Flank Wear Of Cutting Tool Research Articles

Parametric optimization to establish eco-friendly nanofluid minimum quantity lubrication (NMQL) practice for turning superalloy Inconel 718

Purpose The purpose of this paper, an experimental study, is to investigate the optimal machining parameters for turning of nickel-based superalloy Inconel 718 under eco-friendly nanofluid minimum quantity lubrication (NMQL) environment to minimize cutting tool flank wear (Vb) and machined surface roughness (Ra). Design/methodology/approach The central composite rotatable design approach under response surface methodology (RSM) is adopted to prepare a design of experiments plan for conducting turning experiments. Findings The optimum value of input turning parameters: cutting speed (A), feed rate (B) and depth of cut (C) is found as 79.88 m/min, 0.1 mm/rev and 0.2 mm, respectively, with optimal output response parameters: Vb = 138.633 µm and Ra = 0.462 µm at the desirability level of 0.766. Feed rate: B and cutting speed: A2 are the leading model variables affecting Vb, with a percentage contribution rate of 12.06% and 43.69%, respectively, while cutting speed: A and feed rate: B are the significant factors for Ra, having a percentage contribution of 38.25% and 18.03%, respectively. Results of validation experiments confirm that the error between RSM predicted and experimental observed values for Vb and Ra is 3.28% and 3.75%, respectively, which is less than 5%, thus validating that the formed RSM models have a high degree of conformity with the obtained experimental results. Practical implications The outcomes of this research can be used as a reference machining database for various metal cutting industries to establish eco-friendly NMQL practices during the turning of superalloy Inconel 718 to enhance cutting tool performance and machined surface integrity. Originality/value No study has been communicated till now on the turning of Inconel 718 under NMQL conditions using olive oil blended with multi-walled carbon nanotubes-based nanofluid. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2023-0317/

Influence of singular and dual MQL nozzles on sustainable milling of Al6061-T651 in different machining environments

Al6061-T651 alloy is widely used in the aerospace industry due to its superior properties and is a very difficult-to-cut material with high quality because of tool wear and thermal softening. This situation causes low surface quality, high cutting force, and limited tool life, as well as an increase in total consumed energy, total carbon dioxide emission, and total machining cost. Therefore, it is necessary to sustainably increase this aerospace alloy's machining performance. In the presented study, for the first time, milling performance and sustainability assessment of Al6061-T651 alloy under dry, minimum quantity lubrication (MQL), nano molybdenum disulfide (MoS2) reinforced nanofluid-assisted MQL (N-MQL) cutting conditions were investigated using the single nozzle and dual nozzles, two different MQL flow rates, and three different cutting speeds. In this context, the results of surface roughness, cutting force, feed force, cutting tool flank wear, total consumed energy, total carbon emission, and total machining cost were obtained. As the cutting speed increased, the cutting force, feed force, total consumed energy, total machining cost, and total carbon emission decreased by 12.9 %, 18 %, 7.8 %, 6 %, and 0.1 %, while the surface roughness increased by 34.9 %. In the MQL and MoS2 N-MQL cutting conditions at the same flow rate, using dual nozzles instead of a single nozzle improved machining response and sustainability indicators. In addition, increasing the flow rate improved machining performance and sustainability indicators. Using the double nozzle MoS2 N-MQL method reduced the surface roughness, cutting force, feed force, flank wear, total consumed energy, total carbon emission, and overall machining cost by 74.2 %, 63.9 %, 68.4 %, 66 %, 27.9 %, 0.4 %, and 6.39 %, respectively.

