Amount Of Tool Wear Research Articles

Tool wear prediction based on kernel principal component analysis and least square support vector machine

Abstract To accurately predict the amount of tool wear in the machining process, a monitoring model of tool wear based on multi-sensor information feature fusion is proposed. First, by collecting the cutting force, vibration, and acoustic emission signals of the tool during the whole life cycle, the multi-domain characteristics of the signal are extracted; then, kernel principal component analysis is used to reduce the dimensionality of the extracted data, and the principal components whose cumulative contribution ratio exceeds 85% are obtained. The redundant features with little correlation with tool wear were removed from the feature vectors to generate the fusion features. Finally, the fusion features are input into the least squares support vector machine model optimized by particle swarm algorithm for regression prediction of tool wear. The non-linear mapping relationship between the physical signal and the tool wear is discovered, which effectively realizes the prediction of the tool wear. Compared with the existing tool wear prediction methods, the method proposed has higher prediction accuracy.

Experimental investigation of Aluminum Nitride ceramics based on compliant finishing process

Aluminum Nitride (AlN), as a type of advanced functional ceramic material, has found wide applications in many fields, owing to its advantageous properties such as excellent thermal conductivity, high hardness and strength, etc. Nevertheless, these beneficial features bring great challenges to its machinability using current existing methods that commonly result in unsatisfactory surface qualities. In this paper, we investigated the processing performance of AlN by introducing the compliant bonnet finishing approach based on different tool bonding materials and abrasive sizes. The distinctive finishing qualities, material removal rates, tool wear behavior, etc., were studied and compared under various process conditions. Unlike other ceramics, resin bonded diamond tools with a 3 μm abrasive size exhibit significant wear when used on AlN ceramics. The curves for tool wear amount and wear rate are investigated. Meanwhile, compliant tool with the smaller abrasive can obtain the sub-50 nm surface roughness. The comparison with traditional rigid pellet finishing further demonstrates the advantageous finishing performances by using compliant tools on the AlN ceramics.

An application of hybrid Taguchi-ANN to predict tool wear for turning EN24 material

This work is an attempt to predict tool wear for turning EN24 material by the hybrid Taguchi-ANN (Taguchi-Artificial Neural Network) method. The objective is to minimize the tool wear. The independent factors are cutting environment, feed rate, depth of cut, nose radius, and tool type. A Spinner numerical control lathe is used to assess performance. As per the Taguchi orthogonal array, 27 experiments are conducted for each value of the uncontrollable factor (spindle vibration). Optimal setting is structured by Taguchi analysis and the response table. The additive model is used to predict the response. Conformity test is carried out to check whether the predicted and experimental values of response are within the range given by the confidence interval. Furthermore, the ANN is used to predict and analyze the tool wear. The result showed that the supremely important parameter is depth of cut and the least important parameter is tool type. The ideal set found is A3, B3, C3, D1, and E3. Through ANN analysis, it is observed that the experimental values are very close to the predicted values of tool wear. The predicted value at optimal setting is 0.0401 mm. The experimental values at optimal setting is 0.0422 mm. In addition, the study showed that when the feed rate and nose radius are both set to high levels and the depth of cut is medium, using an uncoated tungsten carbide tool with minimal lubrication results in the least amount of tool wear.

Wear characteristics of the tool in the cold stamping process of ultra high strength steel sheets by establishing a novel wear test method based on the progressive die

Demands for lightweighting and crashworthiness of the vehicle body have increased. For this purpose, advanced high strength steel to the automobile body was regarded as a solution with respect to manufacturing cost and impact energy absorption. However, increasing the strength of the automotive steel sheet lead to a diversity of problems caused by the tool wear due to higher forming load than that of commonly used steel sheets. Hence, systematic wear experiment and evaluation methods are required to quantitatively and qualitatively evaluate the tool wear amount in the sheet metal forming process. In this study, a methodology is proposed to quantitatively evaluate the wear of sheet metal forming tool based on the experimental results. In order to carry out a systematic wear test and save the time and cost, the progressive die set was designed to be suitable for wear test. The designed testing machine can simultaneously test four types of punches made under various tooling conditions such as materials, shapes, and coatings. Through the measurement of the wear depth, roughness, and surface imaging of the punch and product roughness, which represent the wear characteristics, quantitative evaluation methods for tool wear in the sheet metal forming process are established. By referring to the wear test results, it is confirmed that it is appropriate to analyze the reasonable tool wear characteristics by using the proposed methodology for quantifying the tool wear in the sheet metal forming process.

