Tool Tip Temperature Research Articles

Dry machining of Inconel 718 super alloys using uncoated tool: Experimental and numerical analysis

Aerospace super alloy Inconel 718 is difficult to process through conventional machining operation. Alloys with high strength at high temperatures and high strain hardening, high chemical affinity (towards tool material, and Co binder) etc. impose adverse effects towards smooth machining. Poor thermal conductivity of Inconel 718 promotes excessive temperature rise at the chip-tool interface which causes rapid tool wear, and degraded surface integrity of the end product. Adequate understanding of machining process phenomena along with precise control of machining parameters may yield satisfactory result. Trial, and error experimentation is indeed uneconomical; hence, in the present reporting, Finite Element (FE) based numerical simulation is attempted to model machining responses in the extent of cutting force, tool-tip temperature, depth of flank wear progression, chip-tool contact length, and finally, chip reduction coefficient. Simulation results are verified through experimental tests. Simulation results are found in good agreement with experimental results. Therefore, simulation results can reliably be used as an alternative instead of actual experimental effort.

Investigation of the effects of constitutive law on numerical analysis of turning processes to predict the chip morphology, tool temperature, and cutting force

Turning process is one of the most complex manufacturing processes to simulate. The ability to accurately simulate turning processes depends on the availability of accurate workpiece material properties as well as the workpiece flow stress behavior change with deformation parameters such as strain, strain rate, and temperature. The goal of this paper is to determine the parameters of constitutive equation of flow stress for hardened AISI630 steel according to Johnson-Cook (JC) and power viscosity law (PVL) models. The numerical analysis of turning process has been done based on the finite elements method (FEM). Predicted results have been compared with experimentally determined data like, cutting force, tool tip temperature, and chip shape to validate the FE models. The numerical simulation results indicate that the adeptness of PVL model in forecasting the plastic behavior of AISI630 steel is quite acceptable and the predicted results are very close to experimental results in comparison with JC model. In addition, the results showed that the serrated chip morphology was accurately predicted over a large range of machining parameters using PVL model. Furthermore, FE analysis and PVL model have been used to predict cutting forces and tool temperature during different turning conditions. It has been found that for low feed rates, the chip form will be changed from continuous to saw-tooth form, e.g., at 0.1 mm/rev feed, with increasing cutting speed from 28 to 62 m/min the chip form was changed from continuous to saw-tooth type. In addition, during machining at cutting speed of 28 m/min, the cutting force is stable, while at cutting speed of 62 m/min, the resultant cutting force is fluctuating. This fluctuating force along with the build-up edge formation increases machined surface roughness at a speed of 62 m/min unexpectedly.

Simulation and experimental researches on the substrate temperature distribution of the large-capacity HFCVD setup for mass-production of diamond coated milling tools

To improve the precision and homogeneity for mass-production of HFCVD diamond coated milling tools, the simulation of substrate temperature field generated by the HFCVD setup was conducted, adopting a 3D simulation model well in accordance with the actual equipment. Firstly, the deviation of the simulation model is assessed by comparing the simulated temperature and measured temperature based on a validation test. The comprehensive influences of various critical setup parameters on the fabrication of diamond coatings are illustrated systematically according to the Taguchi simulation scheme (L16, five factors and four levels), including the filament diameter d, the filament temperature Tf, the separation between two adjacent filaments D, the filament height H, and the material of sample holder M, in order to obtain an optimal HFCVD setup. The results indicate that filament diameter d and the separation between two adjacent filaments D can effectively contribute to adjusting the average temperature; the distance between filaments and tool tips H, and the material of sample holder M exhibit remarkable effects on the temperature uniformity; the filament temperature Tf shows obvious influences on both the average temperature and the temperature uniformity. Furthermore, the optimal HFCVD setup has been proposed, based on which a more uniform temperature field around all the tool tips can be acquired, contributing to the mass-production of high-quality and high-precision diamond coated milling tools. Afterwards, the mass-production experiments of depositing MCD and NCD diamond coatings on WC-6% Co milling tools were conducted in the actual HFCVD reactor, and tool-tip temperature were measured, revealing that the optimal setup can produce an extremely uniform temperature field. Moreover, the characterizations and cutting performances of MCD and NCD diamond coatings deposited on milling tools were evaluated, indicating that high-quality and high-precision diamond coatings with quite satisfactory homogeneity of thickness, surface and cross-sectional morphologies, chemical compositions and phases can be acquired during mass-production of diamond coated milling tools on the base of the optimal HFCVD setup.

