Wear Model Research Articles

Tool Wear Prediction in Machining of Aluminum Matrix Composites with the Use of Machine Learning Models

This paper discusses the diagnostic models of tool wear during face milling of Aluminum Matrix Composite (AMC), classified as a difficult-to-cut material. Prediction and classification models were considered. The models were based on one-dimensional simple regression or on multidimensional regression trees, random forest, nearest neighbor and multilayer perceptron neural networks. Measures of diagnostic signals obtained from measurements of cutting forces and vibration accelerations of the workpiece were used. The study demonstrated that multidimensional models outperformed one-dimensional models in terms of prediction accuracy and classification performance. Specifically, multidimensional predictive models exhibited lower maximum and average absolute prediction errors (0.036 mm vs. 0.050 mm and 0.026 mm vs. 0.045 mm, respectively), and classification models recorded fewer Type I and Type II errors. Despite the increased complexity, the higher predictive accuracy (up to 0.97) achieved with multidimensional models was shown to be suitable for industrial applications. However, simpler one-dimensional models offered the ad-vantage of greater reliability in signal acquisition and processing. It was also highlighted that the advantage of simple models from a practical point of view is the reduced complexity and consequent greater reliability of the system for acquiring and processing diagnostic signals.

Unveiling the temperature effect on reciprocating sliding wear mechanism of a TA15 alloy fabricated by wire-arc additive manufacturing

TA15 alloy has been widely used for load-bearing structural components in aircraft engines and subjected to sliding wear at different temperatures in operation. Therefore, the temperature effect on sliding wear mechanism of a TA15 alloy fabricated by wire-arc additive manufacturing was investigated in detail. Results showed that the coefficient of friction and wear volume exhibited multi-stage changes with increasing temperature. As the temperature increased, the crack morphology changed from randomly distributed pores to delamination cracks. The classic oxidative wear model collapsed at high temperatures. We modify the model by introducing dissipated energy and delamination coefficient to accurately predict the wear volume of TA15 alloy.

Frictional Abrasion of Rubber: Transition from Sliding to Rolling

ABSTRACT To develop applicable friction and wear models on tire scale, reliable test data are required. Consequently, friction tests on block level are requested because the distribution of contact pressure as well as slip velocity is nearly homogeneous at the contact surface of the sliding rubber block. However, wear mechanism and energy intensity levels of sliding rubber blocks and rolling rubber wheels or tires differ significantly. Consequently, linking both sliding and rolling frictional abrasion is required; thus, a wear model for rubber material is introduced to consider both deformation slip and sliding. The model input for sliding friction and resulting wear rate is derived from linear friction test experiments using sliding rubber blocks at different loading. A unique and sophisticated re-mesh algorithm ensures proper mesh modification due to abrasion of the structure. A wear energy evolution approach is developed to consider low abrasion with small sliding distances to predict wear at rolling rubber wheels. The simulation framework of abrasion modeling is successfully validated using laboratory abrasion tests.

Modeling and Measurement of Tool Wear During Angular Positioning of a Round Cutting Insert of a Toroidal Milling Tool for Multi-Axis Milling

The aim of this study was to develop a concept for an angular positioning method for a round cutting insert in a torus cutter body dedicated to the multi-axis milling process under high-speed machining cutting conditions. The method concept is based on a developed wear model using a non-linear estimation method adopting a quasi-linear function. In addition, a tool life model was developed, taking into account the cutting blade work angle parameter, the laser marking method for the round cutting insert, and a wear measurement methodology. The developed tool wear model provides an accuracy of 90% in predicting the flank wear of the cutting blade. The developed procedure for angular positioning of the round cutting insert enables the entire cutting edge to be fully utilized, extending the total tool life. In addition, the measured largest defect values between the worn cutting edge and the nominal outline of the round cutting insert indicate the location of notching-type wear.

Modelling and theoretical research on transient lubrication and wear coupling behavior of main bearing during start-up of low-speed diesel engine

This study endeavors to establish a transient mixed lubrication model for time-varying wear of main bearings under dynamic loading conditions during the startup process. This model accounts for variations in oil film thickness attributable to deformation, wear profiles, and journal misalignment throughout the operational cycle. The evolution of main bearing lubrication characteristics during the startup process was analyzed, as well as the evolution of wear profiles and their effects on lubricating properties under different numbers of startups. The results indicate that as the number of startup cycles increases, the wear rate gradually levels off. With increasing startup times, there is a decrease in contact pressure and a slight reduction in oil film pressure, resulting in enhanced lubricating performance. Furthermore, the influence of startup duration on wear is significantly greater than that of radial clearance.