Определение оптимального режима обработки металлов при анализе динамики систем управления резанием

Introduction. In numerous experimental studies of metal cutting processes on metal-cutting equipment, the existence of some optimal processing mode is noted, which was most vividly formulated by A.D. Makarov in his point on the existence of an optimal cutting temperature (processing speed). Here, by the authors from Russia, the emphasis is on the description of the optimality of cutting processes related to the properties of the processed material and the properties of the tool used in this process. However, there is another opinion in the Western scientific literature, which is generally based on the regenerative nature of vibrations in cutting dynamics. Vibration regeneration is associated with the dynamics of the cutting process, which is significantly affected by a lagging argument reflecting the variability of the cut layer. The connection of these two approaches is seen through the analysis of the stability domain of the dynamic cutting system in the parameter space: cutting speeds and tool wear values. Subject. Based on this, the paper considers the question of the relationship between the optimal according to A.D. Makarov the processing mode and the dynamics of the cutting process, including the regeneration of tool vibrations during metal turning. To do this, two research hypotheses are formulated and numerical modeling is performed in order to determine its reliability. Purpose of the work: to consider the position of A.D. Makarov on the existence of an optimal cutting mode, from the point of view of the stability of the dynamics of metal turning. For this purpose, two hypotheses are put forward in the work to be analyzed. The paper investigates: a mathematical model describing the dynamics of vibration oscillations of the cutting wedge tip, taking into account the dynamics of the temperature formed in the contact zone and its influence on the forces that prevent the forming motions of the tool. Research methods: a series of field experiments was carried out on a metalworking equipment using the capabilities of the measuring stand STD.201-1, the purpose of which was to determine the effect of the thermal expansion of metals on the value of the buoyant force. Based on numerical simulation of the initial nonlinear mathematical models, as well as simulation of models linearized in the vicinity of the equilibrium point, an analysis of the stability of the cutting system with variations in the cutting speed and the amount of tool wear along the flank is conducted. The results of the work. The results of field experiments are presented, which showed a significant linear increase in the force pushing out the tool with an increase in temperature in the contact zone of the tool and the workpiece. The results of simulation of the state and the corresponding phase trajectories when the cutting wedge is embedded in the workpiece, as well as the forces decomposed along the axis of deformation of the tool, are presented. The results of modeling the Mikhailov vector hodograph for a linearized model of the dynamics of the cutting process are presented. Conclusions: The research results have shown that only the second hypothesis put forward by the authors makes it possible to adequately interpret the point put forward by A.D. Makarov. The main addition to the description of the point of A.D. Makarov, the authors consider it necessary to take into account changes in the pushing force with an increase in the temperature of the contact zone of the tool and the workpiece.

Особенности применения ультразвука при плазменно-механической обработке деталей из труднообрабатываемых материалов