Experimental investigation to optimize tool performance in high-speed drilling: a comparative study

In this study, the influence of drilling parameters on circularity error, tool tip temperature and flank wear is investigated while drilling of Ti–6Al–4V alloy specimens with dissimilar cutting tool materials under dry machining conditions. In addition, optimal control factors for circularity error, tool tip temperature and flank wear have been determined using Taguchi–Grey relational analysis. Rotational speed of the spindle, feed rate and drill bit material are considered as control factors. Numerous drilling experimental runs have been performed employing L27 orthogonal array on a CNC vertical machining centre with 12O-mm-diameter holes on 10-mm-thick plates. An infrared thermal camera FLIR E60 is employed to record the temperature at tool chip interface, and Kistler 8793 tri-axial accelerometer is used to get hold of vibration data in real time. Analysis of variance has been carried out to ascertain the most substantial control factors among rotational speed, feed rate and drill bit material and also to establish the effects of the same over circularity error (Cr), temperature (T) and flank wear (VB).

Finite element modeling of ultrasonic-assisted turning: cutting force and heat generation

Adding ultrasonic vibrations to conventional turning can improve the process in terms of cutting force, surface finish and so on. One of the most important factors in machining is the heat generation during the cutting process. In ultrasonic-assisted turning (UAT) the tool tip also vibrates at very high frequency and this sinusoidal motion causes complexity in heat modeling of the cutting system. Modeling and simulation of cutting processes can help to understand the nature of process and provides information to select optimum conditions and machining parameters. In this article, a finite element model has been developed for predicting tool tip temperature in UAT. The effect of machining parameters including cutting speed, feed rate and amplitude of vibration on the tool tip temperature has been investigated. In order to simplify the machining process, the cutting experiment has been carried out in dry condition. The results showed that by applying ultrasonic vibration to the cutting tool, the tool tip flash temperature increases but in some condition its average value could be less than the conventional machining.

A study on effect of tool tip temperature on wear of ceramic cutting tools

This work reflects the effects of tool tip temperature on flank wear of ceramic cutting tools during the turning of nickel alloy 718 (HRC 45). Two types of ceramic cutting inserts were used Al oxide (620) and mixed oxide (6050), during the turning operation under dry environmental conditions at various cutting speeds of 145 m/min, 230 m/min and 360 m/min respectively. The Al oxide inserts showed better results at cutting speed of 145 m/min and 230 m/min than mixed oxide. The worn out edges of inserts and micro structural properties were obtained by using SEM and tool makers microscope. The results were obtained after analyzing each test. The wear resistance of cutting inserts were affected by the tool tip temperature at the cutting zone.

Diamond tool wear mode, path and tip temperature distribution considering effect of varying rake angle and duncut/Redge ratio

Diamond tool wear has been proven to strongly depend on the temperature at the cutting zone. This is because the elevated temperature so attained during machining not only lowers carbon cohesion energy thereby reducing the fracture toughness of diamond tool due to C–C bond weakening but also facilitates high rate of carbon diffusion from diamond tool into silicon workpiece leading to high tool wear. This research therefore studied the response of diamond tool wear path and mode to changing rake angle and ratio during ultraprecision single point diamond turning of a monocrystalline silicon. It was observed from the study that the tool with larger rake angle and high ratio experienced stronger cutting resistance from the workpiece thereby causing the kinetic friction to be high. Additionally, silicon carbide (Tribochemistry) formation was observed to be through both solid-state single phase and multiphase reaction which are in tandem with sp 3 –sp 2 disorder (graphitization) of diamond with bulk of the observed tool wear happening in the flank face which could be due to increasing rake angle influence on the changing ratio.

