face, the relationship between the parameters of the variable curvature directrix function and the working rake angle, and shear angle has been obtained. By the method of finite element simulation analysis, the stress field in the cutting zone of two different configuration tools has been analyzed. It has been found that the tool with variable curvature directrix rake face has a ‘bending moment’ effect on the tool-chip interface due to its curved surface configuration, and a ‘prying’ effect at the tool tip. These two effects promote the separation of chips from the workpiece and make the cutting process more force-saving. The research of this paper will have reference significance for the design and application of the curved surface configuration rake face tool.

Research on wear of CBN tool in precision machining of AISI M2 hard turning

Abstract In precision machining, tool wear deteriorates the surface quality of the workpiece and affects its surface integrity. Especially in hard turning precision machining, the tool is very prone to wear under the coupling load of large cutting force and high cutting heat. Therefore, tool wear has become one of the obstacles restricting the promotion of hard turning precision machining technology. This study investigates the effect of hard turning parameters on CBN tool wear using a single factor experimental method for dry hard turning AISI M2. The valuable research results are that: (1) The most prominent influence factor of CBN tool wear is cutting speed, and the increase of each processing parameter can aggravate tool wear; (2) The rake face, flank face and cutting edge of CBN tool are all worn, and their manifestations are crater, friction groove and micro chipping respectively; (3) The failure form of CBN tool is tool tip broken, including fatigue fracture caused by the decrease of tool tip strength and sudden fracture caused by large impact load; (4) The wear of CBN tool is resulted from mechanical friction, material adhesion and oxidation reaction, in which mechanical friction takes the main influence.

Investigation of Joinability Of 25% Recycled Al6016 Sheets By Friction Stir Butt Welding At Different Tool Rpm

In this study, 25% recycled 2 mm thick Al6016 sheets used in the production of automotive body and chassis parts were used. They were joined in the butt position using different tool speeds on the mold milling machine. The tool tip was selected as 2379 quality steel and the surface hardness was increased to 62-64 HRC. The sinking tip was designed as a conical geometry. In the joints, 400 mm/min welding progress speed, 1.8 mm tool tip immersion depth, 15 mm shoulder width and 90o tool inclination angle were kept constant. The rotation speed of the stirring tip was determined as 600 rpm, 1200 rpm, 1800 rpm, 2400 rpm, 3000 rpm, 3600 rpm as variable parameters. Heat inputs were calculated according to variable speeds. Samples taken from the welded joint with the friction stir method were examined with tensile, bending and hardness tests. Macro and micro images were examined and the fracture surfaces were compared. While the highest tensile strength at 400 mm/min feed speed was determined as 214 MPa at 1800 rpm and the lowest value was determined as 83 MPa at 600 rpm, no fracture was observed at 2400 and 3000 rpm as a result of the bending test and it was successful. The highest results of the hardness values of the joint area were measured as 97.4 Hv at 600 rpm rotation speed. It was determined that penetration occurred in the macro structure at all rpm speeds. When the micro images were examined, it was seen that the grain structure thinned from the base metal to the joint area.

Optimizing CNC turning of AISI D3 tool steel using Al₂O₃/graphene nanofluid and machine learning algorithms

Turning AISI (American Iron and Steel Institute) D3 tool steel can be challenging due to a lack of optimal process parameters and proper coolant application to achieve high surface quality and temperature control. Machine learning helps in predicting the optimal parameters, whereas nanofluids enhance cooling efficiency while preserving both the tool and the workpiece. This work intends to utilize advanced machine learning approaches to optimize process parameters with the application of hybrid nanofluids (Al2O3/graphene) during the CNC turning of AISI D3. The Response Surface Methodology (RSM), Back Propagation (BP) neural networks, and Genetic Algorithms (GA) will be utilized to model and predict optimal turning parameters to enhance surface quality and manage tool tip temperature. The experiments ranged the cutting speed, nanofluid concentration, depth of cut, and feed rate from 150 to 180 m/min, 0.3 to 0.9 wt.%, 0.5 to 0.9 mm, and 0.03-0.07 mm/rev. RSM and ANN analyses showed that cutting speed and feed rate had a significant effect on surface quality, contributing 11.5% and 10.5%, respectively, whereas the nanofluid affected tool tip temperature by 42.5%. The GA determined that the optimal cutting speed became 150 m/min, the feed rate was 0.05 mm/rev, the cutting depth was 0.6 mm, and the nanofluid concentration was 0.8%. At temperatures ranging from 23.01°C to 28.41°C, these conditions produced a desirable surface roughness of 0.16 to 0.45 μm. The findings emphasize the benefits of utilizing Al2O3/graphene nanofluid and machine learning algorithms in CNC turning to improve surface roughness and control temperature.

