Tool Flank Research Articles

Identification of parameter-dependent machine learning models for tool flank wear prediction in dry titanium machining

This study uses machine learning (ML) techniques to predict maximum flank wear on cutting tools during the turning of Ti6Al4V, a titanium alloy known for its challenging machinability. We used three models (a) support vector machines (SVM), (b) random forests (RF), and (c) neural networks (NN) to predict maximum flank wear. The machining parameters are taken as input data sets, which compromise cutting speed, feed, and machining time. All the experiments are done at a constant depth of cut to predict maximum flank wear as an output variable. The forecasted maximum flank wear was validated using experimental data to verify their precision. The SVM model outperformed the other ML models in a wider range of cutting parameters concerning tool flank wear. The SVR model is the most accurate model with an average forecasting error of 3.24%. In forecasting maximum flank wear, the RF and NN models followed, with average forecasting errors of 3.88% and 3.71%, respectively. Additionally, the SVM model's robustness was further validated by its ability to maintain stability at varying cutting speeds and feed rates. The research enhances the economics of the machining process by predicting tool flank wear and fostering sustainability in the manufacturing industry, thereby demonstrating the applicability of ML techniques.

Towards sustainable machining: an experimental study of eco-friendly MQL and its impact on machinability and future opportunities

Abstract Enforcement of stricter environmental policies calls for alternative methods that could reduce the usage of cutting fluid during machining. Thus, dry machining and minimum quantity lubrication (MQL) machining are gaining practical importance. From this perspective, the development of new biodegradable MQL fluids and their performance assessment during machining is acquiring global attention. In this work, Jatropha crude oil (JCO) is chemically transformed into an epoxidized product and used as a MQL fluid. The turning experiments are conducted on Nimonic 80A under varying cutting speeds, and feed rates with constant depth of cut to examine the effects on machinability characteristics. The experiments are conducted under three different environments viz. dry, conventional minimum quantity lubrication (CMQL) and epoxidized minimum quantity lubrication (EMQL). The cutting force, tool flank wear, surface roughness and chip morphology are used as performance indicators. Regarding environmental concerns, the EMQL proved to be a viable substitute for CMQL as it demonstrated the lowest cutting force, tool wear and surface roughness. EMQL can reduce tool wear and surface roughness to the extent of about 54% and 22% as compared to the dry machining environment. The cutting force is reduced by about 13% and 34% by adopting CMQL and EMQL respectively even under the high feed (f = 0.45 mm min−1) condition. The sustainability assessment model developed using the Pugh matrix environmental approach disclosed EMQL system helps in attaining the desired machinability qualities while offering environmental friendliness and cleaner production.

PENGUJIAN CUTTER ENDMILL HSS DIAMETER 12 MM DENGAN PEMOTONGAN DEPT OF CUT TERHADAP BAJA AMUTIT DI MESIN MILLING LAGUN FU 100 (LFR 25)

This study aims to analyze the relationship between machining parameters and tool wear (flank wear) in the milling process of amutite steel (SKS3) using a 12 mm diameter High-Speed Steel (HSS) endmill cutter. The machining parameters studied included cutting speed (Vc = 14 m/min and 18 m/min), feed rate (F = 30 mm/min and 75 mm/min), and depth of cut (Doc = 0.5, 1, 1.5, 2 and 2.5 mm). The linear regression method was used to build a mathematical model relating these parameters to tool wear. Experimental data were obtained through a series of machining tests with predetermined parameter variations. The regression analysis results showed that tool wear or flank wear (Vb) was significantly affected by cutting speed (Vc), feed rate (F), and depth of cut (Doc), with constant and exponent values obtained through logarithmic transformation and regression analysis. The regression model obtained has a good level of accuracy in predicting tool wear, although there is a difference between the theoretical and actual Vb values. This discrepancy may be caused by factors not measured in the experiment, such as variations in workpiece material or environmental conditions. This research also provides that the 12 mm diameter HSS endmill cutter is proven to be capable of carrying out the depth-of-cutting process on amutite steel material in the Lagun FU 100 milling machine with the specified depth-of-cut.

