Tool Wear Research Articles

Tool Wear Classification Based on Support Vector Machine and Deep Learning Models

Tool Wear Classification Based on Support Vector Machine and Deep Learning Models

Experimental Investigation of the Micro-Milling of Additively Manufactured Titanium Alloys: Selective Laser Melting and Wrought Ti6Al4V

AbstractIn recent years, additive manufacturing (AM) has gained popularity in the aerospace, automobile, and medical industries due to its ability to produce complex profiles with minimal tolerances. Micro-milling is recommended for machining AM-based parts to improve surface quality and form accuracy. Therefore, the machinability of a titanium alloy (Ti6Al4V) manufactured using selective laser melting (SLM) is explored and compared to that of wrought Ti6Al4V in micro-milling. The experimental results reveal the surface topology, chip morphology, burr formation, and tool wear characteristics of both samples. The micro-milling of AM-based Ti6Al4V generates a surface roughness of 19.2 nm, which is 13.9% lower than that of wrought workpieces, and this component exhibits less tool wear. SLM-based Ti6Al4V produces continuous chips, while wrought Ti6Al4V yields relatively short chips. Additionally, SLM-fabricated Ti6Al4V exhibits smaller burrs after micro-milling than wrought Ti6Al4V. Despite the higher hardness of SLM-based Ti6Al4V, it demonstrates better machinability than wrought Ti6Al4V, resulting in better surface quality with lower tool wear levels and shorter burr heights. This study provides valuable insights into future research on postprocessing AM-based titanium parts, especially using micro-milling.

Multi-objective optimization in EDM of functionally graded Fe-Al using grey relational analysis

Abstract Functionally Graded Materials (FGMs) are multipurpose materials with a specific goal of managing changes in structural, thermal, or functional qualities. They feature a spatial variation in microstructure and/or composition. The current work prepared three layers of sample with different chemical compositions of Fe-Al FGM (50 Al-50 Fe, 45 Al-55 Fe, and 40 Al-60 Fe) at. % produced by powder metallurgy, then studied the machining behavior of these samples. The literature on the machining behavior of FGM was reviewed, and the influence of electrical discharge machine (EDM) process parameters such as voltage (V), current (I), pulse-on time, and pulse-off time on performance characteristics (material removal rate (MRR), tool wear rate (TWR), and surface roughness (Ra)) was investigated. The optimal machining settings for Fe-Al FGM samples will be ascertained by use of Grey Relational Analysis (GRA), which is based on the Taguchi approach, after an experimental investigation of the L18 orthogonal array design of trials. The GRA findings verify that V 140 volts, Ip10 A, Ton 100 μs, and Toff 75 μs is the optimal combination of process parameters. It has been found that the voltage is more significantly affected than the rest of the input parameters to obtain greater material removal rate (MRR) and lower tool wear rate (EWR) and surface roughness (Ra) through the response table. According to the study, choosing the right process parameters can improve the multi-performance feature.

Assessment of Machining Performance for Intelligent Tool Wear Prediction Using Hybrid Extreme Learning Machine

Assessment of Machining Performance for Intelligent Tool Wear Prediction Using Hybrid Extreme Learning Machine

Modeling and Monitoring of the Tool Temperature During Continuous and Interrupted Turning with Cutting Fluid

In metal cutting, a large amount of mechanical energy converts into heat, leading to a rapid temperature rise. Excessive heat accelerates tool wear, shortens tool life, and hinders chip breakage. Most existing thermal studies have focused on dry machining, with limited research on the effects of cutting fluids. This study addresses that gap by investigating the thermal behavior of cutting tools during continuous and interrupted turning with cutting fluid. Tool temperatures were first measured experimentally by embedding a thermocouple in a defined position within the tool. These experimental results were then combined with simulations to evaluate temperature changes, heat partition, and cooling efficiency under various cutting conditions. This work presents novel analytical and numerical models. Both models accurately predicted the temperature distribution, with the analytical model offering a computationally more efficient solution for industrial use. Experimental results showed that tool temperature increased with cutting speed, feed, and cutting depth, but the heat partition into the tool decreased. In continuous cutting, cooling efficiency was mainly influenced by feed rate and cutting depth, while cutting speed had minimal impact. Interrupted cutting improved cooling efficiency, as the absence of chips and workpieces during non-cutting phases allowed the cutting fluid to flow over the tool surface at higher speeds. The convective cooling coefficient was determined through inverse calibration. A comparative analysis of the analytical and numerical simulations revealed that the analytical model can underestimate the temperature distribution for complex tool structures, particularly non-orthogonal hexahedral geometries. However, the relative error remained consistent across different cutting conditions, with less error observed in interrupted cutting compared to continuous cutting. These findings highlight the potential of analytical models for optimizing thermal management in metal turning processes.