A Five-Axis Toolpath Corner-Smoothing Method Based on the Space of Master–Slave Movement

The smoothing of linear toolpaths plays is critical in improving machining quality and efficiency in five-axis CNC machining. Existing corner-smoothing methods often overlook the impact of spline curvature fluctuations, which may lead to acceleration variations, hindering surface quality improvements. The paper presents a five-axis toolpath corner-smoothing method based on the space of master–slave movement (SMM), aiming to minimize curvature fluctuations in five-axis machining and improve surface quality. The concept of movement space in master–slave cooperative motion is introduced, where the tool tip position and tool orientation are decoupled into a main motion trajectory and two master–slave movement space trajectories. By deriving the curvature monotony conditions of a dual Bézier spline, a G2-continuous tool tip corner-smoothing curve with minimal curvature fluctuations is constructed in real-time. Subsequently, using the SMM and the asymmetric dual Bézier spline, a high-order continuous synchronization relationship between the tool tip position and tool orientation is established. Simulation tests and machining experiments show that with our smoothing algorithm, maximum acceleration values for each axis were reduced by 21.05%, while jerk was lowered by 22.31%. These results indicate that trajectory smoothing significantly reduces mechanical vibrations and improves surface quality.

The generation mechanism of cutting heat and the theoretical prediction model for temperature on the rake face of the cutting tool in Zirconia ceramics

Cutting temperature and its distribution are crucial factors influencing tool strength and wear rate, due to the hardness and brittleness of Zirconia (ZrO2) ceramics, significant challenges arise in both direct temperature measurement in the cutting zone and theoretical analysis of cutting heat. Thus, focusing on the turning characteristics of ZrO2 ceramics, this study analyzes the mechanism of cutting heat generation and proposes utilizing thermodynamic state equations to determine the cutting heat source on rake face of tool. Based on the heat source method, a theoretically prediction model for temperature distribution on rake face is established. This model considers primary cutting parameters, workpiece material properties, crack fracture characteristics of the machined surface, and thermal characterizations of the tool material. The relationship between tool wear and cutting temperature is experimentally analyzed to determine the characteristic temperature that indicates the initial stage of tool wear. The validity of the theoretical model is verified, as the predicted results show high consistency with experimental results within the range of experimental parameters, with a relative error within 15.2 %.The results reveal the highest temperature during brittle cutting occurs within the cutting layer area, with the highest temperature occurring approximately 50 μm from the tool tip, followed by a gradual decrease beyond 150-200 μm. This study also demonstrates that cutting heat in ceramic turning does not solely originate from friction heat between tool flank-workpiece but also includes impact heat from tool rake face-workpiece, which under certain cutting parameters exerts a more significant influence on cutting temperature. This model can facilitate the selection and optimization of cutting process parameters for brittle materials and provide a theoretical basis for analyzing the relationship between tool thermal damage, thermophysical properties, and tool wear.

Experimental and numerical analysis on the cutting force, cutting temperature, and tool wear of alloy steel (4340) during turning process

This paper focuses primarily on the wear behavior observed in AISI4340 steel when machining with a multi-layered coated carbide tool. Numerical and experimental examination is processed out to predict the wear performance of AISI 4340 steel along with its cutting force and temperature. In this process, four layers of different coated material are bonded together to form a multi-layered coated carbide tool. The coated thickness is assessed with the assistance of a Scanning Electron Microscope (SEM). Experimental analysis takes place with a heavy duty lathe machine equipped with an infrared thermometer and force dynamometer. Simulation is performed using DEFORM-2D software to simulate cutting forces and interface temperature, and the output results obtained have been compared with the experimental work. With the help of the SEM image, maximum crater wear depth is evaluated and analyzed. Feed plays a crucial role in increasing the chip interface temperature and cutting force. For varied feed rates, the cutting tool edge radius, depth of cut, and cutting speed are taken as the input parameters. The proposed 2D finite element model provides effective parameter values for reducing wear. Results measured indicate that the output parameter values of interface temperature and cutting force obtained from simulation and experimental investigation match each other with high accuracy. Simulation results for temperature distribution around the tool tip show that a maximum temperature of 654 °C is formed at the feed rate of 0.4 mm/rev, leading to high heat flux. For the feed rate of 0.3 and 0.2 mm/rev, there is not much deviation in heat flux around the tool tip. The maximum temperature around the tool tip is near 527 °C for both 0.3 and 0.2 mm/rev. Simulation results show that the lowest tool wear of 0.001 23 mm was obtained for a feed rate of 0.2 mm/rev, followed by 0.004 25 (0.1 mm/rev), 0.005 09 mm (0.4 mm/rev), and 0.007 14 mm/rev.