Tool wear mechanisms and micro-channels quality in micro-machining of Ti-6Al-4V alloy using the Ti(C7N3)-based cermet micro-mills

Abstract The cutting mechanism changes back and forth between ploughing-dominated and shearing-dominated in micro-milling of channel. This study was to research the tool wear mechanisms and micro-channels quality using the Ti(C7N3)-based cermet micro-mills in machining Ti-6Al-4V alloy. Tool wear mechanisms contained the adhesive wear, micro-chipping, oxidative wear, flank wear and diffusion wear. However, the abrasive wear was not discovered, which was a distinct wear mechanism with macro-milling. The higher feed rate induced the tool tip temperature and increased workpiece temperature, and the maximum tool tip temperature was 123.6 °C. Moreover, Tool wear of the micro-mill was improved, and the micro-channels quality also enhanced under the feed rate of 1 μm/flute.

Development of cutting fluid from spent engine oil

The suitability of cutting fluids formulated from spent engine oil has been considered. In the formulation, recycled Spent Engine Oil was used as a base oil, liquid washing soap as emulsifier, phenol was applied as disinfectant while sulphur served as extreme pressure agent. Analysis and comparative assessment of the physical-chemical properties of samples of cutting fluid was conducted. From the performance analysis, the optimal sample has values such as flash point, 205.92 o C; pour point, -13.04 o C. Viscosity, at 40 o C gave an average value of 96.06cst. At 100 o C, have average value of 7.57cst. The sample has average pH value of 9.03. In corrosion grading, it rated non-corrosive. Furthermore, the effectiveness of the developed products was measured, among other parameters, through tool tip temperature, material removal rate and tool tip wear. Sample VII presented the least mean temperature of 32.5 o C. Sample III presented the minimum mean value of tool tip wear. Sample VII gave the best material removal rate of 5.68g/min. From the results obtained from the analysis, the developed spent engine oil based cutting fluid samples compared favourably with the conventional cutting oil, thus making them acceptable for machining application and can also be an economical choice for use in machining processes. Keywords: Spent engine oil, Cutting Fluid, Turning, Regeneration process, Comparative assessment

Statistical analysis of different machining characteristics of EN-24 alloy steel during dry hard turning with multilayer coated cermet inserts

This research article describes the experimental and statistical analysis of flank wear, material removal rate, tool tip temperature, surface roughness parameters (i.e. Ra, Rz and Rt), chip morphology, chip thickness and dimensional deviations (i.e. circularity and cylindricity). Taguchi's L27 orthogonal array has been selected for experimental design and ANOVA (analysis of variance) has been used to study the significance of cutting parameters on the responses. The experimental study exhibits that depth of cut is the predominant machining parameter influencing surface roughness followed by feed rate and cutting speed. Similar result was found for flank wear and dimensional deviations. However, cutting speed was found to be the most crucial input parameter for tool the tip temperature whereas feed rate was the most notable input variable for material removal rate (MRR). Abrasion and chipping are two major wear mechanisms found for flank wear in this study. During chip morphology study using scanning electron microscope material side flow, serrations, shear band, shear cracks, smooth and rough surfaces are observed. Further, the effect of flank wear on surface roughness parameters, dimensional deviations and effect of MRR on different patterns of crater wear were studied. For each response, mathematical model was developed with regression analysis and the models having higher R-Sq values show favorable relationship between predicted and experimented values. Finally, the optimal combination of machining parameters has been obtained using neuro-genetic algorithm.

Prediction of temperature distribution over cutting tool with alumina-MWCNT hybrid nanofluid using computational fluid dynamics (CFD) analysis

The accurate measurement of tool tip temperature in turning has been a challenging task for researchers. The present study covers the computational fluid dynamics (CFD) analysis of a single point carbide cutting tool dissipating heat and subjected to streams of nanofluid mist. This study is an attempt to numerically analyze the thermal behavior of the cutting tool having constant temperature heat source at its tip. To determine the optimized experimental value of nodal temperature, machining of AISI 304 steel has been carried out using alumina and alumina-MWCNT hybrid nanofluid mist with minimum quantity lubrication (MQL) system. Furthermore, the conjugate heat transfer (CHT) analysis has been performed to investigate the temperature distribution over the rake and flank face of carbide cutting insert. An overview of the mathematical model, complete geometry, and mesh generation of the carbide cutting tool is presented. Additionally, the CHT simulation results for the mist of alumina and alumina-MWCNT hybrid nanofluids were compared and validated successfully with the experimental data. The maximum variation of 5.79% has been observed between experimental and simulation data, which in turn proves the proposed conjugate heat transfer-based CFD model as an alternative approach to investigate the influence of cooling media on cutting tool under MQL technique.

