Wear Rate Model Research Articles

Modelowanie numeryczne procesu zużycia ściernego matryc do kucia na gorąco

Modelowanie numeryczne procesu zużycia ściernego matryc do kucia na gorąco

Enhanced particle filter for tool wear prediction

Timely assessment and prediction of tool wear is essential to ensuring part quality, minimizing material waste, and contributing to sustainable manufacturing. This paper presents a probabilistic method based on particle filtering to account for uncertainties in the tool wear process. Tool wear state is predicted by recursively updating a physics-based tool wear rate model with online measurement, following a Bayesian inference scheme. For long term prediction where online measurement is not available, regression analysis methods such as autoregressive model and support vector regression are investigated by incorporating predicted measurement into particle filter. The effectiveness of the developed method is demonstrated using experiments performed on a CNC milling machine.

Predictive modeling for flank wear progression of coated carbide tool in turning hardened steel under practical machining conditions

Growing needs for economical and environmental friendly manufacturing processes have increased usage of coated carbide tools in dry and high-speed machining of hardened steel. However, most undesirable characteristic of the machining process is tool wear; especially the flank wear, which adversely affects the dimensional accuracy and product quality. Therefore, prediction of flank wear progression will be extremely valuable. In the present study, a flank wear rate model is developed incorporating abrasion, adhesion, and diffusion as dominant wear mechanisms. Given the cutting conditions, tool geometry, and workpiece and cutting tool material properties, the model predicts flank wear progression with machining time. Developed model is calibrated and experimentally validated in turning of hardened AISI 4340 steel at different levels of hardness using chemical vapor deposition (CVD)-applied multilayer TiCN/Al2O3/TiN-coated carbide tool under practical 3-D machining conditions. As predicted results generally agree well with the experimental observations, proposed model could be helpful to predict the flank wear progression and hence to support the optimization studies within the domain of the cutting parameters.

Optimization of dry sliding wear conditions for AlSi10Mg/SiCp composites using response surface: genetic algorithm approach

Purpose – The purpose of this research paper is to find the optimum parameters, namely, the sliding speed, applied load and percentage of silicon carbide particles (SiCp), under which AlSi10Mg/SiCp composites experience minimum wear. Design/methodology/approach – Wear rate (WR) of AlSi10Mg, AlSi10Mg/10SiC and AlSi10Mg/20SiC was measured using pin-on-disk equipment according to ASTM G99 standards. Response surface method was used to design the experiments, model and analyze the tribological behaviour. Tests were conducted as per Box–Beheken design of experiments. The wear mechanisms were observed using scanning electron microscope. Genetic algorithm was used to find the optimum parameters for minimum WR. Findings – Wear mechanisms underwent changes with variation in applied load, sliding speed and per cent SiCp. An optimum wear condition was obtained when the process parameters, namely, the sliding speed, applied load and percentage of SiCp, were at 4 m/s, 10 N and 20 per cent, respectively. Combined GA-RSM approach was successfully used to predict the minimum WR condition of AlSi10Mg/SiCp composites with an accuracy of 94 per cent. Originality/value – The tribological behaviour of AlSi10Mg/SiCp composites has been investigated in detail. A statistical WR model is proposed. This paper provides an optimum condition to design the tribo contact between steel and AlSi10Mg/SiCp composites.

English

The proper selection of machining parameters can result in better machining performance in the electrical discharge machining process. However, this job is not always easy since the phenomena occurring between the electrodes in EDM are not yet fully understood. This study reports the development of a comprehensive mathematical model for the electrode wear rate (EWR) of a graphite tool in EDM on Ti-5Al-2.5Sn alloy, which has not yet been presented. Experiments for positive polarity of the graphite electrode, based on design of experiment (DOE), are first conducted. Modeling and analysis are carried out through the response surface methodology, utilizing the experimental results. A confirmation test is also executed to confirm the validity and the accuracy of the mathematical model developed. The confirmation test exhibits an average error of less than 6%. Negative electrode wear is evidenced for particular settings. The combination of 15A peak current, 350µs pulse-on time, 180µs pulse-off time and 95V servo-voltage and positive polarity causes negative tool wear. It is apparent that the developed model can evaluate electrode wear rate accurately and successfully.

