Stages Of Tool Wear Research Articles

Survival life analysis applied to tool life estimation with variable cutting conditions when machining titanium metal matrix composites (Ti-MMCs)

A survival analysis methodology is employed through a novel approach to model the progressive states of tool wear under different cutting conditions during machining of titanium metal matrix composites (Ti-MMCs). A proportional hazards model (PHM) with a Weilbull baseline is developed to estimate the reliability and hazard functions of the cutting inserts. A proper criterion is assigned to each state of tool wear and used to calculate the tool life at the end of each state. Accounting for the machining time and different stages of tool wear, in addition to the effect of cutting parameters, an accurate model is proposed. Investigating the results obtained for different states, it was shown that the evolution of the time-dependent phenomena, such as different tool wear mechanisms, throughout the whole machining process were also reflected in the model. The accuracy and reliability of the predicted tool lives were experimentally validated. The results showed that the model gives very good estimates of tool life and the critical points at which changes of states take place.

Tool Wear Monitoring for Ultrasonic Metal Welding of Lithium-Ion Batteries

This paper presents a tool wear monitoring framework for ultrasonic metal welding which has been used for lithium-ion battery manufacturing. Tool wear has a significant impact on joining quality. In addition, tool replacement, including horns and anvils, constitutes an important part of production costs. Therefore, a tool condition monitoring (TCM) system is highly desirable for ultrasonic metal welding. However, it is very challenging to develop a TCM system due to the complexity of tool surface geometry and a lack of thorough understanding on the wear mechanism. Here, we first characterize tool wear progression by comparing surface measurements obtained at different stages of tool wear, and then develop a monitoring algorithm using a quadratic classifier and features that are extracted from space and frequency domains of cross-sectional profiles on tool surfaces. The developed algorithm is validated using tool measurement data from a battery plant.

Investigation on the influence of tool wear upon chip morphology in end milling titanium alloy Ti6Al4V

Titanium alloys are widely utilized in aerospace, automotive, biomedical and chemical engineering, etc., thanks to their excellent combination of high-specific strength, fracture, corrosion resistance characteristics, etc. However, titanium alloys are difficult-to-machine materials. Tool wear is one of the bottlenecks restricting their machining efficiency. A systematic study on the relationships among tool wear, chip morphology, and cutting vibration is inadequate. In this study, chip morphology and cutting vibration characteristics under different tool wear stages are examined using optical microscope, SEM, and vibration test system. The mechanism of tool wear in end milling titanium alloy is also investigated. Results indicate that with the progression of tool wear, the chip segment degree becomes more and more serious. The mechanism for this phenomenon is probed. Tool wear progression enlarges the cutting vibration which causes the friction force on tool/chip interfaces to increase, and this aggravates chip edge wear accordingly. On the contrary, the increase of chip segment degree induces the progression of cutting vibration and tool wear. Therefore, the aim of the present research is to investigate the sophisticated relationship. This will benefit for improving cutting efficiency and guaranteeing machining quality in end milling titanium alloy.

Monitoring the tool wear, surface roughness and chip formation occurrences using multiple sensors in turning

Tool wear, chip formation and surface roughness of workpiece under different cutting conditions have been investigated in machining using acoustic emission (AE) and vibration signature in turning. The investigation has shown that the AE and vibration components can effectively respond to the different occurrences in turning including tool wear and surface roughness. The AE has shown a very significant response to the tool wear progression whereas the resultant vibration (V) represented the surface roughness in turning. The vibration components Vx, Vy and Vz described the chip formation type and are found to have the most significant response to the change of feed, depth of cut and cutting speed respectively. The amplitude of vibration components, Vx, Vy and Vz increased with the increase of feed rate, depth of cut and cutting speed respectively. Even though the frequency of different signal components fluctuated at the different stages of tool wear and at different cutting conditions, the frequency of vibration components was always within a band of 98–40kHz, and the AE has varied between 51kHz and 620kHz.

