Wear Rate Model Research Articles

Advanced Machine Learning and Experimental Studies of Polypropylene Based Polyesters Tribological Composite Systems for Sustainable Recycling Automation and Digitalization

Advanced Machine Learning and Experimental Studies of Polypropylene Based Polyesters Tribological Composite Systems for Sustainable Recycling Automation and Digitalization

Enhancing Surface Quality and Tool Longevity in EDM of D2 Steel Using Copper Composite Tools

Hard material machining and die manufacture are the main applications for electrical discharge machining (EDM). For EDM, conventional electrode materials include graphite, steel, brass, pure copper, and alloys based on copper. Unfortunately, excessive tool wear is a common problem with these materials, which raises the cost of machining. In this investigation, hardened D2 steel was machined using a composite tool made of 90% copper and 10% silicon carbide. The powder metallurgy method was used to create the composite tool. Surface roughness (SR) and electrode wear rate (EWR) were compared to a number of process variables. For experimentation, a response surface methodology based on CCD design in design of experts software was used. SR and electrode wear rate models were created using the CCD approach. Utilizing analysis of variance, the most important factors and their effects on EWR and SR were determined. The lowest tool wear rate of 0.39 gm/min is achieved with a current of 5 Amps, a pulse duration of 100 µs, and a pulse interval of 10 µs with an R2 of 0.9957, which accounts for 99.57% of the variability, the tool wear rate model fits the data very well and obtained lowest surface roughness of 2.8 µm.

Wear prediction study considering TBM hob slip

Aiming at the problem of serious tool wear and untimely tool change affecting the construction efficiency when TBM is digging in microfractured tuff strata, the hob wear prediction study is carried out based on engineering examples. By analysing the rock-breaking mechanism of hob wear, a linear wear rate model and a life prediction model considering hob slip are derived based on the CSM model and the abrasive wear theory; the wear rate and the wear amount at the tool change point are further calculated by the prediction model in comparison with the measured value, and the furthest digging distance of the hob is calculated by the life prediction model. The results show that: the relative error between the measured average wear rate and the calculated linear wear rate considering the hob slip is 5.3%; the life prediction model predicts that the longest digging distance of the positive hob is 857 rings and the shortest distance is 198 rings. The results of the study are of guiding significance for the prediction of tool wear and the selection of the timing of opening and changing the hob in TBM tunneling.

A dual-stage wear rate model based on wear mechanisms analysis during cutting Inconel 718 with TiAlN coated tools

A dual-stage wear rate model based on wear mechanisms analysis during cutting Inconel 718 with TiAlN coated tools

Tyre and brake thermal management in NASCAR

The need to manage race car tyres is routine faire and several academic papers have already appeared on this topic. We contribute to this literature with refined tyre grip and wear-rate models. Less well known is a methodology for managing the thermal transients in the car's braking system. This knowledge gap is addressed with a physically-based disc-and-calliper brake-heating model. The parameters in each of the models are optimised against measurement data captured on an instrumented Generation 7 (Gen 7) NASCAR driven on the Darlington speedway. These models are replicated on each corner of the vehicle. The remainder of the paper is directed to studying the minimum lap time performance of a Gen 7 NASCAR that is subject to tyre wear and temperature variations; brake heating influences are emphasised. Due to their novelty, the results focus on the performance impact of temperature variations and constraints on the front brake disc temperatures. Constraints on the brake temperatures are introduced to protect the brakes from fade and thermally-induced damage.

ANN-NSGA-assisted investigation of tribo-performance of lead-free nickel boron coating

In recent times electroless Ni-B coatings free of lead are being investigated with an aim to replace the lead stabilized bath. Traditional formulations of Ni-B coatings often rely on the use of heavy metal/lead-based stabilizers. However, the environmental and health concerns associated with these stabilizers have prompted the exploration of stabilizer-free formulations. The tribological behavior and wear mechanisms of heat-treated heavy metal-free Ni-B coatings were investigated systematically by varying load (10–50 N), speed (0.5–1.5 m/s) and distance (400–1000 m) in accordance with Taguchi's L27 orthogonal array. An artificial neural network (ANN) combined with genetic algorithm is proposed to investigate and optimize wear rate and coefficient of friction (COF) of heat-treated Ni-B coatings. Globular morphology was obtained for the coatings with crystalline peaks of Ni, Ni3B and Ni2B for coatings heat treated at 350°C for 1 h. The mean absolute percentage error of ANN model for wear rate and COF was 5.2846% and 2.0572%, respectively. The multiobjective optimization showed 30.325 N load, 0.50007 m/s speed and 759.2959 m distance corresponding to simultaneous minimum wear rate and COF of 0.005297 × 10−6 g N−1 m−1 and 0.25238 respectively. The worn surface of optimized conditions coatings exhibited oxidized flattened nodules and debris that act as load bearing area leading to lower wear rate and COF.