Multi-objective Optimization of Turning Titanium Alloy by Grey Rational Analysis

In order to optimize the turning operation on titanium alloy, one needs to understand how different parameter combinations serve under varied conditions and needs. It is critical to compare single and multiple objectives in optimization. This study focused on single and multi-objective optimization evaluations for the primary performance responses of surface roughness (SR) and tool flank wear (TW), aiming for optimal turning process parameters. To examine the effects of feed rate (f), cutting speed (R), depth of cut (d), cutting angle (X), and mist inlet pressure (P) on the responses of both SR and TW, Taguchi L27 orthogonal arrays were used in this study. Moreover, analysis of variances (ANOVA) and grey relational analysis (GRA) have been incorporated in this study, where the former was used to study the influence of each parameter on SR and TW while the latter was used to determine the best combinations for the multi-objective optimization process. The results revealed that for single-objective optimization of SR, the optimal values for f, R, d, X, and P were found to be 0.3 mm/rev, 250 rpm, 1.5 mm, 100 degrees, and 1 bar mist inlet pressure, respectively. For single-objective optimization of TW, the optimal values for f, R, d, X, and P were found to be 0.20 mm/rev, 250 rpm, 0.5 mm, 50 degrees, and 3 bar mist inlet pressure, respectively. Meanwhile, for multi-objective optimization, the optimal values for f, R, d, X, and P were found to be 0.30 mm/rev, 500 rpm, 2.0 mm, 75 degrees, and 1 bar mist inlet pressure, respectively. These optimal combinations of turning parameters resulted in the lowest SR and TW simultaneously.

Performance analysis of uncoated and coated (TiN-, TiAlN-) carbide drills in drilling graphene-reinforced GF/epoxy nanocomposites: Analytical and experimental study

The present study aims to investigate the performance of conventional uncoated and coated (TiN, TiAlN) solid carbide drill tools in drilling bi-directional graphene-reinforced (2 wt.%) glass fiber (GF)/epoxy polymer nanocomposite laminate with two distinct lamination schemes ([0/90]12S and [0/90/±45]6S). Performance measures included thrust force, torque, tool flank wear, peak acoustic emission, root mean square (RMS) of acoustic energy, and average surface roughness. Moreover, the delamination that occurs beyond the critical value of thrust force (computed analytically) has also been addressed. Optimized drilling parameters were used for experimentation to minimize thrust force and torque simultaneously. Both TiN and TiAlN-coated carbide drills outperformed uncoated carbide drills for fewer holes (around 25 for TiN and about 40 for TiAlN), but their performance deteriorated with more holes due to coating chipping or peeling from the original tool material. The (0/90 ± 45)6S graphene-reinforced layup showed less tool wear, deterioration, and acoustic emission energy compared to the (0/90)12S neat layup. TiAlN-coated drills exhibited the smallest wear on the flank face followed by TiN-coated and uncoated carbide drills. Moreover, the smoothest cut surface throughout the 300 holes drilled, averaging 1.5 µm to 1.8 µm in surface roughness, was observed with the TiAlN-coated drill. Therefore, the TiAlN-coated drill is recommended for drilling a larger number of holes due to its reduced tool wear, smoother cut surfaces, and better form accuracy with minimal delamination.

Analyzing the correlation between tool vibration and flank wear in face milling of EN-31 steel employing the CRITIC approach

Analyzing the correlation between tool vibration and flank wear in face milling of EN-31 steel employing the CRITIC approach

A novel procedure to predict cumulative tool wear in turning based on experimental analysis

A novel procedure to predict cumulative tool wear in turning based on experimental analysis

Tool Wear Prediction Combining Global Feature Attention and Long Short-Term Memory Network

This study aims to accurately predict tool flank wear in milling and simplify the complexity of feature selection. A hybrid approach is proposed to eclectically integrate the advantages between the long short-term memory (LSTM) network and the global feature attention (GFA) module. First, the feature matrix is calculated using the multi-domain feature extraction method. Subsequently, a parallel network is employed to achieve feature fusion. The stacked LSTM network extracts the temporal dependencies between features and the GFA module is used to adaptively complement key features representing global information of samples. Finally, the output features are concatenated, and tool wear prediction is achieved through a fully connected layer. Experiments demonstrate the optimal performance in predicting tool flank wear. Specifically, using the proposed GFA-LSTM framework reduces the mean absolute error (MAE) by 36.9%, 17.7%, and 25.2% in three experiments compared to the simple LSTM, validating the effectiveness of the proposed method.