Classification-Based Parameter Optimization Approach of the Turning Process

The turning process is a widely used machining process, and its productivity has a significant impact on the cost and profit in industrial enterprises. Currently, it is difficult to effectively determine the optimum process parameters under complex conditions. To address this issue, a classification-based parameter optimization approach of the turning process is proposed in this paper, which aims to provide feasible optimization suggestions of process parameters and consists of a classification model and several optimization strategies. Specifically, the classification model is used to separate the whole complex process into different substages to reduce difficulties of the further optimization, and it achieves high accuracy and strong anti-interference in the identification of substages by integrating the advantages of an encoder-decoder framework, attention mechanism, and major voting. Additionally, during the optimization process of each substage, Dynamic Time Warping (DTW) and K-Nearest Neighbor (KNN) are utilized to eliminate the negative impact of cutting tool wear status on optimization results at first. Then, the envelope curve strategy and boxplot method succeed in the adaptive calculation of a parameter threshold and the detection of optimizable items. According to these optimization strategies, the proposed approach performs well in the provision of effective optimization suggestions. Ultimately, the proposed approach is verified by a bearing production line. Experimental results demonstrate that the proposed approach achieves a significant productivity improvement of 23.43% in the studied production line.

Friction stir welding of Haynes 282 Ni superalloy by using a novel hemispherical tool.

In the present investigation, friction stir welding (FSW) of a gamma prime (γ') strengthened Haynes 282 nickel-base superalloy by using a novel hemispherical tool is documented. A joint efficiency of ~ 96% was achieved in the as-welded condition, which further increased to ~ 100% after two-step post-weld aging heat treatment. An extremely fine (~ 2μm) grained microstructure was observed in the FSWed region compared with the coarse (~ 48μm) grain base metal region. The carbides (MC and M23C6) and γ' precipitates are identified as the important microstructural constituent phases observed in the welded region. The aging heat treatment resulted in the precipitation of the γ' strengthening phase and altered the morphology of the M23C6 carbide phase in the welded region from a continuous film to discrete particles at the grain boundaries. The preliminary results concerning tool life suggest that no significant tool wear occurs at least up to a welding distance of 200mm. Therefore, the novel hemispherical tool design allows the successful FSW of high-temperature application materials without any significant tool wear or high heat generation.

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.

Microscopic Analysis and Evaluation of Thermal Elevation and Wear of Drills for Implant Site Preparation: An In Vitro Study

Drilling for implant site preparation generates heat, which can cause bone necrosis if temperatures exceed 47 °C for over a minute. Factors influencing heat include drill size, speed, pressure, irrigation, and tool wear. Frequent drill replacement is essential, as wear from repeated use and sterilization affects performance. This study compared three pilot drills with similar designs from different manufacturers, testing each on pig ribs for 15 perforations after 15 sterilization cycles. Researchers measured temperature increase, drilling time, and surface wear. Results showed that drill no. 1 generated more heat than drills no. 2 and no. 3, though none reached critical temperatures. Drill no. 2 took the longest to reach the desired depth and displayed the most deformation. Findings highlight the importance of adhering to the recommended operational limits, suggesting that drills should be replaced after 15 cycles to ensure efficacy and patient safety.

Nickel-based alloy efficient milling with ceramic tool and experimental verification in closed impeller

Nickel-based alloys are a class of materials that possess exceptional properties, including superior corrosion, oxidation, and fatigue resistance. They are increasingly utilized in high-performance critical components, particularly in the fields of aerospace engines and gas turbines. Nickel-based alloys pose significant challenges during machining due to their high cutting forces and work hardening, leading to low machining efficiency, severe tool wear, and subpar surface quality of the machined parts. To address these challenges, an orthogonal cutting experiment was conducted on GH4061 alloy to evaluate the machining performance by using monolithic ceramic milling tools. The optimal cutting parameters combination for dry cutting of nickel-based alloys was determined. The surface quality was tested and analyzed, including surface micro structure, residual stress, and surface roughness. The machining experiment was conducted on GH4061 closed impeller. The results demonstrated that high-speed cutting was more effective than low-speed cutting in improving the surface quality of the machined part. In the rough processing, monolithic ceramic milling tools was used to quickly remove the excess material. The adhesive and diffusion effects mainly contributing to the wear of the monolithic ceramic tool in GH4061 milling. Average surface roughness 1.41 μm can be obtained through dry milling using a monolithic ceramic tool with cutting speed 602.88 m/min, cutting depth 0.3 mm, cutting width 6 mm and feed per tooth 0.03 mm/z, along with metal removal rate 5184 mm3/min. High cutting speed will resulting in relatively low residual stress in the surface layer as well as a lower thickness of the surface alternation layer. Finally, a physical GH4061 closed impeller was machined to verify the proposed milling method.