Influence of TiAlN coating thickness in dry machining of AISI 1045 steel using Finite Element simulation and experiments

High performance cutting can be accomplished using coated tools with optimal coating thickness. Therefore, Finite Element (FE) simulation and experimental investigation are employed to study the influence of thickness of TiAlN coating in the range of 1 to 4 μm during face milling of AISI 1045 steel under dry condition. FE simulation is successful in effectively investigating the influence of coating thickness in machining performance in terms of cutting forces, Von Mises stress, tool tip temperature and crater wear of uncoated as well as coated milling inserts. Simulation results have predicted cutting forces and temperature with maximum errors of 9.21 % and 12.20 %, respectively. FE simulation further demonstrates 2.100 and 1.602 μm as the depths of crater for 1 and 3 μm thick TiAlN coated inserts, respectively, which are also validated by the experiments. The experimental results demonstrate that 3 μm thick coated tool is superior in mitigating cutting forces, particularly under higher cutting speed (150 m/min), bringing down tool tip temperature (6.67 %) and machined surface roughness (18.18 %) as compared to 1 μm thick TiAlN coated milling insert. The results obtained from the current research work clearly indicate that the effect of coating thickness can be effectively investigated using the FE simulation before finalising the optimal coating thickness for the coating depositions and machining experiments.

Investigation of Temperature at Al/Glass Fiber-Reinforced Polymer Interfaces When Drilling Composites of Different Stacking Arrangements

This attempt covers an investigation of cutting temperature at interfaces of Fiber Metal Laminates (FMLs) made of glass fiber-reinforced polymer (GFRP) stacked with an Al2020 alloy. GFRP/Al/GFRP and Al/GFRP/Al composite stacks are both investigated to highlight the effect of stacking arrangement on thermal behavior within the interfaces. In a first test series, temperature history is recorded within the metal/composite stack interfaces using preinstalled thermocouples. In a second test series, a wireless telemetry system connected to K-type thermocouples implanted adjacent to the cutting edge of the solid carbide drill is used to record temperature evolution at the tool tip. Focus is put on the effects of cutting speed and stacking arrangement on the thrust force, drilling temperature, and delamination. From findings, the temperature histories show high sensitivity to the cutting speed. When cutting Al/GFRP/Al, the peak temperature is found to be much higher than that recorded in GFRP/Al/GFRP and exceeds the glass transition point of the GFRP matrix under critical cutting speeds. However, thrust force obtained at constitutive phases exhibits close magnitude when the stacking arrangement varies, regardless of cutting speed. Damage analysis is also discussed through the delamination factor at different stages of FML thickness.

Unsupervised detection and mapping of sparks in the Electrochemical Discharge Machining (ECDM) process

Material removal in electrochemical discharge machining is caused by sparks generated in a tool immersed in an electrolytic solution. Being the primary machining agent in this non-contact machining process, mapping the locations of microscopic sparks is of great interest. The distribution of sparks around the tool surface could give insights into the machined hole properties like the size, surface finish, and depth as compared to the machining parameters such as applied voltage, tool size, rotation speed, and feed rate. This paper is focused on detecting sparks in photographs of the ECDM process captured using a high-speed camera. A novel approach of using a tri-planar reflective surface for capturing the location of sparks in 3D space using a 2D camera output is attempted. Traditional spark detection methods use neural network classifiers that need labeled data for training. This labeled data often comes from human intervention and contains inherent biases that could lead to misclassification. In this paper, an unsupervised spark detection methodology is demonstrated, which eliminates the need for human intervention and relies on the number of neighboring pixels detected in regions of interest (ROIs). The feasibility of using adaptive background modeling to classify thousands of images and identify the ones with sparks is demonstrated in this work. The masking technique combining effects of erosion followed by dilation is used to determine the exact boundaries of the spark contours in every image. Centroids for each of these contours are then transformed from the skewed coordinate system as observed in camera images, to a three-dimensional orthogonal coordinates system centered around the tool. The same procedure is repeated for various voltages to benchmark the distribution of sparks around a tool tip in an ECDM process.

Co-Kriging model-based multi-fidelity regression for refining milling stability predictions of variable tool overhang length using limited experimental data

Determining chatter-free machining parameters is critical in process planning since chatter vibrations significantly affect machining quality and production efficiency. Stability lobe diagram is essential in selecting chatter-free machining parameters, but its predictions confront challenges in both theoretical accuracy and experimental efficiency. To address this, the Co-Kriging modelling is introduced to predict the tool overhang length-dependent stability limits with limited experiments. First, tool tip dynamics and cutting force coefficients of a source overhang length are roughly identified to obtain sufficient low-fidelity (LF) theoretical stability limits. The entropy-based sampling and affine transformation are used to sequentially obtain high-fidelity (HF) experimental stability limits and update LF stability limits. HF and updated LF datasets are combined to train a multi-fidelity (MF) Co-Kriging model. For a target overhang length, MF stability limits of the source overhang length serve as LF data, and a minimum mean absolute percentage error (MAPE)-based sampling guides the acquisition of HF stability limits. Combining HF data and LF data processed by affine transformation to train a target Co-Kriging model. Case studies reveal that the proposed method exhibits lower MAPE values and significantly outperforms other comparison methods in predicting experimental stability limits, particularly when confronted with limited experimental data.

