Milling Cutter Research Articles

MACHINE WHELL EDGE DETECTION MORPHOLOGICAL OPERATIONS

One of the critical issues of image processing, defined as obtaining useful information from the image and improving the quality of the image, is edge detection. How edge detection performance will be affected by adding morphological operators to edge detection algorithms is among the issues that have not been fully resolved. In the study, Canny and Sobel edge detection algorithms were applied to different milling cutters used in machinability. Morphological operators were applied to the determined edges, and their effects on the edges were examined. Mean Square Error (MSE) and Peak Signal Noise Ratio (PSNR) values were used to compare the performances of edge detection algorithms. According to MSE and PSNR results, it was seen that the Canny algorithm gave better results than the Sobel algorithm. In addition, it was concluded that the images obtained as a result of the applied morphological operations provided better performance than the images that were not applied for both Canny and Sobel algorithms.

An Integrated Model Based Prediction of Machining Accuracy for Milling Machine

The accuracy of machining can be predicted during the design process of CNC machine tools, while the prediction accuracy depends on the prediction model. However, when establishing the prediction model, the coupling effect among the machine tool’s different components is always ignored for modeling efficiency, so this will lead to its reliability cannot be guaranteed. To address this problem, the model reduction theory and the lumped parameter method are used in this study to set the state-space equations of the essential structural parts. Moreover, the electro-mechanical coupling parameter equation of the servo system is transformed into a state-space equation. Then the state-space equations of the components and the servo system are coupled to establish the machine tool dynamic model. Furthermore, a theoretical model of instantaneous undeformed chip thickness is found, and according to the linear relationship between the micro-cutting force and the instantaneous undeformed chip thickness, the instantaneous cutting force model of the cylindrical milling cutter is established. Based on these, the integrated model, which considers the mechanical structure, control system and cutting force, is obtained and further used in Simulink to build the machining accuracy prediction platform, as well as the accuracy of the integrated prediction model is verified. Moreover, the prediction model established by the integrated modeling method can effectively simulate the actual machining conditions of the machine tool, and the superiority of prediction is confirmed by comparing the simulated and measured results in peripheral milling applications. The results show the error in the system response efficiency is 14.8%, while the error in position accuracy and delay characteristics is less than 10%, the error between the predicted size of the prediction model and the actual size is within 28 μm, a minimum prediction error is 7 μm.

Исследование влияния элементов режима и шага зубьев фрезы на технологические параметры и температурное поле процесса обработки заготовок тонкостенных деталей

When machining workpieces of thin-walled parts, the temperature field differs from the field, which is formed during massive workpieces treatment. The reason for this is that machining of a thin-walled billet is interfered with its surface, being opposite to the one under machining. It has a significant effect on the temperature field, since the intensity of heat removal from this surface into the environment is significantly less than heat removal into the underlying layers of a massive material blank. In this regard, the problem of finding a rational mode of the machining process of thin-walled workpieces is relevant. The aim of the study is to determine the effects of the elements of the milling mode of thin-walled workpieces and milling cutter teeth space on the technological parameters of the milling process of titanium alloy workpieces and to develop recommendations for choosing this milling mode. For this purpose, a numerical modeling of the technological parameters of the milling process of blanks of massive workpieces and thin-walled parts made of titanium alloy, was performed experiencing various combinations of feed to the milling cutter tooth, cutting speed and milling cutter teeth space. When machining a thin-walled workpiece, due to less intense heat removal from the cutting zone into the workpiece, the temperatures in the areas of chip contact with the front surface of the tooth, the back surface of the tooth with the workpiece and the temperature of the workpiece itself are higher than when in a massive workpiece treatment. The patterns of changes in the parameters of the milling process of thin-walled workpieces depending on the feed, cutting speed and the milling cutter teeth space are established. With a larger tool stepover, the average and maximum temperatures in the areas of chip contact with the front surface of the tooth and the back surface of the tooth with the workpiece are lower in most of the combinations of mode elements used. Equations that establish the effect of feed on the milling cutter tooth, cutting speed and spacing of teeth on the parameters of the machining are obtained. The results of the study will allow choosing a rational milling mode and spacing of teeth in the work on workpieces of thin-walled parts made of titanium alloy.