Developed Mathematical Model of Wear Rate for Al Alloy with Nanoparticle Reinforcement

The wear behavior of squeeze cast Al5456alloy with TiC/Flyash nanoparticles is examined. L27 orthogonal array design is preferred to perform the wear experiments to study the influence of various applied loads, sliding distances and sliding speed. ANOVA is carried out to detect the significant and non-significant factors. The maximum and minimum amount of wear is attained as 0.012957mm3 /Nm and 0.002387mm3 /Nm in the 21th and 5th experiments respectively and The optimal factors are recognized to be a sliding distance of 700 m, load of 70 N, and sliding speed of 9 m/s. A model of the regression with three operational factors and three levels was developed for this study. The equations for WR were created by decreasing the sum of the square residuals using the conventional least square method. The regression output and experimental results are compared to estimate the predicted error.

Occurrence of catastrophic tool wear patterns through systematic thermomechanical modeling

Occurrence of catastrophic tool wear patterns through systematic thermomechanical modeling

Prediction of Tool Wear Rate and Tool Wear during Dry Orthogonal Cutting of Inconel 718

A new prediction method was proposed based on the positive feedback relationship between tool geometry and tool wear rate. Dry orthogonal cutting of Inconel 718 was used as a case study. Firstly, tool wear rate models and a tool wear prediction flowchart were proposed. Secondly, the evolution of the tool geometry during tool wear was analyzed considering the combined effect of tool crater wear and tool flank wear. Thirdly, the evolution of the cutting temperature, normal stress and tool–chip relative sliding velocity on the tool wear surface was studied, the evolution of the tool wear rate during tool wear was revealed. Finally, the evolution of the tool geometry and tool wear rate during tool wear were applied to the tool wear prediction method to accurately predict the tool wear. The prediction error of KT is less than 15% in comparison with the experimental results. The tool wear prediction method in this paper is helpful to improve the prediction accuracy of tool crater wear.

Taguchi-Grey Optimization of Tribological Characteristics of Blended SAE 40 Lubricant

A high proportion of lubricants used in automobile engines are mineral-based oil. The depletion of oil reserves and the concerns (non-biodegradable, toxic and environmental issues) of mineral based lubricants prompted the research for a viable alternative. Vegetable oil has been proposed as a potential substitute for the mineral-base lubricants due to its natural and eco-friendly characteristics. In this study, optimization of tribological characteristics of blended SAE 40 produced from SN 500 mineral oil, Shea butter bio-base oil, and viscosity improver was carried out on pin-on-disc tribometer. Taguchi and Taguchi-grey relational method were used to optimize the load and sliding speed to obtain the minimum specific wear rate and coefficient of friction (COF) for the blended SAE 40. The optimum parameters using Taguchi’s and Taguchi-grey relational analysis methods are 8 N load and 5 cm/s sliding speed. At this optimum condition, the minimum specific wear rate of 0.007 mm3 /Nm and minimum coefficient of friction of 0.001 were observed. The developed mathematical model was validated against the experimental results. Deviation of about 5% was obtained in the wear rate model using Taguchi model. Also, the correlation of about 89.77% was observed between the model developed using Taguchi-grey relational model and experimental values. This implies that the two models can be used to predict the tribological properties of blended SAE 40 lubricant.

Analysis and Modeling of Tool Wear Rate in Powder Mix EDM and Pure EDM Using Central Composite Design

The process of using dielectric fluid combined with different types of powders to improve the output of the machined surface is known as powder-mixed electrical discharge machining (PMEDM). In the electrical discharge machining (EDM) industry, this procedure is quickly gaining popularity. This investigation's goal is to ascertain whether tantalum carbide (TaC) powder-mixed dielectric fluid can reduce tool wear during the subsequent EDM machining of stainless-steel material. Two different EDM medium's tool wear rates and mathematical models were investigated during the machining. TaC powder at a concentration of 25.0 g/L in kerosene dielectric fluid was used for the machining process. The peak current, pulse on time, and pulse off time were the machining variables used. These variables' effects on the copper based EDMed electrode tools TWR were identified. The TWR for stainless steel (SUS 304) during electrical discharge machining was reduced by 37.9% when TaC powder additive was used, according to the results, demonstrating the effectiveness of this alternative method for reducing tool wear. The most influential factor, according to the tool wear ratio model for EDM with TaC powder additive (TWRPMEDM), is current, followed by pulse on-time and pulse off-time.