Artificial Neural Network Model for Prediction of Tool Tip Temperature and Analysis

Technological improvements put computer systems in the center of our life and various scientific disciplines. These can range from controlling a device in our home to public institutions and the industry. One of these disciplines is a sub-area in mechanical engineering called machining is concerned with not only mechanical systems but also computer aided systems. Artificial Neural Networks -an area of artificial intelligence- which is concerned with learning and decision making of computers is a field that scientists are very interested in. In this study, an Artificial Neural Network (ANN) system was designed for predicting the temperature at the tool tip during the machining process. In the metal cutting process, tool tip temperature is one of the conditions that must be identified, analyzed and monitored along with the main cutting force. For this purpose, an ANN model was developed to determine The Tool Tip Temperature (TTT) in the turning process. In the designed ANN model, parameters consisting of three inputs and one output were used. The three input variables were rake angle (γ- o ), approaching angle (c- o ), feedrate (f-mm/rev) respectively. The output parameter was the TTT (T- 0 C). The most appropriate model was determined according to Mean Squared Error (MSE) ration. In the test phase of the ANN, the smallest MSE was obtained with the model formed as 3-5-1. In this network settings, calculations were MSE=0.00144, R 2 =0.9956 (absolute fraction of variance) in the training phase and MSE=0.00231, R 2 =0.9954 in the test phase. The results show that the designed ANN model can be used for predicting and analyzing tool tip temperature.

Comparative study of turning process on EN47 spring steel with different nose radii using statistical technique

Spring steel (EN47) samples are machined (turning) using Sandvik make coated tungsten carbide tool insert with different nose radii (0.4 and 0.8mm) in dry condition and the results are compared with each other. Spring steel is widely used in the manufacturing of vehicle components such as crankshaft, knuckle and leaf spring. EN47 spring steel material is relatively low cost compare to other alloy steels. Experiments are conducted based on taguchi L9 technique. Input parameters are cutting speed, feed rate and depth of cut. The corresponding output parameters are cutting force, surface roughness and tool tip temperature have been analyzed. Experimental result reveals that better surface roughness obtained with higher nose radius. ANOVA results confirm that cutting force is influenced by depth of cut (ap), surface roughness is influenced by feed rate (f) and tooltip temperature is influenced by cutting speed (Vc). Chip morphology and machined surface samples are analyzed using scanning electron microscope (SEM).

Investigation of Cutting Force Tool Tip Temperature and Surface Roughness during Dry Machining of Spring Steel

Today’s growing demand for steels and spring steels are widely used in industries as they possess high yield strength and their property resistance to deform easily. Spring steels have huge demand in manylarge scale industries, because of their applications in nuclear power plant, jet engine parts, forming tools and extrusion dies. EN47 is one of such spring steels with relatively low cost. Machinability study of EN47 material was analysed using a L27 orthogonal array (OA) for dry turning condition using TiCN/Al2O3/TiN CVD coated tungsten carbide insert with nose radius of 0.4mm. Depth of cut (d), Speed (v), feed (f) and are varied to the level-3. During machining, cutting forces and cutting temperatures was measured using Kistler based dynamometer and heat gun respectively. Surface roughness was measured by using Mitutoyo SJ201 after machining. Machined surface and chip were analysed using scanning electron microscope (SEM). Tool tip temperature, surface finish and cutting forces are optimized using Design of Experiments technique and proof trails are conducted with satisfactory results.