Research on bionic design of cylindrical milling cutter based on the curvilinear configuration of the rake face of beaver teeth

Research on bionic design of cylindrical milling cutter based on the curvilinear configuration of the rake face of beaver teeth

Calculation of wheel path for 3+2-axis grinding of brazed carbide profile mill cutters for wood and plastic

Calculation of wheel path for 3+2-axis grinding of brazed carbide profile mill cutters for wood and plastic

Research on the minimum cutting thickness of variable density micro-texture ball-end milling cutter

The critical cutting thickness determines the minimum cutting amount of the tool for the workpiece material, which indirectly affects the machined surface quality of the workpiece and the manufacturing accuracy of key components. It is of great significance to study the minimum cutting thickness of a ball-end milling cutter based on a variable distribution density micro-texture model. Therefore, in this paper, the ball-end milling cutter is taken as the research object, and the variable distribution density micro-texture model is established. Based on the stick-slip friction theory, a theoretical prediction model is established for the minimum cutting thickness of titanium alloy. This model considers different forms of friction in the tool-chip contact area and takes into account the influence of the cutting-edge radius and the geometric parameters of the micro-texture. Based on the machined surface quality of the workpiece, an experimental method for solving the minimum cutting thickness is proposed for milling titanium alloy with a variable distribution density micro-texture ball-end milling cutter. The theoretical prediction model of minimum cutting thickness is verified by finite element simulation and milling tests. The results show that the minimum cutting thickness increases with an increase in the radius of the cutting edge. The error between the theoretical value and the experimental results is less than 10%, which fully verifies the accuracy of the theoretical model of the minimum cutting thickness of the variable distribution density micro-texture ball-end milling cutter.

Generation method and antifriction performance evaluation of discrete micro-pit surface texture based on high speed ball-end milling process

Benefiting from the structural characteristics of the ball-end milling cutter and the tool motion characteristics during the cutting process, the high speed ball-end milling process can be directly used to manufacture discrete surface micro-pits texture with different sizes and distributions. The influencing mechanism of the interval and distribution of the micro-pit texture on the antifriction performance was investigated by combining Fluent fluid simulation and reciprocating sliding friction test under oil immersion lubrication condition. Results show that the textured surface with micro-pit features shows obvious antifriction ability. The friction coefficient of textured surface was reduced by 61.5 % compared with that of polished specimens. The interval can influence the oil film bearing capacity and then the antifriction ability. The most significant friction reduction effect was achieved when the micro-pit interval was 900 μm. Additionally, the friction coefficient can be further reduced by optimizing the distribution of the micro-pits. The friction coefficient decreased to 0.121 for the orientation angle 70° condition.

Prediction of surface roughness and depth of cut in abrasive waterjet milling of alumina ceramic using Machine learning algorithms

In abrasive waterjet (AWJ) milling process, the ability to accurately predict outcomes such as surface roughness (Ra) and depth of cut (DoC) holds immense significance for cost reduction, resource optimization, and minimizing material wastage. However, a major challenge lies in the limited availability of AWJ milling datasets, hindering the development of robust machine learning models. To address the predicament of outcome, the present study employs a bootstrapping data augmentation technique to expand small AWJ milling datasets. Augmented data is used to train machine learning models, and hyperparameter fine-tuning is conducted using grid search and 5-fold cross-validation.In the prediction of surface roughness (Ra) for AWJ milling of alumina ceramic, the study finds that a Multi-Layer Perceptron (MLP) Regression model with a 4–100-100–1 architecture, 'relu' activation function, 'adam' solver, alpha value of 0.0001, and 'adaptive' learning rate outperforms the decision tree and random forest regression models. In the case of prediction of AWJ milling depth of cut (DoC) in alumina ceramic, the random forest regression model surpasses MLP and decision tree regression models. It employs hyperparameters including 100 estimators, 'gini' criterion, 'log2′ for maximum features, a maximum depth of 50, a minimum sample split of 10, a minimum sample leaf of 2, bootstrap as ‘True’, and a minimum impurity decrease of 0.The methodology followed to develop the machine learning models in this study is also tested in wire electrical discharge machining (WEDM) process in the machining aspects of metal matrix composites (MMC) for the prediction of surface roughness (Ra). The experimental dataset was adopted from (Satishkumar et al., 2011). In case of prediction of surface roughness (Ra) in WEDM, the random forest regression model outperforms MLP and decision tree regression models. These developed machine learning models hold the potential to greatly assist manufacturing engineers in selecting optimal input parameters for AWJ milling and WEDM, thereby reducing the wastage of machine resources.