Determination of machinability metrics of AISI 5140 steel for gear manufacturing using different cooling/lubrication conditions

AISI 5140 steel is mostly used in gear manufacturing for variety of industries. Those gears can be manufactured via casting, powder metallurgy or forging techniques. Nevertheless, machining (via turning and milling processes) remains the most common manufacturing method to fabricate them. Milling of gears made from 5140 steel can be challenging due to the excessive energy consumption, rapid tool wear and poor surface finish. Therefore, traditional and environmentally friendly coolants are usually applied during machining to improve the surface finish and prolong tool life. The current study aims to investigate machinability performance of 5140 steel under different cooling/lubrication conditions. Several machinability metrics were investigated and analyzed (surface roughness, cutting temperature, tool wear, chip morphology, and energy consumption). Milling tests were performed under different cutting speeds (75 and 100 m/min), different feed rates (0.15 and 0.2 mm/rev) and dry, minimum quantity lubrication (MQL), and cryogenic liquid cooling/lubrication conditions (dry, MQL and cryo-LN2). The results showed that using Cryo-LN2 cooling/lubrication tended to improve all the investigated machinability metrics compared to dry condition. The surface roughness was reduced by approximately 54%, while the cutting temperature was reduced by 87%. Similarity, the cutting tool flank wear was reduced by 20% thus energy consumption was minimized by 15%. The current study shows the importance of cryogenic machining in industry for difficult to cut materials.

Investigation of tool flank wear effect on system stability prediction in the milling of Ti-6AI-4 V thin-walled workpiece

Excessive tool wear can shorten tool life and cause low machining surface quality and efficiency in the milling of Ti-6AI-4 V thin-walled workpieces. The influence mechanism between the tool flank wear and stability predication is of significant for its further development in milling Ti-6Al-4 V. However, the relationship between tool flank wear and stability predication needs to be further investigated as the effect of time-varying tool flank wear is ignored in conventional methods. In this work, a system stability prediction model considering time-varying tool flank wear effect in milling of Ti-6AI-4 V thin-walled workpiece is proposed. The tool flank wear region is discretized into differential elements, and then, the friction effect and process damping effect caused by extruding function between tool and workpiece are analyzed, and a time-varying milling force model is established. In this process, the relationship of cutting tool flank wear band width VB and section radius difference NB is determined, and the indentation volume between tool and workpiece is iteratively calculated, which is used to investigate process damping. After, the time-varying milling force coefficients are derived considering different tool flank wear status. Then, in modal space, the evolutionary process of stability lobe diagrams considering tool flank wear effect is determined. Subsequently, to effectively predict system stability, tool flank wear curves and dynamic cutting force coefficients are calibrated by slot milling, and the average errors between cutting force prediction values considering tool flank wear effect and experimental values in feed direction and normal direction are 7.3% and 12.1%, respectively. Finally, a series of machining tests are conducted to verify the effectiveness of tool flank wear on the machining stability in the milling of Ti-6AI-4 V thin-walled workpieces to some extent, and the experimental results show that the system stability prediction accuracy of the proposed method is improved by 23.8% compared with that using conventional method.

Parametric Optimization and Modeling for Flank Wear of Tisin-Tialn Nanolaminate Cutting Insert

Selection of machining parameters and better prediction for cutting tool flank wear is indispensable in hard machining as flank wear is directly influences the quality of machined surface. In the current study, parametric optimization and predictive model were carried out for the flank wear of TiSiN-TiAlN nanolaminate cutting insert in hard turning of 58 HRC AISI 1045 medium carbon steel which is an unexplored area. Taguchi’s method was employed for parametric optimization and predictive model was established for flank wear by response surface methodology (RSM) based regression analysis. Cutting speed = 40 m/min, feed rate = 0.3 mm/rev and depth of cut = 75µm generates optimum value of flank wear 0.07 mm. In conclusion, verification test was carried out to validate the optimal set of parameters and the result was shown a great reduction of 81.42% in the flank wear. The predictive model elaborated for flank wear was dependable and helps to make better prediction to the manufacturing industries within specified range of the experimentation.