The Study Wear Resistance of the Modified Surface of the Cutting Tool

One of the effective ways to improve the efficiency of cutting tools is the use of innovative types of multilayer coatings combining friction properties and high wear resistance. The object of study of this work was to investigate the influence of the composition of sublayer with anti-friction properties like component functional multilayer coatings on tool life. The data obtained in these studies were the basis for the development of the concept of functional multilayer coatings for cutting tools with programmable properties, providing an opportunity for each coating layer to perform a required function at a certain stage of tool wear. As used HSS substrate which is preliminarily subjected to ion nitriding by glow discharge and in addition alloyed gas-metal ions before coating deposition. The final step involved coating deposition process TiCrN using filtered cathodic vacuum arc deposition (FCVAD). Studies have shown that mixing the antifriction alloys which are widely used to improve friction properties allow to increase the tool life is not more than two times. This method of the tool life increase by reducing the shear strength of boundary adhesion between the tool and the work material does not seem to be the most effective for multilayered coatings under analysis, as for almost all studied anti-friction materials, the adhesion between the coating and the modified surface was rather low. This precludes their practical application due to technological reasons. Implantation the chemical elements can achieve much better results. Elements such as indium, silver and nitrogen increase tool life in 2 - 3 times for different cutting conditions (using dry cutting or cutting with cutting fluid). The obtained results can be considered as the most promising. Indium and silver are interactive with respect to Fe and may be used as lubricants in metal and promote a crushed chip forming at cutting using coating under the study. Ion surface modification of the tool with other studied elements demonstrates unstable or negative results that reduction in tool life or inability to provide good adhesion between the coating and substrate.

Barkhausen Noise Emission of Surfaces Produced by Hard Milling Process

This paper deals with influence of tool wear on surface integrity after hard turning expressed mainly through the Barkhausen noise responses. Grinding operations can be sometimes replaced by hard machining (hard turning and milling). Chip separation in hard turning differs from mechanism of chip separation during grinding. For this reason surface integrity expressed in variable terms differs. Surface integrity can be expressed in such term as surface roughness, shape deviations as well as characteristics such as residual stresses, structure transformations, and microhardness alteration. Being so, it can be beneficial to apply the suitable nondestructive surface testing techniques to obtain information about surface integrity expressed in complexity of this term. Nowadays, Barkhausen noise technique is widely used in a variety of industrial applications. This technique is sensitive to stress state as well as microstructure features. For this reason, Barkhausen noise emission is used in this study to reveal magnetic and stress anisotropy developed in a certain stage of tool wear. The paper also discusses very high BN responses associated with the specific aspects of produced surfaces.

Wear of diamond grinding wheel in ultrasonic vibration-assisted grinding of silicon carbide

It is recognized that grinding efficiency and ground surface quality are determined by grinding wheel performance. Additionally, the investigation on wear behavior is essential for evaluating the grinding wheel performance. There is a lack of research on the tool wear behavior during ultrasonic vibration-assisted grinding (UAG), whose grain motion trajectory differs from that in conventional grinding (CG). In the present work, CG and UAG tests of silicon carbide (SiC) were conducted in order to investigate the effects of ultrasonic vibration on the tool wear through tracking observation of grains. Meanwhile, the grinding forces and ground surface roughness correlated to the tool wear stages were studied. The results demonstrated that the main wear types during UAG were micro-fracture and macro-fracture which caused the wheel sharpening, while during CG, the main wear type was attritious wear that made the wheel blunt. As a result, UAG obtained lower and more stable grinding forces while slightly rougher ground surface in comparison with CG.

The effectiveness of palm oil methyl ester as lubricant additive in milling and four-ball tests

This paper examines the effectiveness of palm oil methyl ester (POME) as lubricant additive using the four-ball and milling tests. In milling 55 HRC-stavax® (modified AISI 420 stainless steel) under flood lubrication, three stages of tool wear occurred: 1) initial wear by delamination, attrition and abrasion; 2) cracking at the substrate, 3) followed by formation of individual surface fracture at the cracks which would then enlarge and coalesce to form a large fracture surface. Mineral oil sprayed in mist form was more effective in reducing the coating delamination and delaying the occurrence of cracking and fracture. The effectiveness of mineral oil in suppressing these wear modes could be enhanced by the presence of POME. The mechanism by which the POME suppressed these wear modes could be explained by the results obtained in the four-ball tests which showed that the presence of POME as additive in the mineral oil reduced the friction coefficient, severity of welding and increased the critical load for welding to occur.