Calculation of force parameters of workpiece machining process with end mill cutters

The aim is to develop and validate an operational methodology for calculating the force parameters and characteristics of the tool and the process of milling structural materials with end milling cutters. The structural schemes of machining and force models of oblique cutting processes in the modes of axial tool feed and continuous plastic deformation of the processed material were used when developing the method of preliminary calculation of the total axial force working on the cutting edge of end milling cutters. The rotating tool tests were conducted on a Hermle UWF 1202 H 3-axis machining center supplemented with a Kistler piezoelectric dynamometer (model 9272). Authors suggested, developed and tested the preliminary calculation method applied to the force characteristics of the machining process of workpieces by end milling cutters, considering how the energy power of ductile fracture of the machined material affects the process. Contact friction arising on the front and rear surfaces of the cutting tool does not reach the limiting value being subject to the Coulomb – Amonton law, that is, it is estimated by the dependence directly proportional to the normal pressure. After calculations, we defined the materials of the workpiece for milling, that is 45 steel (AISI 1045), and the end two-tooth cutter, uncoated T14K8 alloy, which was used to produce samples. The following milling modes were established: 4 mm boring depth; 50, 100 and 150 m/min cutting speeds; 0.05 and 0.1 mm/rev cutting tool feed. Deviation of the measured values of axial cutting force from the calculated values in the range of changing values of tool feed rate was found to be no more than 11%, and in the range of changing values of cutting speed no more than 15%. The developed calculation and analytical methodology for estimating force parameters of the machining process by end milling cutters provides an increase in the efficiency and reliability of the preliminary prognostic calculation of operating parameters and characteristics of cutting elements of end milling cutters.

Study on milling behavior of TiAlN coated tool with variable distribution density micro-texture

Considering that after milling titanium alloy with a ball-end milling cutter, the wear degree of different areas of the rake face is different, which indicates that the tool-chip contact conditions in this area are different, and then the micro-texture action mode is different. To improve the effect of micro-texture, this paper establishes a mathematical distribution model of variable distribution density micro-texture based on the two-zone method, builds a variable distribution density micro-texture ball-end milling titanium alloy test platform, studies the influence of variable density micro-texture parameters on tool milling behavior, and optimizes the parameters based on the improved particle swarm optimization algorithm. The results show that the micro-texture with variable distribution density has a positive effect on the milling behavior of the tool. The micro-texture parameters of the stickiness area have the greatest influence on the milling behavior of the tool. A texture parameter is optimized, and the overall milling behavior of the variable density micro-texture TiAlN coated milling cutter is optimal. This study provides a theoretical basis for the design and preparation of variable distribution density micro-textured tools. Highlights Based on the two-zone method, the mathematical distribution model of the variable distribution density micro-texture of the rake face of the tool is constructed. The influence mechanism of micro-texture parameters on the milling behavior of a ball-end milling cutter is explored. The multi-objective optimization of the variable density micro-texture parameters was carried out, and the optimal parameter combination was obtained. It is verified that the variable distribution density of the micro-texture has a positive effect on the cutting performance of the tool.

Hybrid tools for improved removal and surface finish of metals and non-metals

Increasing productivity and surface quality in manufacturing is inevitable for the efficient use of resources. Precision smooth surfaces are generally achieved through sequential milling, grinding, fine-grinding, and polishing. This research aims to increase productivity through a shorter process chain. Hybrid tooling technology is presented where an elastic fine grinding tool is integrated with a conventional milling cutter or a grinding tool, in order to produce smooth surfaces on metal and non-metals. A hybrid milling cutter with an elastic tool could produce a low-waviness surface as compared to that of a milled-only surface. Surface roughness could be reduced by almost 50% using the hybrid milling tool on a steel workpiece. A monocrystalline silicon surface was machined with a hybrid grinding tool. Surface roughness of Ra ~ 100 nm could be obtained for hybrid tool in comparison to Ra ~ 200 nm with grinding only tool. The surface machined with a hybrid tool showed ductile mode cutting streaks, whereas, the ground surface was observed to be completely in brittle mode. Additionally, the hybrid tools also showed reduced machining vibrations due to the damping effect induced by the elastic tool member.