Modeling and optimization for surface roughness and tool flank wear in hard turning of AISI 4340 steel (35 HRC) using TiSiN-TiAlN nanolaminate coated insert

PurposeThe present study spotlights the single and multicriteria decision-making (MCDM) methods to determine the optimal machining conditions and the predictive modeling for surface roughness (Ra) and cutting tool flank wear (VB) while hard turning of AISI 4340 steel (35 HRC) under dry environment.Design/methodology/approachIn this study, Taguchi L16 design of experiments methodology was chosen. The experiments were performed under dry machining conditions using TiSiN-TiAlN nanolaminate PVD-coated cutting tool on which Taguchi and responses surface methodology (RSM) for single objective optimization and MCDM methods like the multi-objective optimization by ratio analysis (MOORA) were applied to attain optimal set of machining parameters. The predictive models for each response and multiresponse were developed using RSM-based regression analysis. S/N ratios, analysis of variance (ANOVA), Pareto diagram, Tukey's HSD test were carried out on experimental data for profound analysis.FindingsOptimal set of machining parameters were obtained as cutting speed: at 180 m/min., feed rate: 0.05 mm/rev., and depth of cut: 0.15 mm; cutting speed: 145 m/min., feed rate: 0.20 mm/rev. and depth of cut: 0.1 mm for Ra and VB, respectively. ANOVA showed feed rate (96.97%) and cutting speed (58.9%) are dominant factors for Ra and VB, respectively. A remarkable improvement observed in Ra (64.05%) and VB (69.94%) after conducting confirmation tests. The results obtained through the MOORA method showed the optimal set of machining parameters (cutting speed = 180 m/min, feed rate = 0.15 mm/rev and depth of cut = 0.25 mm) for minimizing the Ra and VB.Originality/valueThis work contributes to realistic application for manufacturing industries those dealing with AISI 4340 steel of 35 HRC. The research contribution of present work including the predictive models will provide some useful guidelines in the field of manufacturing, in particular, manufacturing of gear shafts for power transmission, turbine shafts, fasteners, etc.

Effect of MQL flow rate on machinability of AISI 4140 steel

Many studies were performed about the influence of minimum quantity lubrication (MQL) technique on cutting performance in the literature, but there is no paper examining the effect of different MQL flow rates and cutting parameters on machinability of AISI 4140 material as a whole. In this study, the effects of different MQL flow rates and cutting parameters on surface roughness, main cutting force and cutting tool flank wear (VB), with great importance among the machinability criteria, and forming as a result of the machining of AISI 4140, were revealed. At the end of the experiments, it was determined that rise of flow rate affected main cutting forces positively to a certain extent; yet, it exhibited no significant effect on surface roughness, but reduced VB. Also, it was observed that both main cutting force and surface roughness increased with the increase of feed, while generally decreased with the increase of cutting speed. It was seen that flank wear was positively affected by the increase in flow rate; and this decreased with the increase in flow rate. R2 values obtained as 99.8% and 99.9% for main cutting forces and surface roughness values modeled statistically with the help of quadratic equations, respectively.

The influence of ultrasonic elliptical vibration amplitude on cutting tool flank wear

In this article, the effect of vibration amplitude during ultrasonic elliptical vibration–assisted turning on cutting tool flank wear ( VBmax) and tool diffusion wear mechanism has been experimentally studied in machining of AISI 4140 hardened steel. To achieve this goal, an ultrasonic elliptical vibration–assisted turning setup was designed and manufactured. This device was then used in both ultrasonic-assisted tuning and ultrasonic elliptical vibration–assisted turning tests (i.e. one-dimensional and two-dimensional ultrasonic-assisted machining). According to the achieved results, ultrasonic elliptical vibration–assisted turning is more effective than ultrasonic-assisted tuning in reducing tool flank wear; at an amplitude of 13 μm, work velocity of 180 mm/s and feed of 0.09 mm/rev, VBmax were decreased 30.3% and 54.3%, respectively, in case of ultrasonic-assisted tuning and ultrasonic elliptical vibration–assisted turning. It was also observed that increasing the amplitude of ultrasonic vibrations reduces VBmax; at work velocity of 180 mm/s and feed of 0.09 mm/rev, the reduction of VBmax in ultrasonic elliptical vibration–assisted turning with amplitudes of 5 and 13 μm is, respectively, 39.3% and 54.3%, compared with that of conventional machining. The results also show that the application of ultrasonic vibrations weakens the cutting tool diffusion wear mechanism. This attenuation is much higher for ultrasonic elliptical vibration–assisted turning in comparison to ultrasonic-assisted tuning. Besides, the amount of attenuation in cutting tool diffusion wear mechanism decreases with increasing vibration amplitude.