Introduction. Structural materials, including materials made of heat-resistant and hard-to-work steels, are widely used in various branches of mechanical engineering. To increase the efficiency of manufacturing parts of thermal equipment from heat-resistant and hard-to-work steels, the technological method of cutting with preliminary plasma heating of the workpiece is used. There is also a technological method of cutting metals, including hard-to-process materials by ultrasonic turning. Proceeding from this, in order to increase the efficiency of plasma machining of hard-to-process materials, it is necessary to investigate the technological possibilities of using ultrasonic turning of hard-to-process materials during plasma machining. The purpose of the work: to investigate the wear of cutting tools when using ultrasound in the conditions of plasma-mechanical processing of parts made of hard-to-process materials. The paper investigates the features of the plasma-mechanical processing under ultrasonic cutting conditions and determines the wear values of carbide cutters VK8, T5K10 and T15K6 when processing steels of grades 20Cr13Ni18 and 20Cr25Ni20Si2(cast). And also the wear of these cutters was determined under the conditions of conventional turning of the same materials to compare the results of wear of the cutters in different processing conditions. The research method is to determine the linear wear of carbide cutters along the back surface with conventional, plasma-mechanical and plasma-mechanical cutting assisted with ultrasonic cutting using an instrumental microscope and visual estimation with a 10x magnifying glass. Results and discussion. The paper presents the results of experimental studies to determine the wear of cutting tools when processing heat-resistant steels of the 20Cr13Ni18 and 20Cr25Ni20Si2(cast) grades with carbide cutters of the VK8, T5K10 and T15K6 grades. Studies were carried out to determine the wear of carbide cutters as with conventional mechanical cutting, plasma-mechanical cutting, as well as plasma-mechanical cutting using ultrasound. The experiments were carried out when turning these materials on a modernized lathe mod.1A64. A rectifier with a controlled choke and a plasma torch mod.APR-403 are connected to the lathe; a plasma holder is placed on the lathe carriage. A semiconductor rectifier serves as a power source with a compressed electric arc of current. The arcing takes place between the cathode (plasma torch) and the anode (blank) at the point of the plasma-forming gas; compressed air passes through the nozzle channel of the plasma torch. During the experiments, the position of the plasma torch was adjusted relative to the part rotation axis. When conducting experiments on studying the wear of cutters under conditions of ultrasonic plasma-mechanical cutting, ultrasound was applied to the cutting edge using a device developed by the authors. When processing heat-resistant steels under the usual turning condition, processing modes were adopted: cutting speed V = 10 m/min, cutting depth t = 3...4 mm, longitudinal feed Sl = 0.31 mm/rev. It is found that when processing steel grade 20Cr13Ni18 by conventional cutting, the back surface of the carbide cutter made of T5K10 wears out to 1 mm in size within 10 minutes, and for the cutter made of VK8 – within 15 minutes. During plasma machining, the cutting speed and the feed rate were increased 2 times; the results of the wear of the cutters show that at the same time T5K10 wears out to 1 mm within 20 minutes, VK8 – within 25 minutes. Plasma-mechanical processing using ultrasound show that the carbide cutter T5K10 wears out by 0.50 mm in less than 50 minutes of cutting, and VK8 wears out by 0.35 mm. The same results are obtained when processing heat-resistant steel 20Cr25Ni20Si2(cast). Thus, the study of wear of carbide cutters in the processing of heat-resistant steels shows that the use of ultrasonic cutting in plasma-mechanical processing of steels can significantly reduce the amount of tool wear. The presented results confirm the prospects of using ultrasonic plasma-mechanical cutting of heat-resistant steels with blade tools.

An Approach to Measure Tool Wear through Image Processing in Incremental Sheet Metal Forming

The Incremental sheet metal forming (ISF) is come into the light due to its unique forming technique. In ISF, the metal sheets are transformed into the final product without using dedicated died. The plastic deformation of metal sheets is conducted through a simple forming tool. Its processing time resembles that the ISF is suitable for the formation of customized products, prototypes, and low volume production. Tool life in manufacturing processes is an important consideration for productivity. The present study is an approach to use image processing techniques to measure the exact location and amount of tool wear in the ISF tool which is made of 440C steel. Presently the complex histogram plot is under study. Therefore to predict the tool wear, feed-forward backpropagation (FFB) algorithm is utilized. It is reported that the maximum predicted tool wear of 0.0663mm is found in the trail run 05 with an error of 0.0104mm. The best-fitted value of the FFB model is observed at the epoch 05 with the value of 5.922e-005. The overall coefficient of performance i.e. R2 of FFB modeling is reported as 90.52 % with the mean absolute error (MAE) of 0.0042 which shows a good agreement of the prediction model.

Pseudo analytical modelling of flank wear for coated/micro blasted cemented carbide cutting tools

Machining of difficult to cut material leads to excessive amount of tool wear owing to dynamic nature of stresses. The amount of tool wear affects the machinability as well as tolerances during the cutting operation. Thus, monitoring of the flank wear is necessary under sustainable cutting environment. However, such monitoring in industrial and practical applications is a tedious task. The current study focuses on development of pseudo analytical model to predict the wear behaviour during the machining operation for the coated as well as surface modified (coated/micro blasted) tools. The model is possibly the first of its kind which incorporates the hardness of the coating, workflow stress and forces acting on the tool, while predicting the tool wear values. The developed model was calibrated and validated experimentally during the turning of Nimonic C 263 using AlTiN coated tools (treated and untreated) at varying cutting conditions. During the analysis it was found that the experimental results were very much in agreement with predicted values of the flank wear, and the flank wear progression also followed the similar pattern as that of the later.