Mathematical modeling and simulation of generation milling process to manufacture complex face gear surface through multi-axis machine kinematics

Manufacturing of face gear is a complex process, due to its varying geometry, hence the application is not wide as conventional gear geometry. The developments in analytical tools and kinematics of the CNC machine tools motivate researchers to explore the manufacturing process and associated applications. This article presents an efficient method for the generation milling of spur face gear utilizing a nutating head multi-axis CNC machine tool where the tool swings about an arbitrary axis in an inclined plane. The mathematical model of the disk milling cutter and face gear geometry were derived from the shaper geometry by applying the theory of gearing, equation of meshing and coordinate transformation. The cutter location (CL) data was evaluated by aligning the tool orthogonal unit vector and the tooth surface normal vector at the contact point by calculating the appropriate transformation matrices. The evaluation of machine coordinates on a multi-axis CNC milling machine was analyzed with respect to the machine pivot point and the axes movement during generation milling for the face gear drive was studied on the nutating head machine. The NC data is derived from the CL data using the inverse kinematics and the machining simulation was carried out using suitable software. The tooth surface deviation of a maximum of 43.5 μm was observed between the simulated model and the theoretical model, which is well within the requirement of roughing. The generation milling process with the proposed machine configuration is concluded as a profound face gear manufacturing technique.

Evaluation of the Structural Strength of a Prefabricated Milling Cutter with Replaceable inserts During Machining

Simulation modeling of the stress state of a prefabricated milling cutter with replaceable inserts during machining was carried out in the ABAQUS 2020 program using the finite element method. It has been established that the structural strength of a cutting tool depends on the geometry, material and cutting conditions. Based on the simulation, stress concentrators in a milling cutter with replaceable inserts were identified. The safety factor of the structure has also been determined, which meets the standard requirement. It has been established that a prefabricated milling cutter with replaceable plates during machining under extreme conditions ensures its performance with a margin of 20%. Thus, a prefabricated cutter with replaceable inserts is applicable for machining newly created and restored surfaces after hardfacing.

Modeling and Coefficient Identification of Cortical Bone Milling Forces of Ball-End Milling Cutter for Orthopaedic Robot

Modeling and Coefficient Identification of Cortical Bone Milling Forces of Ball-End Milling Cutter for Orthopaedic Robot

Evaluation of Non-Planar Tool Interaction in Milling of Shaped Surfaces Using a Copy Milling Cutter

When milling complex parts or curved surfaces, we encounter several problems that must be addressed in the production process. Various factors affect the quality and accuracy of production. The main objective of this paper was to analyse the size of the effective tool diameter when machining a shaped surface concerning the selected position, namely at the perpendicular position of the tool. At the same time, the distribution of the engagement area on the tool surface was evaluated by extracting the area content and volume data at the point of contact. This study highlights the importance of the choice of finishing strategy in a CAM system. The results showed that the tool engagement size corresponded to the extracted data describing the area and volume for each tool position with regards to the curvature of the surface. The negative deviations obtained by the scanning method were due to machining near the tool centre, which was affected by the changing effective tool diameter.

Dynamics modeling and simultaneous identification of force coefficients for variable pitch bull-nose cutter milling considering process damping and cutter runout

Dynamics modeling and simultaneous identification of force coefficients for variable pitch bull-nose cutter milling considering process damping and cutter runout