Research on tool wear and breakage state recognition of heavy milling 508III steel based on ResNet-CBAM

Milling water chamber head material 508 III steel belongs to extreme manufacturing, and the tool failure is very serious in the process of machining. How to monitor and identify the tool wear damage state in time and effectively is a key problem to be solved urgently. Identifying chip morphology changes under machining conditions plays a very important role in characterizing tool wear and breakage. Tool wear has an important influence on the chip morphology during the process of milling 508III steel, and changes in chip morphology can also reflect the tool wear and breakage state. Therefore, this paper takes the chip morphology image as an important feature for tool wear and breakage recognition, and uses Gaussian fuzzy estimation morphology method to preprocess the chip morphology image. Build a ResNet network combined by convolutional block attention module (ResNet-CBAM) tool wear and breakage recognition model, and explore the selection of the model backbone network, determination of the ResNet backbone network depth, and fusion methods of different attention mechanisms. Through the ablation experiment and visual analysis of the attention mechanism module, it is verified that the ResNet-CBAM model proposed in this paper has an accuracy rate of 96.67% in tool wear and breakage state recognition, especially in the stage of severe tool wear and breakage. This study realizes the prediction and early warning of tool life, and provides effective guarantee for the efficient cutting of large parts of high-end equipment and the stable operation of manufacturing system.

Simulation and experimental verification of the orthogonal friction continuous wear of PTFE-Kevlar fabric liner

Woven fabric liners, which are customizable and maintenance-free, have extensive applications in self-lubricating spherical bearings. However, owing to the orthogonal anisotropy and non-homogeneous characteristics, their frictional and wear behaviors are complex. Currently, average performance testing is primarily based on long-term macroscopic wear experiments. However, unobservable parameters such as mesoscopic stress and pressure distribution in liners are bottlenecks in the experimental exploration of wear sources and mechanisms. Therefore, an innovative strategy for modeling orthogonal friction and continuous wear in non-homogeneous liners is presented. This approach has the potential to overcome experimental limitations and significantly expedite liner design and cost-effective validation. The initial step involves establishing a mesoscopic voxel-based planar model of the liner that maintains the topological relationship during wear processes. This is achieved by introducing a circular voxel mesh and spatial transformation methods. Based on orthogonal friction and wear assumptions, separate constitutive models for orthogonal friction and wear are developed. Using the CETR UMT-3 friction and wear testing machine, GCr15 is selected as the counterface material, the pin disc wear method is adopted to conduct sliding test on PTFE and Kevlar fibers, and the required wear constitutive parameters are fitted. Furthermore, incremental equations for the total wear are derived. An element wear fusion strategy is introduced. This approach leads to the development of a continuous wear algorithm for liners and subsequently to the establishment of a voxel-based finite element model with continuous wear capability in the form of a circular voxel grid. This method transcends experimental methods and allows for the determination of the mesoscopic contact pressure, stress distribution, and variations in the contact material composition patterns of liner. The accuracy of the average macroscopic wear prediction is validated experimentally. This method has the potential for practical applications in bearing design.

Wheel wear of mountain metro vehicles with complex line conditions

Purpose Mountain metro vehicles have unique wheel wear characteristics due to the complex flat and longitudinal lines. With a combination of flat and longitudinal curved tracks, the traction and braking conditions are more frequent in mountain metro vehicles. This paper aims to analyze the wheel wear characteristics of mountain metro vehicles in complex flat and longitudinal lines. Design/methodology/approach A dynamic model of the mountain metro vehicle and a wear model are established to analyze the dynamic and wheel wear characteristics of mountain metro vehicles. The wheel wear law of mountain metro vehicles under complex track conditions is analyzed, and the suppression measure based on variable stiffness rotary arm nodes of mountain metro vehicles is proposed. Findings The results showed that the maximum wheel wear depth without considering the ramp track and considering the ramp track are 3.283 mm and 3.717 mm, respectively; the maximum wheel wear depth increases by 13.2%. Wheel wear can be effectively suppressed by the variable stiffness rotary arm model, and the maximum wear depth of the wheel profile is 3.316 mm, which is reduced by 10.79% compared with the constant stiffness model. Originality/value A dynamic model of a mountain metro vehicle is established, and the metro vehicle wheel wear under the large ramps under the traction and braking conditions is analyzed, and the metro vehicle wheel wear suppression measure based on variable stiffness rotary arm nodes is proposed. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2024-0247