Experimental and finite element simulation based investigations on micro-milling Ti-6Al-4V titanium alloy: Effects of cBN coating on tool wear

Micro-milling process is a direct and flexible fabrication method in producing functional three dimensional micro-products. The advance of micro-milling process ultimately depends on the development of micro cutting tools since it is a tool-based process. Therefore, in this study an attempt to improve the performance of carbide micro-end mills by applying cubic boron nitride (cBN) coating was carried out. Experiments and finite element method (FEM) based simulations were used to study the effect of cBN coated tool in micro-machining of Ti-6Al-4V titanium alloy. The experiments were conducted to compare the performance of cBN coated and uncoated micro-end mills in terms of surface roughness, burr formation and tool wear. FE simulations were employed to investigate chip formation process in micro-milling to reveal the effects of cBN coated micro-end mills with increased edge radius in terms of cutting force generation, tool temperature and contact pressure, sliding velocity and hence tool wear rate. The simulation results were further utilized for estimating tool life using a sliding wear rate model and compared with experiments. This study clearly showed that the cBN coated carbide tool outperformed the uncoated carbide tool in generation of tool wear and cutting temperature.

Cutting Mechanism and Model for Cutting Al/SiCp Composites

Al/SiCp composite material is rapidly advanced due to its applications to weapon, military, aeronautics and astronautics. In some cases, fields of research are stagnating for its difficulty in material processing. In this study, we are particularly concerned about the cutting mechanism of Al/SiCp through modeling and simulations on wear rate of the tools. These simulations of tool wear rate and cutting mechanism of Al/SiCp are proved by cutting tests on Al/SiCp with nanocemented carbide tool WC-7Co and common cemented carbide tool YG8. A detailed investigation suggests that the cutting instinct of Al/SiCp is of interrupted cutting process. And the grain loss, less tipping and blade fracture during tool wear results from high frequency intermittent shock by SiC grain. The wear behavior on the tool flank is mainly of grain loss. However, the wear behavior of the rake face is not only of grain loss, but also abrasive wear of WC grain by SiC grain. It is conclusively demonstrated that the model of tool wear rate is sufficient for revolution characterization of tool wear rate on grain size, volume fraction of reinforcement, and also significantly important to prove the interrupted cutting process mechanism of Al/SiCp.

Optimization of Machining Parameters on Tool Wear Rate of Ti-6Al-4V through EDM Using Copper Tungsten Electrode: A Statistical Approach

Electrical discharge machining (EDM) is relatively modern machining process having distinct advantages over other machining processes and able to machine Ti-alloys effectively. This paper attempts to investigate the effects of peak ampere, pulse on time and pulse off time on tool wear rate (TWR) of titanium alloy Ti-6Al-4V in EDM utilizing copper tungsten as an electrode and positive polarity of the electrode. A mathematical model for electrode wear rate is developed in this paper. Design of experiments method and response surface methodology techniques are implemented. The validity test of the fit and adequacy of the proposed models has been carried out through analysis of variance. It can be seen that as the peak current increases the TWR decreases till certain ampere and then increases. The excellent surface finish is investigated in this study at short pulse on time and in contrast the long pulse duration causes the lowest TWR. Long pulse off time provides minimum TWR and the impact of pulse interval on TWR depends on peak current. The result leads to wear rate of electrode and economical industrial machining by optimizing the input parameters.

Tool wear monitoring using neuro-fuzzy techniques: a comparative study in a turning process

Tool wear detection is a key issue for tool condition monitoring. The maximization of useful tool life is frequently related with the optimization of machining processes. This paper presents two model-based approaches for tool wear monitoring on the basis of neuro-fuzzy techniques. The use of a neuro-fuzzy hybridization to design a tool wear monitoring system is aiming at exploiting the synergy of neural networks and fuzzy logic, by combining human reasoning with learning and connectionist structure. The turning process that is a well-known machining process is selected for this case study. A four-input (i.e., time, cutting forces, vibrations and acoustic emissions signals) single-output (tool wear rate) model is designed and implemented on the basis of three neuro-fuzzy approaches (inductive, transductive and evolving neuro-fuzzy systems). The tool wear model is then used for monitoring the turning process. The comparative study demonstrates that the transductive neuro-fuzzy model provides better error-based performance indices for detecting tool wear than the inductive neuro-fuzzy model and than the evolving neuro-fuzzy model.