Deformation Analysis of Continuous Milling of Inconel718 Nickel-Based Superalloy.

As a difficult-to-process material, Inconel718 nickel-based superalloy is more and more widely used in aerospace, ocean navigation, and large-scale machinery manufacturing. Based on ABAQUS simulation software, this paper takes the milling force and temperature in the milling process of the nickel-based superalloy as the research object, and establishes the empirical formula for the prediction model of cutting force and cutting temperature based on the method of multiple linear regression. The significance of the prediction model was verified by the residual analysis method. Through data analysis, it is obtained: within a certain experimental range, the influence degrees of each milling parameter on the cutting force and cutting temperature are and , respectively. The actual orthogonal cutting test was carried out on the machine tool, and the reliability and accuracy of the prediction model of cutting force, cutting temperature and tool wear amount were verified. The model formulas of the shear velocity field, shear strain field and shear strain rate field of the main shear deformation zone are constructed by using mathematical analysis methods. The influence law of cutting speed and tool rake angle on the variables of main shear zone is calculated and analyzed. Through the combination of theory and experiment, the relationship between cutting force, chip shape and machined surface quality in milling process was analyzed. Finally, with the increase in the cutting force, the serration of the chip becomes more and more serious, and the roughness of the machined surface becomes greater and greater.

Preparation and characterization of ultra-thin dicing blades with different bonding properties

Ultra-thin dicing blade is usually used to achieve a high precision cutting in semiconductor back-end packaging and assembly. Lots of interactional parameters involving in dicing blade preparation and cutting process bring difficulties to high cutting qualities and good working life of dicing blade. In order to address these problems, this study prepared three kinds of dicing blades and characterized the cutting properties of three dicing blades. It first proposed the abrasive exposure coefficient and the tool deviation coefficient to provide parameters for the cutting force model. Then, the experimental apparatus was set up to verify the proposed cutting force model. And a series of parameters including feed rate, spindle current, edge chipping coefficient, tool wear amount, and grinding performance are used to characterize the comprehensive performance of prepared dicing blades. Finally, the edge morphology was observed under 3D microscope to analysis the hardness of different dicing blades. The theoretical and experimental results indicate that the proposed cutting force model can reflect actual cutting process. There is an inverse proportional function between the shedding of abrasive particles from matrix and the hardness of the matrix. The cutting performance of dicing blades is very dependent on the material of workpiece. C-dicing blades presents outstanding comprehensive effects with small chips and good self-sharpening properties.

Prediction of machine tool wear using the weighted k-nearest neighbor method and Neural network model with acceleration response

In the manufacturing industry, with the decrease in the working population, there is a demand for intelligent manufacturing processes (smart factory). When focusing on cutting, predicting and detecting tool wear during machining is an important technical issue for autonomy. However, the tool wear of cutting tools varies from machining to machining even under the same machining conditions, with the same type of tool, and with the same material and shape of workpiece. Therefore, even if a representative wear prediction model is constructed to predict tool wear, the prediction accuracy is low and not practical. In this research, we will verify whether the amount of tool wear can be predicted by a neural network, which is a type of machine learning, using the vibration data obtained during cutting and the past. The accuracy of the proposed method is also verified by comparing the wear volume prediction by one representative neural network with the wear volume prediction by the combination of the proposed multiple neural network.

Experimental investigation into tool wear, cutting forces, and resulting surface finish during dry and flood coolant slot milling of Inconel 718