Simulation study on mechanical wear of the diamond grain cutting pipeline steel

With the exploitation of marine resources, the development of maintenance operation technology for subsea pipelines transporting oil and gas has become the focus worldwide. Diamond bead wire serves as important engineering equipment in subsea pipeline maintenance, and the study of the wear mechanism of diamond grains on the beads is key to improving the cutting efficiency and lifetime of diamond bead wire. In this work, a theoretical model of the mechanical wear rate of the diamond grain was established, and a simulation model of the diamond grain cutting X65 pipeline steel was developed by applying smoothed particle hydrodynamics method. By studying the effects of the cutting factors of the diamond grain on mechanical wear, the mechanisms of adhesive wear, abrasive wear, and fatigue wear were clarified. The results indicate that the diamond grain in line contact or large surface contact with X65 steel contributes more to wear rate reduction than point contact; The mechanical wear rate predominated by adhesive wear and abrasive wear of the diamond grain increases with the increase of cutting speed and depth. And when the cutting speed is 22–26 m/s and the depth is 20–30 μm, the growing trend of the mechanical wear rate turns gentle, which is more suitable to balance improving cutting efficiency and reducing mechanical wear.

Modelling on the synergy of mechanical and electrical wear in a current line/catenary-pantograph system

The metro system of electrified rolling stock is an important vehicle for partly solving the metropolitan transportation and carbon emission problems. This study aims to analyse the wear of current collector/catenary-pantograph system in the rolling stock. A theoretical wear rate model between the conductor wire and the current collector of the pantograph system was adopted from the literature and further decomposed into mechanical load, electrical current, current arc erosion, and the synergy components. Based on the decomposed model, an experimental protocol for finding the curve-fitted parameters for the theoretical model was proposed. The numerical data adopted from a previous literature was employed in the decomposed model to discuss the effects of mechanical loading, electrical current, and vehicle speed on the wear rate components. From the decomposed wear rate model, the so-called electrical current lubrication on the total wear rate due to the applied electrical current could be observed directly. Moreover, the nonlinear couplings among the control factors in the operation of the system manifested significantly. Thus, in the design phase the optimization analysis should be performed on the control parameters using the theoretical wear rate model to extend the life and reliability of this catenary-pantograph system.

Study on thermal-mechanical characteristics and crater wear of cemented carbide tools during the milling 508III steel

The water chamber head is made of 508III steel with high strength and hardness. The cemented carbide tool bears a large thermal-mechanical load during the cutting process, which leads to severe insert wear and damage as well as low tool life. Firstly, the milling experiments and finite element (FE) simulation were carried out to study the thermal-mechanical characteristics of tools. Secondly, the thermal-mechanical coupling simulation was carried out to explore the temperature field, strain, total deformation of the milling cutter, and the deformation and strain of the rake face of the milling insert respectively. Finally, the tool wear experiment was carried out, and the form, morphology, and energy spectrum of tool wear were analyzed, and the parameters of the crater wear were measured. The proposed crater wear rate was used as the characterization variable of tool wear, and the crater wear rate model was established to explore the wear evolution process of inserts preliminarily. The research results can provide theoretical support and experimental basis for the in-depth study of the tool failure mechanism and tool optimal design of the high-efficiency milling water chamber head.

Wear of micro diamond tool in ultra-precision turning under dry and minimum quantity lubrication conditions

Minimum quantity lubrication (MQL) is an effective way to reduce the cutting temperature and tool wear. To reveal the effect of MQL on the wear of micro diamond tool, a calculation model for the cutting temperature of micro diamond tool under dry friction condition is established firstly by using the Fourier’s law of heat conduction. Regarding the boundary film as a layer of heat-conduction medium, a revised calculation model for the temperature distribution on tool rake face under MQL condition with different cutting fluids is further established. The predicted results indicate that low viscosity is beneficial to the wetting of cutting fluid on tool-chip contact interface, which can relieve the friction. The reduction of friction finally decreases the cutting temperature. Secondly, the cutting temperature–dependent wear volume of micro diamond tool is predicted by using the Usui wear rate model in response to different cutting fluids and different cutting distances. In dry cutting, the graphite wear of micro diamond tool prevails. However, the application of MQL can slow down the graphitization of diamond, so the wear of micro diamond tool visibly decreases. Finally, cutting experiments with different cutting fluids are performed to verify the established models. The experimental observations agree well with the theoretical prediction results. Such satisfactory consistency confirms that the cutting fluid with low viscosity can reduce the cutting temperature and inhibit tool wear effectively.