Numerical evaluation of wear parameters using meta-models

AbstractWear parameters identified by linear friction tester (LFT) experiments overestimate the wear mass loss when applied on a laboratory abrasion & skid tester 100 (LAT100) simulation. On the other hand, the identification of wear parameters directly from the LAT100 experiment can be challenging since variables such as the contact area and the slip velocity are not measured experimentally and need to be assumed. To improve the identification process, numerical calibration is used as a more suitable approach. This approach relies on meta-models as a target function for minimization. The meta-models are generated using a sample of wear parameters applied to an LAT100 finite element modeling (FEM) to calculate the corresponding wear mass.. In this model, a transport velocity is defined for the rolling simulation, and an arbitrary lagrangian–eulerian (ALE) adaptive meshing approach is adopted for the wear modeling. For the wear model, a combination of archard’s wear model and schallamach’s abrasion law is used. This model contains a pair of wear parameters to be identified. The ALE adaptive meshing technique moves the nodes independently of the material. Since the mesh topology remains the same, failure of the simulation occurs if the wear volume loss exceeds that of the element. Meta-models are created to extend wear modeling beyond this failure. Once the meta-models are created, they are used as a target function for the minimization algorithm. The minimization algorithm aims to find the optimal wear parameters by minimizing the difference between experimentally observed and numerically produced wear mass loss. The minimization algorithm inputs a set of wear parameters into the meta-models which in turn yield a prediction of the wear mass loss. The process is carried out until an optimum parameter set is identified. Such an approach has a lower accuracy if the parameters are identified directly from the experiment using assumptions regarding the contact shear stress and the sliding velocity. Nonetheless, the main advantage of parameters identified using the meta-model approach is the usability of these parameters in an LAT100 model.

A Contact Mechanics Model for Surface Wear Prediction of Parallel-Axis Polymer Gears.

As surface wear is one of the major failure mechanisms in many applications that include polymer gears, lifetime prediction of polymer gears often requires time-consuming and expensive experimental testing. This study introduces a contact mechanics model for the surface wear prediction of polymer gears. The developed model, which is based on an iterative numerical procedure, employs a boundary element method (BEM) in conjunction with Archard's wear equation to predict wear depth on contacting tooth surfaces. The wear coefficients, necessary for the model development, have been determined experimentally for Polyoxymethylene (POM) and Polyvinylidene fluoride (PVDF) polymer gear samples by employing an abrasive wear model by the VDI 2736 guidelines for polymer gear design. To fully describe the complex changes in contact topography as the gears wear, the prediction model employs Winkler's surface formulation used for the computation of the contact pressure distribution and Weber's model for the computation of wear-induced changes in stiffness components as well as the alterations in the load-sharing factors with corresponding effects on the normal load distribution. The developed contact mechanics model has been validated through experimental testing of steel/polymer engagements after an arbitrary number of load cycles. Based on the comparison of the simulated and experimental results, it can be concluded that the developed model can be used to predict the surface wear of polymer gears, therefore reducing the need to perform experimental testing. One of the major benefits of the developed model is the possibility of assessing and visualizing the numerous contact parameters that simultaneously affect the wear behavior, which can be used to determine the wear patterns of contacting tooth surfaces after a certain number of load cycles, i.e., different lifetime stages of polymer gears.

Numerical modelling and experimental investigations to predict the tool wear of copper electrodes during µ-EDM process

The micro electrical discharge machining (µ-EDM) process is one of the most widely used techniques to produce miniaturized components in micro-electro mechanical system (MEMS) applications due to its inherent advantages. This work investigates the wear phenomena and the morphology of the copper electrodes during the micro-die sinking process. A numerical model of a single spark is developed assuming the Gaussian distribution of heat flux to estimate the crater dimensions formed in the copper tool electrode (tool wear) used as a result of electric discharge. The crater dimension attained from the ABAQUS finite element model is validated with experimental results using a single spark test setup. Moreover, the effect of input parameters namely capacitance and voltage on the electrode wear rate and surface roughness is also studied. The crater dimensions from the single discharge study are used to formulate the wear model for different possibilities of crater distribution, such as non-overlapping craters, craters with less than 30 % overlap, and 50 % overlap. The electrode wear rate (EWR) also displayed a decline from 20.4 % to 11.6 % and further to 8 % when the overlap was permitted up to 30 % and up to 50 % for the wear model respectively. The developed model results are further compared with experimental results in terms of the electrode wear rate and depth of erosion and the deviations are found to be 20.33 % and 20.55 % respectively

Reliability analysis of cutting tools using transformed inverse Gaussian process-based wear modelling considering parameter dependence