A MIXED TIME-/CONDITION-BASED PRECOGNITIVE MAINTENANCE FRAMEWORK FOR ZERO-BREAKDOWN INDUSTRIAL SYSTEMS

Forecasting of process outages for reducing downtime and machine scrap parts have been actively pursued in the manufacturing industries to ensure that maintenance is carried out only when required. In this paper, we propose a precognitive maintenance framework based on mixed timeand condition-based models to predict both wear and degradation stage of realistic engineering systems. The decision-making framework performs stage classification using support vector machines and wear estimation using time-based autoregressive moving average with exogenous inputs models. Our proposed framework is supported by mathematical rigour, and its effectiveness is evaluated with experimental results on a high-speed industrial computer numerical control milling machine for tool wear stage identification and wear estimation.

Tool Wear Prediction Based on Fuzzy Cluster Analysis

There are several stages of tool wear in turning process. The theory and the algorithm of the fuzzy cluster analysis (FCA) are applied in the research of the CNC turning tool wear State.We collect of the force signals and vibration signals at each stage. Using wavelet filtering and power spectrum methods, typical parameters changes are detected. We extract the signal feature for fuzzy clustering. Experimental results show that the tool wear prediction is achieved in turning by using this pattern recognition method.

RETRACTED: Tool Wear Intelligence Measure in Cutting Process Based on HMM

RETRACTED PAPER: A method of tool wear intelligence measure based on Discrete Hidden Markov Models (DHMM) is proposed to monitor tool wear and to predict tool failure. FFT features are first extracted from the vibration signal and cutting force in cutting process, and then FFT vectors are presorted and converted into integers by SOM. Finally, these codes are introduced to DHMM for machine learning and 3 models for different tool wear stage are built up. Pattern of HMM is recognised by calculating probability. The results of tool wear intelligence measure and pattern recognition of tool wear experiments show that the method is effective.

Fuzzy Clustering and Visualization Analysis of Tool Wear Status Recognition

One of the biggest problems in manufacturing is the failure of machine tools which due to loss of surface material in cutting operations. Therefore, an effective diagnosis mechanism is necessary for the tool condition monitoring so that production loss and downtime can be avoided. For this, signals acquired from vibration and force sensors were processed to monitor the status of the tool wear. This paper explores the use of Frequency Band Energy (FBE) analysis and Fuzzy Clustering (FC) techniques for tool wear status recognition in metal cutting. In the first stage of the proposed scheme, FBE based on wavelet packets decomposition is performed on cutting vibration and force signals measured on the CNC machine tools. The different stages of tool wear can enhance or inhibit the effect of different frequency components. It made the extracted features sensitive to tool wear. The recognition method for tool wear status was studied through Fuzzy C-means clustering system. In order to examine the performance of clustering results, Visualization of clustering is mapped by principal component analysis (PCA). Experimental results have shown that this approach is a superior and effective method for tool wear status recognition.

Cutting force and its frequency spectrum characteristics in high speed milling of titanium alloy with a polycrystalline diamond tool

In this paper, a series of experiments were performed by high speed milling of Ti-6.5Al-2Zr-1Mo-1V (TA15) by use of polycrystalline diamond (PCD) tools. The characteristics of high speed machining (HSM) dynamic milling forces were investigated. The effects of the parameters of the process, i.e., cutting speed, feed per tooth, and depth of axial cut, on cutting forces were studied. The cutting force signals under different cutting speed conditions and different cutting tool wear stages were analyzed by frequency spectrum analysis. The trend and frequency domain aspects of the dynamic forces were evaluated and discussed. The results indicate that a characteristic frequency in cutting force power spectrum does in fact exist. The amplitudes increase with the increase of cutting speed and tool wear level, which could be applied to the monitoring of the cutting process.