Use of Longitudinal Roughness Measurements as Tool End-of-Life Indicator in AISI 1045 Dry Longitudinal Turning

The important portion of machining costs associated with cutting inserts and scraps induces the search for better effectiveness in turning. This paper presents the results of an exploratory study on the influence of tool flank wear on roughness indicators (arithmetic average roughness, root mean square roughness and maximum height of the roughness profile). The objective is to determine which of these indicators is best correlated with the cutting tool flank wear. In order to do this, specimens of AISI 1045 are machined until the end of life of a cutting insert. Significant, strong and positive correlations are found between all three roughness indicators and the tool flank wear. The most significant correlation is found with the arithmetic average roughness and the root mean square roughness of the profile. The choice of the end-of-life criteria for cutting inserts in industrial contexts is also discussed.

Investigation of Cutting Performance for NAK80 Hardened Steel under Different Assisted Machining Systems

In this study, five different assisted techniques, including without assistance, laser-assisted, flood assisted, MQL-assisted and cold air-assisted were employed for NAK80 mold steel milling. The 18 set experiments were performed in each assisted system but 27 sets were executed in the without assistance situation. Under each assisted milling circumstance, the effects of process parameters on the variations of surface roughness, cutting force, tool wear and surface morphology of the workpiece are thus investigated. Milling experiments of NAK80 mold steel by cutting-tool of extra-fine particle tungsten carbide with TiSiN coating were conducted. And the experiments of the process parameter combinations such as spindle speed, feed rate and radial depth of cut were also planned. The results show that, under the same milling conditions, the surface roughness and cutting force are decreased as the spindle speed is increased, but both of them is increased as the feed rate and radial cutting depth are increased. In addition, the maximum flank wear of the cutting-tool is increased as the spindle speed, feed rate and radial cutting depth are increased. In terms of cutting assistance, the cutting performance exhibited in the cold air-assisted milling prevails over that in milling without assistance as well as with the other each assisted system. As a result, the cutting-tool flank wear, surface roughness and cutting force are all better than the other assisted techniques.

Experimental and theoretical analysis of tool life between plasma enhanced CVD and PVD multilayer nanocoated cutting tools

Tool life of the traditional cutting tools is comparatively lesser on machining the martensitic stainless steel AISI 416 which is one of the hardest materials. In order to increase the tool life, wear-resistant nanocoatings on the cutting tools have been explored. This study enunciates a comparison of tool life between PECVD (plasma-enhanced CVD multilayer nanocoated) and PVDMNC (PVD multilayer nanocoated) cutting tools on turning a martensitic stainless steel AISI 416 by experimental and theoretical investigations in addition to exploration of the machinability studies of cutting tool flank wear, tool hardness and surface roughness of work material. An orthogonal design, signal-to-noise ratio and Analysis of Variance (ANOVA) methods were employed to confirm the parameters like cutting speed, tool hardness and feed rate that are involved in the study to estimate the cutting tool- life. The investigations confirmed that cutting speed was the most dominant factor in determining tool life while comparing with other parameters. It was observed from the ANOVA results that the cutting speed, tool hardness, and feed rate have contributed 41.44%, 33.79%, and 24.35% respectively in determining the tool life of PECVD cutting tools whereas the contributions of the same parameters were found to be 40.01%, 32.90%, and 26.63% respectively for PVDMNC cutting tool. It is evident from the results that the cutting performance of the PECVD cutting tool is superior in terms of cutting speed and hardness which were enhanced by 1.43% and 0.89% respectively in addition to lesser wear rate when compared to the performance of PVDMNC cutting tools.