MODELING OF ROUGH ROTARY MILLING OF CRANKSHAFT PINS

The development of the modern automotive industry requires a quick adaptation of new production methods. This is possible thanks to software capable of simulating manufacturing processes. The paper discusses the modeling of the machining operation of a crankshaft’s crankpins for a diesel engine with the use of the planetary milling method. i.e., modeling of milling operation when a disc milling cutter, having its cutting inserts directed inwards, is performing rotary motion, and at the same time, the axis of this milling cutter circulates around the axis of a machined crankpin. For this purpose, a geometrical model of the machining of the crankshaft’s crankpin has been developed. Based on the design documentation of the crankshaft of the 4C90 type diesel engine and the documentation of the Steyr internal disc milling cutter, their CAD models have been developed, and the both models were linked together with suitable kinematic dependencies. In the next step, the crankpin having a length of 25 mm was divided by planes (in quantity lp=21) into 1.25 mm sections. On the main cutting edge of two cutting inserts of the disc milling cutter, points were marked at intersection locations with these planes. Using the Inventor 2016 system, twelve spline curves have been generated for each plane because each plane intersects 12 cutting inserts mounted in cassettes positioned around the circumference of the body of the disc milling cutter. Next, the spline curves were brought to a common coordinate system, rotating them at an angle resulting from the positioning of the cassettes with cutting inserts in the body of the disc milling cutter. Prepared in such a way, spline curves were written in dwg format, which allowed for trimming of the spline curves at the circle with a radius of rcp = 27.90 mm, corresponding to the radius of the crankpin after milling, considering grinding allowance (ø55h6 + 0.80 mm grinding allowance). As a result, it enabled to leave sections of the arcs tangential to the diameter ø55.80 mm and, in such a way, generate the outline of the shape of the crankpin using the REGION command for 21 cross-sections. The outline of the cylindricity of the crankpin was obtained using the strategy of outlines of the roundness, which were generated earlier; this strategy consisted in the collection of 360 points on the circumference of 21 mutually parallel sections cut by planes perpendicular to the axis of the crankpin. To determine the effects of the circular feed rate of the circulating move of the axis of rotation of the internal disc milling cutter on the accuracy of the machining, simulations of the shape of the crankpin were performed for three values of the feedrate: vf = 1200 mm/min; vf = 2100 mm/min and vf = 3000 mm/min. The spline curves with a determined (depending on the duration of the simulation) number of points: 3500, 2100 and 1409 were obtained for each simulation. The calculated cylindricity deviation for the feedrate vf = 1200 mm/min amounted to CYLrck = 0.2272 mm, for the feedrate vf = 2100 mm/min – CYLrck = 0.2406 mm, while for the feedrate vf = 3000 mm/min – CYLrck = 0.2929 mm.

FACE MILLING CUTTERS FOR COMPOSITE MILLING HEADS

The paper considers designs of the face milling cutters used in composite milling heads. The advantages and disadvantages of known face milling cutters are analyzed. The design of the face milling cutter, in which the number of additional screws is equal

Modeling and analysis of radial throw of micro-milling tool based on tool-attachment errors in high-speed rotating

In the process of micro-milling complex structures, radial throw is likely to cause lower dimensional/form accuracy, which will severely affect the performance of the components. Therefore, it is necessary to investigate the source contributing to the radial throw. According to the kinematic process of the radial throw arising from the attachment errors of the micro milling cutters, a mathematical model considered the attachment errors and the variable section geometry of the micro milling cutters was established to predict the radial throw on the basis of the principle of minimum total potential energy and the Timoshenko beam theory. In comparison to the mathematical model, the proposed finite element model (FEM) presetting the attachment errors shows the effect of modal vibration and the variation of radial throw with attachment errors. To further investigate the environmental factors influencing the radial throw, a measurement method based on the laser measurement system is presented to achieve the on-machine measurement of runout, and a specific extraction method of attachment errors was proposed to help validate the mathematical model. The difference between the results of the mathematical model, FEM, and the experiment is not exceeding 10 % within 3 μm of the maximum runout. Radial throw varies strongly with attachment errors, and the high rotation speed will aggravate the system instability caused by the attachment errors. The main contributor among experimental factors to the variation of runout is the form accuracy of micro milling cutters, accounting for 4.7 % at the highest. This method can provide a theoretical basis for the sources of unbalanced cutting force analysis and the improvement of dimensional/form accuracy.

Image super resolution by double dictionary learning and its application to tool wear monitoring in micro milling

It is an effective means to improve the machining quality of product by monitoring the tool wear conditions in micro milling. However, due to the small size and high speed of the micro milling cutter, it is difficult to capture the clear image of tool wear by CCD camera. Therefore, a double dictionary sparse coding super-resolution (SR) method is proposed to improve the resolution of micro milling tool wear images in this work. Based on the traditional single dictionary, this work proposes the residual dictionary to reconstruct the residual image of the tool, achieving the double dictionary coefficient encoding reconstruction. In order to extract local features of low resolution (LR) tool wear images, the Gobor filter banks are designed, and then the PCA method is used to reduce dimension of extracted features. The dictionary learning based on a single high resolution (HR) image is realized, which reduces the dependence of super-resolution algorithm on large datasets. The effectiveness of Gabor filter and double dictionary for restoration tool wear image details is verified by experiments. Compared with proposed method, traditional interpolation method, sparse coding super resolution model [32] and super resolution convolutional neural network model [26], the PSNR mean value of those methods are 43.62, 42.19, 43.20, 43.21, respectively, which shows that the proposed method has excellent performance in super-resolution reconstruction of micro milling tool images for tool wear monitoring.