Reliability analysis is crucial for ensuring the performability of the desired function. The cutting tool performs the machining operation at varied conditions to manufacture diverse products. During operation, the tool degrades stochastically in the form of wear. To avoid the unfavourable consequences occurring from severe tool wear, appropriate formulation of the tool reliability, considering threshold degradation level as the failure criterion, is crucial. However, the degradation of the tool during machining is impacted by the current state of the tool wear and operating conditions. Considering these, the present study proposes a state-dependent transformed inverse Gaussian (TIG) process incorporating the effects of operating conditions to develop the tool wear model. In order to evaluate the proposed method, tool wear experiments are conducted at different operating conditions following the Taguchi orthogonal array experimental design. The experimental data are utilised to estimate the parameters of the developed model using the Bayesian approach. Following the parameter estimation, tool reliability is evaluated under varying operating conditions. The comparison of the estimated median time to failure of the tools with the failure time observed in the validation experiments ensures the effectiveness of the proposed model. The proposed approach has the potential to estimate the reliability of the industrial products subjected to state-dependent degradation under varied operating conditions.

Predictive modeling of abrasive wear in in-situ TiC reinforced ZA37 alloy: A machine learning approach

Abrasive wear rates are of significant interest in various industrial applications where materials are subjected to severe wear conditions. The study analyzed high-stress abrasive wear rates on the novel in-situ TiC reinforced ZA37 composites. The inclusion of in-situ TiC reinforcement in ZA37 alloy has shown potential for enhancing wear resistance. The impact of tribological test parameters on the abrasive wear response was analyzed using response surface methodology (RSM). Using tribological data, various machine-learning algorithms were trained to predict the wear behaviours of the developed composites. The performance measurements show that the machine learning models accurately predicted the abrasive wear response of test samples. Our findings suggest that machine learning can revolutionize tribology, paving the way for tribo-informatics.

Wheel-rail wear characteristics of a modern tram passing curves with small radius

The wheel-rail wear was predicted for modern trams with independently rotating wheelset running on a groove-shaped rail. The tram vehicle-track coupled dynamics model, considering the wheel-rail multi-point contact, was developed using software UM to evaluate the dynamic responses of the vehicle and track. Hertz contact theory, the FastSim algorithm, and Archard material wear model were used to solve the normal contact stress, tangential contact stress, and wheel-ail wear, respectively. The wheel and rail profiles were updated when the wear depth reached to 0.1 mm. In calculation, the wheel and rail wear was calculated and analyzed separately. The results of groove rail and independently rotating wheelset wear predicted by this model coincided with relevant literature, which proved the effectiveness of this model. The wheel and rail wear characteristics of modern trams passing through curved tracks with small radii and the influence of wheel-rail friction coefficient on wheel and rail wear were calculated and analyzed using this model. The results show that the wheel and rail wear on the circular curve and the rear transition curve is more intense. The wheel wear is the most intense on circular curve while the rail wear is on the rear transition curve. The wear of inner and outer rails and wheels of wheelset one increases with the increase of wheel-rail friction coefficient while the wear of inner and outer wheels of wheelset three have no obvious change. The wear of the inner and outer rails is the most intense at the gauge corner position while is the lightest at the guard rail. The wear of wheelset one is more intense than that of wheelset three and the inner wheel wear is more intense than that of the outer wheel. The present analysis contributes to improve the life of tram wheel and rail and reduce the frequency of wheel-rail maintenance during operation.

Analysis of Friction and Wear Properties of Friction Ring Materials for Friction Rings under Mixed Lubrication

Aiming at the problem of mechanical seal failure due to serious wear and tear in operation, the numerical model of the thermal–solid coupling wear of the seal ring is established by taking the friction sub-material as the research object, and the hardness, wear coefficient, and friction coefficient of different soft-ring materials are obtained by a test to verify the accuracy of the numerical model of wear. Additionally, the temperature field and deformation field of the seal ring of different materials are calculated, and the effects of the material parameters, such as elasticity modulus and thermal conductivity, on the temperature, relative deformation, and axial deformation trend are reported. The wear relation of the mechanical seal was optimized, and the correction coefficients of several materials were calculated. The results show the following: the main wear of the seal ring is due to adhesive wear leading to particle shedding and extrusion, adhesive wear causes material transfer, which alters the composition of the worn surface.in turn leading to cratering, which also causes the wear of the seal ring; the friction performance is better when the soft-ring material is graphite (C); the temperature, as well as the deformation, is smaller when the soft-ring material is silicon carbide (SIC); the correction coefficients for the life of SIC are calculated to be 0.23, for C, to be 0.14, and for stainless steel (Ss), to be 0.31, and the corrected equations can more accurately predict the corresponding material. The corrected equation can more accurately predict the service life of the corresponding material.