Vibration energy-based indicators for multi-target condition monitoring in milling operations

The demand for intelligent process monitoring is increasing in aerospace manufacturing to ensure tight tolerances and high surface quality. Real-time monitoring in machining is crucial for machined accuracy and process reliability, reducing production times and costs, and enhancing automation of the manufacturing process. This study presents a robust multi-target condition monitoring method based on the vibration signals. Firstly, three new energy ratio indicators with dimensionless characteristics were defined for tool wear, breakage, and chatter monitoring. Secondly, the vibration energy loss from the tool tip to the tool holder, and spindle housing was measured and compared, and the rules of vibration loss from the tool tip to the spindle housing were revealed. Using force signals as a reference, the monitoring performance of industrially acceptable acceleration and sound signals in multi-target condition monitoring was quantitatively analyzed. Finally, the performance of the proposed vibration energy-based indicators was experimentally illustrated and quantitatively evaluated. It is shown that these indicators can be used to discriminate between tool breakage and chatter, as well as to assess tool wear. The new monitoring method can also minimize the costs of process monitoring by reducing the use of expensive sensors or overusing multiple sensors in a smart manufacturing system.

Investigation on two-dimensional ultrasonic vibration plane turning method based on elliptical plane swinging strategy along short axis

In the ultrasonic elliptical vibration cutting (UEVC) process, the surface morphology suffers from the large fluctuation of ridge height and residual height, which has restricted the development of UEVC technology. Therefore, on the basis of the elliptical plane swinging strategy along a short axis, a surface topography improvement method (i.e., swing ultrasonic elliptical vibration turning (SUEVT)) for two-dimensional ultrasonic vibration plane turning is proposed in this study. The core idea of the method is to swing the ultrasonic elliptical vibration plane along the short axis to form a machining inclination angle, which reduces the ridge height of the machined morphology to a certain extent, thereby optimizing the surface microstructure and reducing the surface roughness. First, this study establishes a mathematical model of the tool tip trajectory of ultrasonic elliptical vibration under different swing angles, theoretically analyzes the influence of swing angles on the tool tip trajectory and surface topography, and provides a theoretical basis for revealing the surface topography formation mechanism of SUEVT. Second, an engineering practice scheme of SUEVT is proposed, and a processing experiment platform is built. Finally, cutting experiments of SUEVT for TC4 titanium alloy were conducted, studying the influence of swing angles on surface topography and roughness and assessing the feasibility of the method. Results showed that compared with ultrasonic elliptical vibration turning (UEVT), SUEVT has certain advantages in improving surface morphology. When the swing angle of SUEVT is 15°, the surface roughness decreases the most, reaching 19.00 %. Under the condition of SUEVT θ = 15°, the surface roughness decreases first and then increases with the increase in spindle speed, while it is proportional to the feed speed and ultrasonic power. The method proposed in this study can provide new methods and new ideas for ultrasonic elliptical vibration high surface quality machining.

Impact of Toolpath Pitch Distance on Cutting Tool Nose Radius Deviation and Surface Quality of AISI D3 Steel Using Precision Measurement Techniques.

The selection of the right tool path trajectory and the corresponding machining parameters for end milling is a challenge in mold and die industries. Subsequently, the selection of appropriate tool path parameters can reduce overall machining time, improve the surface finish of the workpiece, extend tool life, reduce overall cost, and improve productivity. This work aims to establish the performance of end milling process parameters and the impact of trochoidal toolpath parameters on the surface finish of AISI D3 steel. It especially focuses on the effect of the tool tip nose radius deviation on the surface quality using precision measurement techniques. The experimental design was carried out in a systematic manner using a face-centered central composite design (FCCD) within the framework of response surface methodology (RSM). Twenty different experiment trials were conducted by changing the independent variables, such as cutting speed, feed rate, and trochoidal pitch distance. The main effects and the interactions of these parameters were determined using analysis of variance (ANOVA). The optimal conditions were identified using a multiple objective optimization method based on desirability function analysis (DFA). The developed empirical models showed statistical significance with the best process parameters, which include a feed rate of 0.05 m/tooth, a trochoidal pitch distance of 1.8 mm, and a cutting speed of 78 m/min. Further, as the trochoidal pitch distance increased, variations in the tool tip cutting edge were observed on the machined surface due to peeling off of the coating layer. The flaws on the tool tip, which alter the edge micro-geometry after machining, resulted in up to 33.83% variation in the initial nose radius. Deviations of 4.25% and 5.31% were noted between actual and predicted values of surface roughness and the nose radius, respectively.