Influence of the Cooling Temperature on the Surface Quality in Integrated Additive and Subtractive Manufacturing of Aluminum Alloy

The surface quality of parts processed by laser additive manufacturing, especially laser-based directed energy deposition (LDED), makes it difficult to meet actual use requirements. In addition, defects generated during the long-term additive manufacturing process need to be removed in time. Therefore, laser additive and subtractive manufacturing is of great significance for additive manufacturing. The main difference between laser additive-subtractive manufacturing and pure subtraction is that a cooling temperature is required due to the laser process. Therefore, this work studies the temperature variation regularity during LDED and the milling processes, as well as the surface roughness, cross-sectional microstructure, and tool wear under different cooling temperatures for milling. The results show that there is a “turning point temperature” in LDED, and the value of the turning point temperature gradually increases with heat accumulation, which affects the initial temperature of the subtractive manufacturing. When subtracting, a high initial temperature improves surface quality and reduces tool wear, but an excessively high temperature will cause the aluminum alloy to adhere to the tool. Then, the smear metal is difficult to effectively remove, deteriorates the milling quality, and aggravates tool wear. It is found that the higher the cooling temperature generated, the wider the thermally insulated shear band. The insulated shear band may affect the quality of the additive and subtractive manufacturing. Finally, it is determined that the milling temperature of aluminum alloy in this work condition is about 100 °C.

Effects of tool coating and tool wear on the surface and chip morphology in side milling of Ti2AlNb intermetallic alloys

Effects of tool coating and tool wear on the surface and chip morphology in side milling of Ti2AlNb intermetallic alloys

Impact of tool nose size on the performance and wear behavior of carbide tool when boring 1Cr17Ni2 martensitic stainless-steel parts

Purpose This study aims to examine the cutting performance of a coated carbide tool during the boring of 1Cr17Ni2 martensitic stainless steel, with a focus on how the tool’s structural parameters, particularly the nose radius, affect the wear patterns, wear volume and lifetime of the cutting tool, and related mechanisms. Design/methodology/approach A full factorial boring experiment with three factors at two levels was conducted to analyze systematically the impact of cutting parameters on the tool wear behavior. The evolution of tool wear over the machining time was recorded, and the influences of the cutting parameters and nose radius on wear behavior of the tool were examined. Findings The results show that higher cutting parameters lead to significant wear or plastic deformation at the tool nose. When the cutting depth is less than the nose radius, the tool wear tends to be minimized. Larger nose radius tools have weaker chip-breaking but greater strength and wear resistance. Higher cutting parameters reduce wear for the tools with larger nose radius, maintaining their integrity. Wear mechanisms are primarily abrasive, adhesive and diffusion wear. Furthermore, the full-factorial analysis of variance revealed that for the tool with rε = 0.4 mm and 0.8 mm, the factors contributing the most to tool wear were cutting speed (38.76%) and cutting depth (86.43%), respectively. Originality/value This study is of great significance for selection of cutting tools and cutting parameters for boring 1Cr17Ni2 martensitic stainless-steel parts. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2024-0266/

Research Progress towards the Machining of Titanium Alloy Using CNC Milling: A Technical Review

Because of their extraordinary qualities, titanium alloys are very sought-after materials that can be applied to a wide range of sectors. Excellent mechanical and chemical qualities, including a high strength-to-weight ratio and resistance to corrosion, are present in it. The special properties of these alloys make machining them extremely difficult. As frequent tool wear occurs throughout the machining process, Computer Numerical Control (CNC) milling has become a potential method for machining titanium alloys due to its precision and versatility. This review article provides a comprehensive overview of the development of titanium alloy CNC milling, with an emphasis on the effects of cutting tool geometries and materials on machining efficiency. The process examines several aspects of cutting circumstances, including depth of cut, speed, feed rate, and lubrication techniques, and optimizes machining parameters and procedures to achieve the best results. Surface integrity and quality, surface roughness, residual stresses, and microstructural changes brought about by CNC milling are the main points of evaluation.