Computational investigation of testing parameter effects on abrasive wear behaviour of AL2O3 particle-reinforced MMCS using statistical analysis

The wear rate model of 7.3 vol.% Al2O3 particle-reinforced aluminium alloy composites with 16 and 66 µm particle sizes fabricated by molten metal mixing method was developed in terms of applied load, particle size of reinforcement, abrasive grain size and sliding distance based on the Taguchi method. The two-body abrasive wear behaviour of the specimens was investigated using a pin-on-disc abrasion test apparatus where the sample slid against different SiC abrasives under the loads of 2 and 5 N at the room conditions. The orthogonal array, signal-to-noise ratio and analysis of variance were employed to find out the optimal testing parameters. The test results showed that particle size of reinforcement was found to be the most effective factor among the other control parameters on abrasive wear, followed by abrasive grain size. Moreover, the optimal combination of the testing parameters was determined and predicted. The predicted wear rate results were compared with experimental results and found to be quite reliable.

Wear Rate Prediction and Analysis of Metal-Matrix of Ni-Based Super Alloy onto Cast Iron by Laser Cladding

Metal- matrix composites layers were prepared by laser cladding with Ni-based Super-alloy onto CrMo cast iron. Applying uniform experiment design, under conditions of different velocity and load ,the wear tests of alloy layers were carried out and the stepwise regression method are used to establish the wear rate model for prediction of wear rate. It is proved that the modal is significant and represents the character of the wear trend. According to the wear rate model ,the wear characteristics are analysed and the wear mechanisms are identified. The main wear mechanism of laser cladding layer are delamination, adhesive wear and abrasive wear.

Biomechanical modeling of acetabular component polyethylene stresses, fracture risk, and wear rate following press‐fit implantation

Press-fit implantation may result in acetabular component deformation between the ischial-ilial columns ("pinching"). The biomechanical and clinical consequences of liner pinching due to press-fit implantation have not been well studied. We compared the effects of pinching on the polyethylene fracture risk, potential wear rate, and stresses for two different thickness liners using computational methods. Line-to-line ("no pinch") reaming and 2 mm underreaming press fit ("pinch") conditions were examined for Trident cups with X3 polyethylene liner wall thicknesses of 5.9 mm (36E) and 3.8 mm (40E). Press-fit cup deformations were measured from a foam block configuration. A hybrid material model, calibrated to experimentally determined stress-strain behavior of sequentially annealed polyethylene, was applied to the computational model. Molecular chain stretch did not exceed the fracture threshold in any cases. Nominal shell pinch of 0.28 mm was estimated to increase the volumetric wear rate by 70% for both cups and peak contact stresses by 140 and 170% for the 5.9 and 3.8 mm-thick liners, respectively. Although pinching increases liner stresses, polyethylene fracture is highly unlikely, and the volumetric wear rates are likely to be low compared to conventional polyethylene.

2D FEM Estimate of Tool Wear in Hard Cutting Operation: Tool Wear and Simulation of Hard Cutting Process under Steady State

Tool wear plays an important role in cutting process research. It affects the quality of machined surface and cutting parameter to a great extent, such as cutting force, cutting temperature and cutting quiver. In order to predict tool wear in hard cutting process by using FEM method, the character of tool wear during cutting process is presented firstly, and Usui’s tool wear rate model is introduced. Then the FEM model for steady state cutting process using Abaqus is established. FEM model describes the workpiece material characteristic accurately for the process of PCBN tool cutting GCr15 by adoptiving Johnson-Cook constitutive model. Simulation results of steady cutting process offer foundation to simulate tool wear.

Mathematical modeling of tool wear rate in ultrasonic machining of titanium

Ultrasonic machining is a mechanical material removal process used to erode holes and cavities in hard or brittle workpiece by using shaped tools, high-frequency mechanical motion, and an abrasive slurry. In the present study, outcome of the Taguchi model has been used for developing a mathematical model for tool wear rate; using Buckingham’s π-theorem for stationary ultrasonic machining of titanium and its alloys. Six input parameters, namely, tool material, power rating, slurry type, slurry temperature, slurry concentration, and slurry grit size were selected to give output in form of tool wear rate. This study will provide main effects of these variables on tool wear rate and will shed light on the tool wear mechanism in ultrasonic machining of titanium and its alloys. The comparison with experimental results will also serve as further validation of model.