Low-speed milling of stainless steel with TiAlN single-layer and TiAlN/AlCrN nano-multilayer coated carbide tools under different lubrication conditions

This paper evaluates the performance of TiAlN/AlCrN nano-multilayer coated, TiAlN single-layer coated and uncoated carbide tools in low-speed milling of STAVAX (modified 420 stainless steel) under flood and mist lubrication. Scanning electron microscope, energy dispersive X-ray analysis system and Raman spectroscopy were used to examine the tool wear and determine the type of oxide formed on the tool surface during machining. In machining STAVAX with a hardness of 40 HRC, the coated tools were subjected to delamination, attrition and abrasive wear throughout the duration of testing. During machining STAVAX with a hardness of 55 HRC, three distinct stages of tool wear occurred, (i) initial wear by delamination, attrition and abrasion, followed by (ii) cracking at the substrate and (iii) the formation of individual surface fracture at the cracks which would then enlarge and coalesce to form a large fracture surface. The TiAlN/AlCrN coated tool exhibited higher resistance against delamination and abrasive wear than the TiAlN coated tool. The cracking resistance and hardness of the coating, and oxidation of the coating during machining appeared to have significant influences on the resistance of the tool against these wear mechanisms. A longer cutting distance was required to cause TiAlN/AlCrN coated tool to crack and fracture. This was due to the substrate receiving greater protection against cracking and fracture as a result of the coating being removed at a slower pace by abrasion and delamination. The likeliness of the uncoated tool to chip, crack and fracture, and the severity of abrasion increased with an increase in the hardness of the workpiece. Small quantity of mineral oil sprayed in mist form was effective in reducing the severity of delamination and abrasive wear, and delaying the occurrence of cracking, fracture and chipping. The influence of the ductility of the workpiece, tool wear and the lubricants on the surface finish are also discussed. © 2010 Elsevier B.V.

Frequency Spectrum Analysis on Cutting Forces in Cutting Process

Cutting tool wear has relation with the cutting forces. By way of signal processing, the power spectrums of cutting forces in different tool wear stages are analyzed in the present paper. It is proved that several characteristic frequencies exist within a wide frequency range during the cutting process as long as cutting process parameters keep constant. The power value of the characteristic frequency increase with the increase of tool wear. Thus, the tool wear could be predicted by the changes of characteristic frequencies and their power values.

Wear progression of carbide tool in low-speed end milling of stainless steel

A study was undertaken to investigate the wear of PVD-coated carbide and uncoated carbide tools during milling of STAVAX (modified AISI 420 stainless steel) at low speeds. No significant change in the tool wear was observed when the cutting speed was increased from 25 to 50 m/min. It was found that increasing the hardness of the workpiece from 35 to 55 HRC caused a marked increase in the flank wear and a change in the dominant wear mechanism. In machining STAVAX with a hardness of 35 and 40 HRC, the coated tool was predominantly subjected to abrasive wear throughout the duration of testing. During machining STAVAX with a hardness of 55 HRC with the coated tool, three distinct stages of tool wear occurred, (i) initial wear by abrasion, followed by (ii) cracking and chipping, and (iii) the formation of individual surface fracture at the cracks which would then enlarge and coalesce to form a large fracture surface. The coated tool showed much higher fracture resistance than the uncoated tool. The high fracture resistance exhibited by the coated tool could be attributed to the effectiveness of the coating in preventing the formation of cracks which would act as preferential sites for fracture to take place. The experimental results also show that coating prevents edge chipping and enhances the abrasive wear resistance of the tool. Both the ductility of the workpiece and the tool wear appeared to have influences on the surface finish of the workpiece. It was found that the cutting fluid was effective in preventing catastrophic failure of the tool.