Inconel 718 superalloy is a widely used material in aerospace due to its high strength, corrosion resistance, and high resistance to thermal fatigue. Excellent mechanical and thermal properties also make Inconel 718 one of the most difficult-to-machine alloys. This study aims to take a different approach of analyzing tool wear during machining of Inconel 718 by measuring worn-out area on each flute from three different faces of flute. This paper also includes analysis of cumulative tool wear, cutting forces, surface roughness, topography, burr formation, and chip morphology at various machining parameters and cooling conditions. The cutting speed was kept constant at 60 m/min due to the goal of machining at highest possible speed and the limitation in maximum spindle speed of the machine tool. Experiments were carried out in dry and flood coolant machining using uncoated carbide tools by varying depth of cut and feed rate for four different settings each. It was found that the amount of tool wear varied for different flutes when measured from top, rake, and back faces of each flute, even for the same tool. The back and rake faces exhibit more chipping wear when machining is carried out at higher depth of cut, irrespective of the cooling conditions. At the same machining conditions for the range of parameters selected in this study, flood coolant machining resulted in slightly higher tool wear at the back and rake faces of cutting flutes and generated higher cutting speed, which may be interrelated. The gradual increase in tool wear over time resulted in an increase in surface roughness from entry to exit of a 76.2 mm machined slot. Flood coolant machining resulted in slightly smoother surface finish at the lower settings of depth of cut and feed rate, while the burr formation was marginally higher in flood coolant machining during machining at higher feed rate and depth of cut. The amount of serration was found to increase specifically with the increase of feed rate and was found to be higher for dry machining compared to flood coolant machining at the same parameter settings. Finally, the new approach of tool wear analysis from different faces of individual cutting flute could provide important guidelines for predicting tool life or potential catastrophic tool failure during machining of Inconel 718.

Fundamental investigations on wear evolution of machining Inconel 718

Nickel-based superalloys are often used in aerospace industry for different applications, e.g., blisks or turbine blades. Due to its high strength and corrosion resistance, materials like Inconel 718 lead to a poor machinability and, thus, to a high amount of tool wear. In this paper, the influence of different process parameter values on the tool wear is analyzed. For the fundamental investigations, the tool wear evolution was examined for two different path strategies with and without coolant. To identify suitable process parameter values, the width of flank wear land and process forces were analyzed based on a screening design of experiments.

Minimum quantity lubrication turning of hard to cut materials – A review

The machining of hard to cut work materials produced lot of heat produced at the cutting zone resulted in generation of high cutting temperature at the tool-chip/tool-workpiece interface. Further, the high amount of tool wear (flank wear, crater wear), escalates the cutting forces, residual stresses as well as energy consumption and reduces the life of tool during turning process. To overcome these negative effects minimum quantity lubrication (MQL) as sustainable manufacturing technique has been largely used by researchers. High velocity mist droplets after penetration at the cutting zone, formed vapour blanket and give more effectual heat transfer than flood cooling. MQL process enhanced the turning performance in terms of low tool wear, excellent surface finish, and minimum cutting forces, lessen cutting temperature. This study, attempts to vitally evaluate the research scenario during turning of difficult-to-cut materials under environment friendly MQL technique.

Self-adjusting on-line cutting condition for high-speed milling process

The paper presents an intelligent control system for self-adjusting on-line cutting condition for high speed machining (self-HSM) with considering the tool-wear amount to keep the machined product’s quality in allowable limit. For realizing the self-HSM, the empirical analysis of variance (ANOVA) and artifical neural network (ANN) are used. The ANOVA is used for generating the empirical functions which are used as the boundary condition as well as constraint evaluation. The ANN is used for generating the new optimal cutting condition. Then, the self-HSM updates this cutting condition on the real machine — HS Super MC500. The new optimal cutting parameter is sent to the controller for updating the new machining condition to keep the machined part’s quality. The integration of the empirical analysis and ANN enables generating the optimal cutting parameters correctly and efficiently for high-speed milling.

Influence of cryogenic heat-treatment soaking period and temperature on performance of sintered carbide cutting tools in milling of Inconel 718

Cryogenic heat treatment is an innovative heat treatment applied to improve the mechanical properties of sintered carbide cutting tools. In this study, the effect of cryogenic heat treatment used at different temperatures and soaking periods on the mechanical properties of carbide cutting tools was investigated. Cryogenic heat treatment was applied at two different temperatures, −145 °C and − 196 °C, for 24 and 36 h soaking periods. The microstructure of the cryogenic heat-treated cutting tool was investigated as microhardness and grain size. As a result of microstructure analysis, heat treatment soaking period was found to be more effective than heat treatment temperature. Milling tests of the Inconel 718 superalloy were performed under dry conditions using cryogenic heat-treated cutting tools and non-heat treated tools. The effect of heat treatment on cutting tool performance was studied in terms of the amount of tool wear, cutting force, surface roughness values. According to the results obtained, the cryogenic heat treatment applied to the cutting tools has a positive effect on cutting performance. In addition, in the examinations carried out on worn cutting tools, effective wear mechanisms were found to be oxidation, adhesion and abrasion.