Investigating the effect of nanobubble-based cutting fluid on tool wear and cutting forces in milling of Inconel 718

Investigating the effect of nanobubble-based cutting fluid on tool wear and cutting forces in milling of Inconel 718

PERFORMANCE ANALYSIS OF AISI 4340 HARDENED STEEL IN DUAL JET MQL TURNING SYSTEM: A COMPARISON STUDY BETWEEN CVD AND PVD-COATED CARBIDE TOOLS

The hard part turning process used to finish the cylindrical surfaces has some critical machining responses like tool wear with the lower quality of the machined surfaces. Minimum quantity lubrication (MQL)-based machining environment is currently considered an advanced cooling and lubrication technique. Cutting speed, feed rate, and cutting depth are considered input parameters, and the TaguchiL27 orthogonal array (OA) has been adopted as the design of the experiment. In this context, average surface roughness ([Formula: see text]), tool flank wear (VBc), cutting temperature ([Formula: see text]C), and chip morphology have been selected as measured outputs. To improve the machining performance of hardened steel, a sustainable MQL ([Formula: see text] directions) cooling system has been employed at the cutting zone. Iron–aluminum LRT 30 was considered as the base fluid for the hard turning of AISI 4340 steel by PVD (AlTiN) and CVD (TiN/TiCN/Al2O3) coating cutting inserts. The primary effects of process parameters and their influences on the measured outputs have been discussed. The dual jet MQL-based hard turning was performed at three levels of cutting speeds (80, 170, and 260[Formula: see text]m/min), feed rate (0.5, 0.1, and 0.15[Formula: see text]mm/rev), and cutting depth (0.2, 0.3, and 0.4[Formula: see text]mm) with an air pressure of 5[Formula: see text]bar and mist flow rate 50[Formula: see text]ml/h. The findings showed that PVD-coated carbide tools outperformed CVD-coated tools. The model of the measured outputs of both tools has been developed using second-order regression analysis. Utilizing ANOVA analysis, all the predictive models were observed to be significant and acceptable with larger than 90% of [Formula: see text] value.

Application of Image Processing for Tool Flank Wear Measurement and Optimization Using the Taguchi Method

Application of Image Processing for Tool Flank Wear Measurement and Optimization Using the Taguchi Method

Study of the influence of cutting parameters on tool wear and the state of the machined surface

This work presents a study of wear on the clearance face of turning tools. This study will contribute to the development of improved machining precision and efficiency while extending tool life and also ensuring the surface quality produced, despite wear and edge deposition phenomena. A tool flank wear model is developed as a function of the cutting conditions, including the cutting speed, depth of cut, feed rate, and machining time. Factors influencing tool clearance face wear are determined through experimental testing. We also investigate the edge phenomenon reported on the tool cutting face by plotting a curve of the edge variation versus the machining time. Tool wear and built-up edge phenomena both affect the quality of the surface finish produced. Additionally, the edge phenomenon degrades the geometric quality of the tool and generates wear on the tool clearance face. Therefore, models are developed to aid in selection of appropriate cutting conditions that ensure the expected surface finish is realized while also providing control over tool wear. Overall, this method combines experimental and theoretical approaches to study and control turning tool wear with the aim of improving both machining quality and efficiency.

Investigations on the machinability performance of Al2O3/TiCN CVD coated carbide tools in sustainable high-speed hard-turning of AISI 4340 alloy steel

Abstract This study investigates the effectiveness of CVD coated carbide inserts in turning hardened AISI 4340 steel at high-machining speed V=300,350m/min under sustainable dry cutting environment. Experiments were executed in accordance to Taguchi L4 orthogonal array and crucial machinability aspects tool life, tool wear progression and mechanism, cutting force, and surface roughness were evaluated in detail. The results of this study revealed that Al2O3/TiCN coating successfully inhibited the faster progression of tool wear at low cutting speed (300m/min), feed rate (0.05mm/rev) and depth of cut (0.1mm), thus delivering the highest tool life of 19.25 min and lowest cutting force of 76.8 N. However, better surface finish of 0.305µm was obtained at high cutting speed (350m/min), low feed rate (0.05mm/rev), and high depth of cut (0.1mm). Nevertheless, at high cutting speed (350 m/min) and feed rate (0.1 mm/rev), involvement of intense thermal-mechanical effects suppressed the effectiveness of coating and tool completed its useful life at 9.24 min. Severe flaking on the cutting edge was observed at high machining parameters. Scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) analysis revealed that adhesion, oxidation, and small scale chipping and abrasion were the primary wear mechanisms attributing in competing the tool life criteria (Vb=300µm) in all cutting conditions. Furthermore, it was established that the cutting force and surface roughness increased with increasing tool flank wear due to coating delamination, material adhesion and tool chipping. This research emphasizes the significant potential of adopting Al2O3/TiCN coated carbide inserts for high-speed industrial hard-turning of AISI 4340 steel.