CFD modeling of slurry flow erosion wear rate through mitre pipe bend

Erosive wear caused by particulates slurry is one of the major concerns in the pipe bend which may results in the failure of the pipe flow system. In the present work, erosion wear rate through mitre pipe bend caused by silica sand particulates slurry has been investigated using ANSYS Fluent code. The solid spherical particulates of size 125 µm and 250 µm having density of 2650 Kg/m3, were tracked to compute the erosion wear rate using Discrete Phase Method (DPM) model. The particulates were tracked using Eulerian-Lagrange approach along with k-ɛ turbulent model for continuous fluid phase. The silica particulates were injected at solid concentration of 5% and 10% (by weight) from the pipe inlet surface for wide range of velocities viz. 1–8 ms−1. The erosion wear rate was computed through four computational erosion models viz. Generic, Oka, Finnie and Mclaury. Furthermore, the outcomes obtained through Generic models are verified through existing experimental data in the literture. Moreover, the results of DPM concentration, turbulence intensity and particle tracking were predicted to analyze the secondary flow behaviour through the bend cross section. Finally, the effect of particulate size, solid concentration and flow velocity were discussed on erosion wear rate through bend cross section. The findings show that the locality of maximum erosive wear is positioned at the extrados of the bend outlet cross section. Additionally, it is found that Mclaury model offers higher erosion rate as compared to the other models and provides benchmark for designing the slurry pipeline system.

FEM-based simulation of continuous wear of CrAlN-coated tools

The understanding of the correlation between the coating-specific properties of PVD-coated cutting tools, the thermomechanical loads on the cutting wedge and the resulting tool wear, is necessary to avoid costly iterative test series. To obtain this knowledge a hybrid approach based on experimental tests and FEM-based chip formation is used in this study. In this respect, in a first step, a suitable wear rate model is derived and parameterized on the basis of wear analogy tests and experimental machining investigations. This wear rate model is then coupled with the FEM-based chip formation simulation to predict continuous tool wear.

Processing and wear characterisation of self-lubricating AA6082/TiC/Gr composites

ABSTRACT The manuscript presents wear characteristics modelling of AA6082/TiC/Gr composites using rotatable central composite design of response surface methodology. Experiments were conducted at room temperature using pin on disc apparatus. Wear rate model was established as a function of cast sample, applied load and sliding velocity. The analysis of the variance (ANOVA) results revealed ‘Model’ as ‘Significant’ and ‘Lack of fit’ is ‘Not significant’, indicating a good model. The results also show applied load as the most influencing factor while cast sample the least factor affecting the wear rate. The combined effect of cast sample and applied load affects the wear rate more as compared to other combinations. Scanning electron microscopy (SEM) study was also done to correlate the results obtained.

A wear rate model incorporating inflationary cost of agro-waste filled composites for brake pad applications to lower composite cost

Wear rate appraisals are currently indispensable on agro-waste filled composites for brake pads as they predict the expected lifespan of the materials. However, existing wear rate models are inaccurate as predictions omit the inflationary cost of the materials. In this paper, the idea is to account for the inflationary cost of the materials and adjust that into a pseudo wear rate model. The wear rate of agro-waste fillers in an organic matrix to create brake pads under dry sliding wear experiments was considered. Five composite specimens were fabricated in cylindrical specimen height of 14.5 mm and varying diameters of 8, 10, 12 and 15.5 mm and the material wear loss was measured. The 8, 10 and 12 mm diameter specimens revealed that the composite with the best and worst wear resistance were the wear rates of 0.6, 1.4, 1.73 mm3/Nm, and 3.07, 3.54, 4.19 mm3/Nm, respectively. The 15.5 mm diameter specimen showed lower wear rates of 2.13 and 2.14 and 1.56 mm3/Nm than commercial brake pad’s 2.58 mm3/Nm. The pseudo wear rate model predicts the impact of the independent variable i.e. inflationary cost, opportunity cost, time, and sample size. The utility of this effort is to assist the composite manufacturers to take cost-effective decisions and design optimisation can be accomplished to lower the cost of composite products.

Modeling and prediction of wear rate of aluminum alloy (Al 7075) using power law and ANN

The wear process significantly influences machine parts during their useful life. The wear process is complex, and therefore, it is very difficult to develop a comprehensive model involving all the operating parameters. In the present study, wear rate is measured during the wear process at different operating parameters such as force (load), sliding distance, and velocity. Power law and Artificial neural network (ANN) approaches are used to model the wear rate of Al7075 alloy. Power law and neural network-based models are compared using statistical methods with a coefficient of determination (R2), mean absolute percentage error (MAPE), and means square error (MSE). It is seen that the proposed models are competent to predict the wear rate of Al7075 alloy. The ANN model estimates the wear rate with high accuracy compared to that of the power law model. The models developed for wear rate were found to be consistent with the experimental data. ANOVA analysis revealed that the load has a significant effect on the wear rate than the sliding speed and sliding distance.