Effect of minimum quantity lubrication and vortex tube cooling on laser-assisted micromilling of a difficult-to-cut steel

Laser-assisted micromilling is a promising micromachining process for difficult-to-cut materials. Laser-assisted micromilling uses a laser to thermally soften the workpiece in front of the cutting tool, thereby lowering the cutting forces, improving the dimensional accuracy, and reducing the tool wear. Thermal softening, however, causes the workpiece material to adhere to the tool and form a built-up edge. To mitigate this problem and to enhance micromachinability of the workpiece in laser-assisted micromilling, this article investigates the following lubrication and cooling methods: (1) minimum quantity lubrication and (2) vortex tube cooling. Experiments utilizing the two methods are carried out on a difficult-to-cut stainless steel (A286), and the surface morphology, tool condition, burr formation, groove dimensional accuracy, surface finish, and cutting forces are analyzed. Results show that the combination of laser-assisted micromilling and minimum quantity lubrication yields the least amount of tool wear, lower resultant force, better groove dimensional accuracy, and no built-up edge. While vortex tube cooling with laser-assisted micromilling produces smaller burrs compared to minimum quantity lubrication, it yields larger changes in groove dimensions and is characterized by built-up edge formation. Possible physical explanations for the experimental observations are given.

Study on the critical negative rake angle of the negative rake angle tool based on the stagnant characteristics in micro-cutting

The critical negative rake angle of negative rake angle tool is the critical criterion for the state of cutting and plowing in micro-cutting. It affects the flow characteristics of cutting material, the deformation state of chip, the quality of the machined surface, and the amount of tool wear. Meanwhile, a stagnant region often appears in front of the tool surface when a negative rake tool is used to cut the plastic metal material, which would increase the actual negative rake angle. Therefore, based on the stagnant characteristics and the infinite shear strain approach, this paper constructs a critical negative rake angle model, and the orthogonal cutting experiment and the finite element model are used to verify the correctness of the model. By analyzing the deviation of the effective critical negative rake angle (theoretical value) and critical negative rake angle (experimental value), it can be known that the theoretical value is 0.36–4.15% larger than the experimental value, which indicates that the model considering the existence of stagnant region is closer to the actual critical negative rake angle. In addition, the relationship between the stagnant region (the deviation) and the multi-cutting factors can provide experimental basis of angle for solving the effective critical negative rake angle when the critical negative rake angle is known.

The effect of fiber orientation on tool wear in edge-trimming of carbon fiber reinforced plastics (CFRP) laminates

This paper investigates the impact of fiber orientation on tool wear when edge-trimming carbon fiber reinforced plastics (CFRP) with particular ply angles of 0°, 45°, 90°, and 135° with 6.35 mm diameter tungsten carbide end-mills at a constant feed of 0.3 m/min under two spindle speeds. The tool wear progress was examined qualitatively and quantitatively using the scanning electron microscopy and digital light microscopy at eight cutting distances between 0.25 and 8 m. The 45° plies resulted in extensive flank wear while the 90° plies yielded the worst edge radius rounding and worn area regardless of the rotational speed. Edge rounding is related to aggressive 2-body abrasion by the broken carbon fibers interacting with the cutting edge. The 0° ply angle has the least amount of tool wear due to the minimal interactions between the carbon fibers and cutting edge with the delamination in the chip formation.

COMPLEXITY-BASED ANALYSIS OF THE RELATION BETWEEN TOOL WEAR AND MACHINE VIBRATION IN TURNING OPERATION

Tool wear is an important issue that happens in all machining operations when the tool exerts forces on the workpiece. Therefore, engineers should choose the optimum values for machining parameters and conditions to reduce the amount of tool wear and increase its life. Machine vibration is one of the factors that highly affects tool wear. Since both tool wear and machine vibration signal have complex structures, in this research we employ fractal theory to find out their relation. In this paper, we analyze the relation between tool wear and machine vibration signal in different experiments where the depth of cut, feed rate and spindle speed change. The obtained results showed that tool wear and machine vibration signal are related to each other in case of variations of depth of cut and feed rate in different experiments, where both fractal structures get more complex by the increment of these machining parameters. The obtained method of analysis in this research can be potentially applied to other machining operations in order to link the machine vibration to the structure of tool wear.