Estimate of Tool Wear in Milling Operation Based on “Differential” Wear Rate Model

Many research show that in metal cutting process wear rate is dependent on the cutting process variables such as temperature at tool face, contact pressure (normal stress) and relative sliding velocity at tool/chip and tool/work interface; their relationship is described by “differential” wear rate model. Based on this “differential” wear rate model, a method to estimate tool wear in milling operation is proposed and the cutting process variables are predicted by performing chip formation analysis with FEM code ABAQUS/Explicit and heat transfer analysis with ABAQUS/Standard. The implementation is exemplified by estimating tool wear of carbide tools in milling of Ck45 work. Both progressive flank wear and crater wear profile are estimated.

Wear rate model for UHMWPE in total joint applications

The wear of polyethylene cup in hip implants is influenced by a set of primary parameters, which have been reported to lead to loosening of the implant and osteolysis. Mass loss as a result of wear leading to osteolysis may cause dislocation and subsequently revision and/or replacement of the implant. An attempt was made to develop a comprehensive wear rate prediction equation in terms of the implant dimensions, namely femoral head roughness, femoral head diameter, subject body weight and mechanical properties of ultra high molecular weight polyethylene (UHMWPE). The effect of mechanical properties of polyethylene was also introduced so that a more comprehensive equation can be developed.

The influence of applied load, sliding velocity and martensitic transformation on the unlubricated sliding wear of austenitic stainless steels

In this work, the sliding wear of AISI 304 and AISI 316 austenitic stainless steels was studied as a function of applied load (from 6 to 20 N) and tangential velocity (from 0.07 to 0.81 m s −1). Wear experiments were conducted in a commercial pin-on-disc equipment and were designed with response surface methodology. Worn surfaces and wear debris were analyzed through scanning electron microscopy, X-ray diffraction, Mössbauer spectroscopy, surface temperature and instrumented indentation. Results indicated plasticity-dominated wear (metallic particle oxidation, adhesive wear and mixed wear) as the sliding wear mechanisms. The wear rate was dependent on the interaction between applied load and tangential velocity, and an empirical model of wear rate as a function of applied load and tangential velocity was proposed by means of central composite design. The change in the wear mechanism was associated with the subsurface plastic deformation and surface temperature, which were strongly affected by sliding speed. In addition, strain-induced martensitic transformation was observed on the sliding surface of the austenitic stainless steels.

Wear rate model for UHMWPE in total hip and knee arthroplasty

The wear of polyethylene cup in hip and knee implants is influenced by a set of primary parameters, has been reported to lead to loosening of the implant and osteolysis. Mass loss as a result of wear and osteolysis may cause dislocation and subsequently revision and/or replacement of the implant. An attempt was made to develop, in the case of hip implant, a comprehensive wear rate equation in terms of the implant dimensions namely, femoral head roughness, femoral head diameter, subject body weight and mechanical properties of ultra high molecular weight polyethylene (UHMWPE). The effect of mechanical properties of polyethylene was included into the model and that resulted in more comprehensive equation. In the case of knee implant an attempt was made to develop in vitro wear rate model in terms of the experimental parameters, such as load and traveled distance.

On the Role of Reinforcements on Tool Performance During Cutting of Metal Matrix Composites

Machining of metal matrix composites (MMCs) has been notoriously difficult due to the extremely abrasive nature of the reinforcements and presents a significant challenge to the industry. This paper presents an analytical tool flank wear rate model that has been developed for orthogonal cutting processes. In this approach, the wear volume loss is formulated based on the process parameters and reinforcement properties. Then, the flank wear rate is developed by considering the tool geometry in orthogonal metal cutting. The developed model was validated with orthogonal cutting tests conducted on 6061 aluminum MMC reinforced with A 2O 3 particulates of different average sizes (9.5 μm, 20 μm, 25 μm) and volume fractions (10% and 20%) under similar cutting conditions. The results showed good agreement between the predicted and measured flank wear data.

Modeling flank wear of carbide tool insert in metal cutting

In this paper theoretical and experimental studies are carried out to investigate the intrinsic relationship between tool flank wear and operational conditions in metal cutting processes using carbide cutting inserts. A new flank wear rate model, which combines cutting mechanics simulation and an empirical model, is developed to predict tool flank wear land width. A set of tool wear cutting tests using hard metal coated carbide cutting inserts are performed under different operational conditions. The wear of the cutting inset is evaluated and recorded using Zygo New View 5000 microscope. The results of the experimental studies indicate that cutting speed has a more dramatic effect on tool life than feed rate. The wear constants in the proposed wear rate model are determined based on the machining data and simulation results. A good agreements between the predicted and measured tool flank wear land width show that the developed tool wear model can accurately predict tool flank wear to some extent.