Study of the Differential Wear of Wheel Profiles on Motor Cars and Trailers of High-Speed Trains

As the operation speed of China’s high-speed trains continues to increase, a variety of complex wheel wear problems continue to emerge. Many line tests show that the differential wheel wear of the motor car and trailer car is obvious. The aim of this paper is to explore the differential wear mechanism of motor cars and trailers and their effect on dynamic performance. Firstly, this paper established a high-speed train model, which consists of two motor cars and two trailers. Then the causes of differential wear of the high-speed train from the perspective of wheel-rail contact and wheel wear were analyzed, and the Jendel wear model was used for wheel wear prediction. The wear model was verified through measured wheel wear data. Lastly, the dynamic performance of the differential wear of the high-speed train was analyzed. The results showed that the different distribution of the adhesive sliding zone in the contact patch, the different wheel-rail normal force, and tangential forces are the reasons for the differential wear. The established dynamic model and wear model can effectively predict the differential wear of the motor cars and trailer, and the maximum wear depths of the motor car and the trailer wheel were 0.886 mm and 0.721 mm. This verified the validity of the simulation model. When wheel differential wear occurs, the overall dynamic performance of the trailer is superior to that of the motor cars.

Mechanism analysis and prediction of bull-nose cutter wear in multi-axis milling of Ti6Al4V with TiAlN coated inserts

Cutter wear is an unavoidable issue during the milling of difficult-to-machine materials such as Ti6Al4V, which severely affects cutting performance and surface quality. Especially in multi-axis milling, the complex and irregular contact area between cutter and workpiece increases the difficulty of wear prediction. This paper proposes a flank wear prediction model of bull-nose cutter in the multi-axis milling process of Ti6Al4V with TiAlN coated inserts. The cutter workpiece engagement (CWE) zone is analyzed and the wear contact length of cutting edge is obtained, which reveals the uneven distribution characteristics of flank wear. After that, by analyzing the geometric profile properties of cutter wear in multi-axis milling, abrasive and adhesive wear, a flank wear prediction model that takes coating hardness and cutting temperature model into account is established. The proposed model is calibrated and validated by the multi-axis milling experiment of Ti6Al4V with TiAlN coated inserts. The results show that the novel wear model has high accuracy with an average percentage error of 12.76 % and can accurately and quickly predict flank wear in multi-axis milling of Ti6Al4V. Finally, the cutter wear mechanism and chip formation are analyzed, which show that the main wear mechanism is abrasive wear and adhesive wear, and there was no obvious oxidation wear.

The Construction of a Small-Caliber Barrel Wear Model and a Study of the Barrel Wear Rule

The wear of small-caliber barrels is one of the key factors affecting barrel life. Based on the Archard wear model, a high-temperature pin plate wear experiment was carried out, and wear models of chrome-plated layers and gun barrel materials were established. In addition, a finite element model of the interaction between the bullet and the barrel was established. The movement of the projectile along the barrel was simulated and analyzed, and the force distribution of the spatial geometry structure of the rifling was mastered through simulation. The wear law of the gun barrel along the axial direction was obtained based on the wear model of the chrome-plated layer and gun barrel material. A position 100 mm away from the barrel breech wears very fast; this position is where the cone of the bullet is engraved in the barrel. At the position 150–350 mm away from the barrel breech, the barrel bore wears even faster. The barrel chrome layer is mainly affected by the gunpowder impact and projectile engraving, which is consistent with the actual failure of the coating. When the distance to the barrel breech is 350 m, the wear becomes stable. Through an analysis of the diameter of the barrel, it was found that, when the diameter of the barrel exceeded 12.85 mm, the barrel reached the end of its life.

Study of fretting wear mechanisms of complete contacts

The Ti-6Al-4V fretting wear of complete contacts on a proving ring-like rig is investigated in this paper. Under this contact configuration, the Ti-6Al-4V alloy exhibited distinctive fretting wear behaviors. Especially in the continuous wear zones of the fretting specimen and pad, a paired continuous pit and peak were formed, respectively, and moved inward as the continuous wear zones expanded. To explain these fretting wear behaviors of the fretting configuration, a novel phenomenological fretting wear model is proposed in this paper. Additionally, due to the failure of the conventional FE method with a constant wear coefficient to simulate the fretting wear, a new local wear coefficient model, which is position-dependent and time-dependent fretting, is also proposed in this paper.

Evaluation of Mechanical Response during Nano Scale Contact for Contact Mechanics Model of Fatigue Wear

Evaluation of Mechanical Response during Nano Scale Contact for Contact Mechanics Model of Fatigue Wear