Tool Condition Monitoring While Using Vegetable Based Cutting Fluids During Milling of Inconel 625

This investigation has designed a tool condition monitoring system (TCM) while milling of Inconel 625 based on sound and vibration signatures. The experiments were carried out based on response surface methodology (RSM) central composite design, design of experiments. The process parameters such as speed, feed, depth of cut and vegetable-based cutting fluids were optimized based on surface roughness, flank wear. It was found that the sound pressure and vibration signatures have the direct relation with flank wear. The statistical features like root mean square, skewness, kurtosis and mean values were extracted from the experimental data. From the designed NN estimator, the cutting tool flank wear was predicted with the mean square error (MSE) of 0.084212.

Experimental Investigation on Cutting Tool Performance of Newly Synthesized P/M Alloy Steel Under Turning Operation

Components processed through powder metallurgy (P/M) route replace the parts in many of the industrial sectors. The present work focuses on cutting tool characteristics of a newly synthesized Fe–1%C–1%W–1%Ti P/M alloy steel for turning of AISI 1020 steel. In this work, the cutting tool behaviour of P/M tool is also compared with conventional high-speed steel tool. $$\hbox {L}_{{9}}$$ orthogonal array design matrix is employed in conducting experiments in an all-geared headstock lathe. The selected cutting speed, feed rate and depth of cut are used as the influencing parameters in turning AISI 1020, and the cutting tool behaviours of P/M alloy steel tool are evaluated concerning surface finish and tool flank wear. The outcome of the present work reveals that the tool processed through P/M route has exhibited better performance compared to the HSS cutting tool. ANOVA and signal-to-noise ratio were employed to study the effects and contributions of working parameters on the surface finish and cutting tool flank wear of the component. The performance analyses have shown that the cutting speed and feed rate are the most dominant factors for the tool wear and surface finish, respectively. The confirmation test has ensured the validity of the regression model developed in the present work.

Influence of nanolubricant particles’ size on flank wear in hard turning

ABSTRACTThis paper presents the effects of cutting speed, nanoparticles’ size, and their concentration in water-based TiO2 nanofluid on the magnitude of tool flank wear and tool wear rate. The types of nanoparticles and base fluid, nanoparticle size, and nanoparticle concentration can affect the tribological and heat transfer properties of nanofluids, and thereupon, these parameters can affect the cutting forces and temperatures during the metal cutting process, thereby affecting tool wear and nanolubricant consumption. According to the achieved results, with an increase in the size of nanoparticles from 10 to 50 nm, the average decrease in cutting tool flank wear reduces from 46.2% to 34.8%.

Investigation into the effectiveness of cutting parameters on wear regions of the flank wear curve and associated cutting tool life improvement

In machining operations, less tool wear and superior tool life are desired. Therefore, the effects of cutting parameters on tool life should be known and optimal cutting parameters should be chosen to reduce tool wear. In this study, the effectiveness values of cutting parameters on each wear region in the cutting tool flank wear curve were investigated to improve cutting tool service life. For this reason, some statistical methods were employed to determine them and the results were verified by experimental studies. In the initial tool wear and the rapid tool wear regions, the most effective parameter was found as the feed and the tool wear increased with increase of the feed. In the steady-state tool wear region, the effectiveness values of the cutting speed and the feed were very close to each other, but the cutting speed was determined a little more effective.