Experimental investigations on ultrasonic elliptical vibration turning of SiCp/Al composites

ABSTRACT This study identifies key factors affecting SiCp/Al surface formation in ultrasonic elliptical vibration assisted turning (UEVT) and conventional turning (CT) by scratch tests, end face cutting experiments and theoretical analysis. It also evaluates cutting parameters’ effects on deformation of SiCp/Al. Experimental findings underscore theimportance of vibration effect and removal rate. At lower cutting speeds, the ironing effect results in a dense morphology during UEVT that is advantageous for enhancing both surface quality and microhardness. The high removal speed increases the particle-tool interaction, promotes the generation and propagation of cracks indeformation zone. Specifically, at a reasonable cutting speed (200 mm/min), the utilization of vibration results in a 59% reduction in surface roughness and a commendable enhancement in microhardness, coupled with a significant suppression of tool wear. The results of this study are expected to provide positive theoretical recommendations for improving the machinability of SiCp/Al in UEVT.

Comparative Investigations of Tool Wear and Cutting Force for Wet and Dry Turning of Super Duplex Stainless Steels 2507

Comparative Investigations of Tool Wear and Cutting Force for Wet and Dry Turning of Super Duplex Stainless Steels 2507

Characterizing the tool wear morphologies and life in milling A520-10%SiC under various lubrication and cutting conditions

Metal matrix composites (MMCs) are lightweight and widely used materials constantly applied in various industries. Such material’s structural and functional properties change under the contributions of various reinforcing particles and base materials. Multiple technologies are used in the manufacturing and machining these materials, and numerous studies are oriented toward this domain through academic and industrial projects. One aspect that receives less attention is understanding the combined effects of cutting parameters, lubrication conditions, and reinforcing elements on the machinability of such materials. Amongst MMC, limited attention has been paid to A520 alloys reinforced with SiC particles. Therefore, this work investigated the tool wear size and morphology in milling A520-10%SiC under various lubrication and cutting conditions. It was observed that cutting conditions significantly affect the tool life and wear morphology when machining A520-10%SiC. The main wear modes observed were abrasion and adhesion, mainly presented as the built-up edge (BUE) and Built-up layer (BUL). The wet method reduced the formation of BUE and BUL by 95% and MQL by 60% compared to the dry method. It was also observed that better tool life was observed under wet mode than readings made under MQL and dry modes. The outcomes could generate a practical window for the optimum selection of cutting parameters when machining reinforced Al-MMCs, in principle, A520-10%SiC.

Research on numerical simulation and prediction of tool wear in cutting ultra-high-strength aluminum alloys

Research on numerical simulation and prediction of tool wear in cutting ultra-high-strength aluminum alloys

Complementary Machining – Machining Strategy for Surface Modification: A Review

All fabrication techniques utilized to manufacture metallic parts modify the surface integrity of the part. Complementary machining is a relatively recent machining strategy characterized by combining metal cutting and mechanical surface treatment. Typically, it implies that after conventional machining, the cutting insert is used reversely to modify the surface by local plastic deformation. To improve product performance, mechanical surface treatment is an additional phase in the manufacturing process chain that usually results in longer production times and higher costs. As a result, a variety of hybrid techniques have been created, such as complementary machining, which has the benefit of using conventional machine tools and their associated cutting tools. The study on complementary machining is reviewed in the article. The main focus is to assess the viability of complementary machining to modify surface integrity for enhanced properties by specifically establishing its effect on tool wear, surface roughness, microhardness, fatigue, microstructure, and residual stress state.

The influences of alloying elements and processing conditions on the machinability of wrought aluminium alloys: A literature review

Today, wrought aluminium alloys are ranked among the most important materials with low specific density, strength features, corrosion resistance, machinability and recyclability properties in numerous application fields. Machining process of these alloys involves a number of considerations to ensure the highest quality and productivity. Key machinability issues include the rate of tool wear, workpiece surface finish and integrity and machining process sustainability. Understanding and optimising these parameters can lead to improving the machinability, better surface finish, longer tool life, and overall, more efficient and cost-effective machining processes for wrought aluminium alloys. The machining of wrought aluminium alloys remains a challenging task due to their unique characteristics, such as high strength, thermal conductivity and refined grain structures with mechanical and/or heat treatment. Although considerable progress has been made in the development of cutting tool materials and machining techniques for wrought aluminium alloys, further research is required to improve the machinability of these materials and reduce the associated costs and time needed for production. Having access to relevant information about these characteristics can help industries and researchers make informed decisions and achieve better outcomes when machining of these important materials. Accordingly, in the current research work, a comprehensive study has been carried out on machining of wrought aluminium from different points of view.