Intelligent Recognition of End Milling Conditions Based on Cutting Force Model (Development of Monitoring Method without Any Databases)

An intelligent method is proposed to recognize various end milling conditions by comparing simulated and measured cutting forces. Static stiffness of the mechanical structure is identified by utilizing the measured cutting forces, and it is shown that the static deformation of the structure can be taken into account for accurate calculation of uncut chip thickness in the end milling process. A cutting force equation is developed with considering cutting edge roundness, i.e. tool wear, and a milling force model is constructed. Various parameters in the model are identified so that the simulated forces fit best with the measured forces. Edge force component, tool setting angle, specific cutting force resistance, etc. are identified or recognized as the model parameters, which contain rich information about the end milling process. End milling experiments are carried out at various stages of tool wear, and the results show that the proposed index for the tool wear, i.e. the identified edge force component divided by the specific cutting force resistance, has good correlation with the measured tool wear. It is expected that the end milling conditions such as the tool wear, the static stiffness of the structure, the tool setting angle and the specific cutting force resistance can be recognized intelligently without any data bases by the present method.

Impact of ion modification of HSS surfaces on the wear resistance of cutting tools with surface engineered coatings

The paper considers some ways to improve surface engineered coatings for cutting tools. These coatings were formed by two stages: diffusion saturation with nitrogen (ion nitriding) and application of the (Ti, Cr)N hard coating by means of the cathode arc plasma deposition process (CAPDP). The coating includes also an additional ion alloyed layer applied to the previously nitrided surface of HSS. Such multilayered coating makes it possible to significantly increase (in 2.1–2.4 times) the wear resistance of a cutting tool by extending the stage of normal wear. There were studied 16 chemical elements implanted into the base surface and those of four antifrictional materials effecting on the life of a HSS cutter with a surface engineered coating. It was shown that leading positions in wear resistance are taken by coatings with a modified sublayer of elements with high antifrictional properties. A compromise between the high wear resistance and reliability of a coating, which is characterized by a high adhesion to the substrate, is observed in the multilayered coating that contains a sublayer enriched with indium. Indium is present in the sublayer both in metal and bound states (In–N). The positive effect of indium on wear resistance appears to be tied with two types of phenomena developing on the friction surface. Acting as a liquid lubricant, indium in metal state leads to reducing the friction coefficient. At the same time, when heated at cutting, indium is partly oxidized with developing of oxygen-containing phases protecting the surface when passing from the normal stage of tool wear to the avalanche-like one. This is beneficial for prolongation the stage of normal friction, considerably enhancing the tool life.

Intelligent tool wear identification based on optical scattering image and hybrid artificial intelligence techniques

Tool wear monitoring is crucial for an automated machining system to maintain consistent quality of machined parts and prevent damage to the parts during the machining operation. A vision-based approach is presented for tool wear identification in finish turning using an adaptive resonance theory (ART2) neural network embedded with fuzzy classifiers. The proposed approach is established upon the fact that the optical scattering image of a turned surface is related to the wear of the cutting tool. By applying the technique of the ART2 neural network embedded with fuzzy classifiers, the state of wear of the turning tool is determined from captured images obtained by laser scattering from the machined surfaces of the workpiece. This approach is not unlike the visual inspection of the surface of a machined workpiece to determine the state of wear of a cutting tool by an expert machinist. However, experimental results indicate that the conventional technique of measuring surface finish does not give values that correlate well with tool wear. On the other hand, the laser scattering image provides a good indication of the tool wear as it is not readily affected by buildup edge or cold-welded material, scratches and other disruptive defects on the turned surface as the tool wears. In this paper, the theory on the laser scattering image and the principle of tool wear identification are described. Based on the scattering images, the proposed approach can correctly identify the condition of ‘significant wear’ prior to the rapid tool wear stage for the cutting tool.

Tool wear and chatter detection using the coherence function of two crossed accelerations

Tool wear and chatter have been found to be the main causes of rejects in the machining of super alloys. A novel detection technique to identify both tool wear and chatter in turning a nickel-based super alloy is introduced. It uses the coherence function between two crossed accelerations from the bending vibration of the tool shank. The value of the coherence function at the chatter frequency reaches unity at the onset of chatter. Its values at the first natural frequencies of the tool shank approach unity in the severe tool wear stage. The results are interpreted using the analysis of the coherence function for a single input-two output model. The advantage of using this method is that the thresholds for detecting severe tool wear and chatter can be easily set, since values of coherence function are normalized to a range of between zero and unity, and are also not so susceptible to changing cutting conditions, because the value of the coherence function is close to unity at the onset of chatter and severe tool wear.