Effecton Surface Properties OF Mild Steel During Dry Turning & Wet Turning On Lathe

In order to tackle a multi-objective optimization problemwhich seeks identification of the best process condition or parametric combination for the manufacturing processes, dry and wet turning, In the present experiment investigation on straight turning of mild- steel bar by using HSS tool. The experiment aimed at evaluating the best process environment which could simultaneously satisfy requirements of both quality and as well as productivity with special emphasis on reduction of cutting tool flank wear. Because reduction in flank wear ensures increase in tool life. The predicted optimal setting ensured minimization of surface roughness, height of flank wear of the cutting tool and maximization of MRR (Material Removal Rate).The experimental analysis showed that surface properties of mild steel improved when wet turning was carried out instead of dry turning.

On-machine tool prediction of flank wear from machined surface images using texture analyses and support vector regression

In this paper, a method for on-machine tool condition monitoring by processing the turned surface images has been proposed. Progressive monitoring of cutting tool condition is inevitable to maintain product quality. Thus, image texture analyses using gray level co-occurrence matrix, Voronoi tessellation and discrete wavelet transform based methods have been applied on turned surface images for extracting eight useful features to describe progressive tool flank wear. Prediction of cutting tool flank wear has also been performed using these eight features as predictors by utilizing linear support vector machine based regression technique with a maximum 4.9% prediction error.

Research on the Cutting Property of Ceramic Tool Cutting Nickel Based Superalloy GH4169

This paper will use the Al2O3-SiCw whisker toughening ceramic tool WG300 and Si3N4-Al2O3 (Sialon) SX9 ceramic tool cutting performance test.Study on different cutting speed, ceramic cutting tool in machining nickel based high-temperature alloy tool life and tool wear mechanism, and analysis of the wear form under different cutting parameters. The test results show that: with the increase of the cutting speed, WG300 and SX9 two kinds of tool durability showed a downward trend, the value of VB is higher than that of Al2O3-SiCw whisker reinforced ceramic cutting tool flank wear of Sialon ceramic cutting tool, but its notch wear value VN is far less than Al2O3-SiCw whisker reinforced ceramic cutting tool,the main failure form of WG300 notch wear, the main failure form of SX9 for the flank wear.

Progressive cutting tool wear detection from machined surface images using Voronoi tessellation method

Tool condition monitoring by machine vision approach has been gaining popularity day by day since it is a low cost and flexible method. In this paper, a tool condition monitoring technique by analysing turned surface images has been presented. The aim of this work is to apply an image texture analysis technique on turned surface images for quantitative assessment of cutting tool flank wear, progressively. A novel method by the concept of Voronoi tessellation has been applied in this study to analyse the surface texture of machined surface after the creation of Voronoi diagram. Two texture features, namely, number of polygons with zero cross moment and total void area of Voronoi diagram of machined surface images have been extracted. A correlation study between measured flank wear and extracted texture features has been done for depicting the tool flank wear. It has been found that number of polygons with zero cross moment has better linear relationship with tool flank wear than that of total void area.

Online Cutting Tool Wear Monitoring Using I-Kaz Method and New Regression Model

This study presents a new method for detecting the cutting tool wear based on the measured cutting force signals using the regression model and I-kaz method. The detection of tool wear was done automatically using the in-house developed regression model and 3D graphic presentation of I-kaz 3D coefficient during machining process. The machining tests were carried out on a CNC turning machine Colchester Master Tornado T4 in dry cutting condition, and Kistler 9255B dynamometer was used to measure the cutting force signals, which then stored and displayed in the DasyLab software. The progression of the cutting tool flank wear land (VB) was indicated by the amount of the cutting force generated. Later, the I-kaz was used to analyze all the cutting force signals from beginning of the cut until the rejection stage of the cutting tool. Results of the I-Kaz analysis were represented by various characteristic of I-kaz 3D coefficient and 3D graphic presentation. The I-kaz 3D coefficient number decreases as the tool wear increases. This method can be used for real time tool wear monitoring.