Effect of structure tool on nano-cutting surface integrity of single crystal γ-TiAl alloy via atomic simulation

Effect of structure tool on nano-cutting surface integrity of single crystal γ-TiAl alloy via atomic simulation

Tribological behavior of Inconel 718 alloy when cutting with a carbide insert prepared using the SPS technique under dry and lubricated sliding conditions

Tribological behavior of Inconel 718 alloy when cutting with a carbide insert prepared using the SPS technique under dry and lubricated sliding conditions

Effects of longitudinal ultrasonic vibration on tool wear behaviors in side milling of GH4169D superalloy

Effects of longitudinal ultrasonic vibration on tool wear behaviors in side milling of GH4169D superalloy

Evaluation of tool wear during micro-milling of ultrasonically assisted abrasive peened Ti-6Al-4V

Evaluation of tool wear during micro-milling of ultrasonically assisted abrasive peened Ti-6Al-4V

The Dynamic Comprehensive Evaluation of the Importance of Cutting Parameters in the Side Milling TC4 Process Using an Integrated End Mill.

In the cutting process, there are many parameters that affect the cutting effect, and the same parameter has different degrees of influence on different performance indicators, which makes it difficult to select key parameters for parameter optimization and parameter combination evaluation while considering multiple performance indicators at the same time. The process of titanium alloy milling with an integrated end mill is studied herein. The values of cutting tool flank face wear and material removal rates are obtained with experimental and analytical methods. Numerical characteristics and causes of the cutting tool flank face wear at different stages are also analyzed. The dynamic, comprehensive evaluation method based on the double incentives model is used to evaluate the dynamic, comprehensive importance of cutting parameters in view of the problem of considering multiple performance indicators and the characteristics of the dynamic change in performance indicators in the cutting process. According to the result of a dynamic, comprehensive evaluation, the cutting parameters with the highest comprehensive importance are selected. Finally, the radar map is used to plot the comprehensive importance of the cutting parameters. The overall comprehensive importance of each cutting parameter is intuitively displayed as well. As a result of the research, the dynamic, comprehensive evaluation method based on the double incentives model has a good application value in the evaluation of tool performance in the cutting process and can quickly select the best tool performance parameter combination; it is established that the most comprehensive parameter is the cutting speed, and the cutting width is the second most important. In turn, the comprehensive importance of the cutting depth is the lowest.

Influence of tool flank wear considering tool edge radius on instantaneous uncut chip thickness and cutting force in micro-end milling

Influence of tool flank wear considering tool edge radius on instantaneous uncut chip thickness and cutting force in micro-end milling

The Influence of nc-AlCrTiN/α-BN Coatings on Increasing the Durability of WC/Co Cutting Inserts in the Inconel Alloy Machining Process.

Anti-wear coatings obtained through PVD methods may significantly increase the durability of cutting tools by impacting their wear mechanisms. This study presents and discusses the results of studies on the impact of the thermal conductivity of PVD coatings on the intensity of the built-up edge (BUE) and built-up layer (BUL) formation in Inconel 600 alloy machining processes. The authors determine the microstructure, phase structure, mechanical properties (hardness, Young's modulus, and adhesion), and thermal conductivity of different PVD coatings selected for the purpose of the study and varying in terms of conductivity-i.e., AlCrTiN and AlCrTiN/BN. Machining processes were carried out under controlled conditions using VBGT160404-M3 cutting inserts with AlCrTiN and AlCrTiN/BN coatings deposited on their surface. The authors prove that the adjustment of the thermal conductivity of PVD coatings to the thermal conductivity of the tool and machined materials can help change the direction of heat flow to cool the cutting zone more effectively. The study results presented in this article show that the deposition of the AlCrTiN/BN coating reduces the friction wear on the tool flank by over 70% and lowers the intensity of BUE and BUL formation processes on the face by 10%, compared to the AlCrTiN coating.