Optimization of controllable turning parameters for high speed dry machining of a super alloy

Turning operations were performed on Inconel 718, a Nickel based super alloy under dry cutting conditions using PVD coated carbide cutting tool. An optimized set of input parameters have be presented for obtaining the best combination of Tool wear, Temperature, surface roughness and Material removal Rate. The control factors that were investigated were Cutting speed, feed and Depth of cut. The chosen response factors are Flank Wear, Tool Tip Temperature, Surface roughness and Material removal rate. For each control factor 3 levels were selected, conducting 27 experiments in total according to full factorial design of experiments. Regression was carried out for the experimental results, where the mathematical model was found to be adequate enough. The mathematical models obtained for both the responses were used for formulating a multi objective optimization which was solved using Genetic Algorithm for optimized control factor values. The optimized solutions were confirmed with experimental results. In addition, tool life was also calculated for optimized solution. A user friendly application program was developed to suit the industry needs.

Optimization of Machining Parameters in Turning of Al6063A-T6 using Taguchi-Grey Analysis

Aluminum alloys are widely used in the transportation, construction, marine, and aerospace. It possesses good corrosion resistance, wear resistance, high strength to weight ratio good formability. In present work an investigation of machining parameters speed, feed and depth cut which effect the surface rough of the workpiece and cutting tool tip temperature. Experiments are carried out with varying speed, feed and depth of cut on Al6063A-T6 on CNC turning machine using carbide tools. Taguchi-Grey analysis is carried out on L9 orthogonal array to find the optimum the speed, feed and depth of cut in order to have minimum surface roughness and low cutting tool temperature. From the results of analysis, it is found that optimum speed (N3) =1400rpm, feed (F1) =0.1mm/min and depth of cut (D3) = 0.75mm for which minimum surface roughness (Ra) is 0.855 microns and cutting tool temperature (T) =4570C in machining of Al6063A-T6 on CNC turning machine.

Measurement of Tool Tip Temperature in Cutting of Titanium Alloy under Cryogenic CO<sub>2</sub> Cooling

Measurement of Tool Tip Temperature in Cutting of Titanium Alloy under Cryogenic CO<sub>2</sub> Cooling

Optimisation of turning parameters on heat treated INCOLOY 800H using cryogenically treated CVD tool with grey-based entropy method

This research work is focused on examining the turning behaviour of heat treated INCOLOY 800H superalloy by varying turning parameters like cutting speed, feed rate, depth of cut and nose radius of tool in dry turning, using cryogenically treated (24 hrs) CVD coated tool of TiAlN. The samples are heated to the temperature of 1,050°C; maintained for 1 hr inside the induction furnace and then cooled in air, after solution treatment. Micro structure, compression test, fractography and wear test were conducted to study the material behaviour. Thrust force, cutting force, surface roughness, cutting tool-tip temperature, material removal rate (MRR) and coefficient of friction (CoF) were considered as output responses. Grey relational analysis (GRA) with an entropy weight method was used to optimise turning parameters. Analysis of variance (ANOVA) was employed to identify most influencing parameters on the responses. The machining performance could be improved (39.07%) efficiently by this projected approach.

An embedded multi-sensor system on the rotating dynamometer for real-time condition monitoring in milling

The newly developed multi-sensor system for a milling process sensor system is capable of simultaneously measuring six channels of machining signals using a rotating tool incorporating a wireless system. Furthermore, the system can be used to measure the spindle torque, T q ; tool vibration in the z-axis, A z ; tool tip temperature, T m and the three components of the cutting force. Cutting force signals are generated by using a cross-beam-legged transducer embedded in the standard milling tool holder. A mini accelerometer is placed under the force transducer, whereas a thermocouple is positioned under a cutting tool insert close to the cutting edge. All signals are collected and sent to the data logger system via an inductive wireless transmitter unit incorporated into the standard rotating tool holder. The calibration, verification and real experimental machining test results reveal that the sensor system is both suitable and reliable for measuring machining signals. The measured signals are found to be importantly related to changes in the flank wear state. Therefore, this system can be used for real-time tool condition monitoring in the milling process.

Determination of a coupling equation for milling parameters based on optimal cutting temperature

The optimization of cutting parameters has a great concern in the field of manufacturing process, especially the relationships among cutting parameters, with the study aiming at exploring a coupling equation to cutting parameters based on the optimal cutting temperature in the milling process of precipitation-hardening stainless steel with cemented carbide inserts. Initially, the association among the ratios of cutting tool wear of the machined surface, the cutting speed, and temperature was respectively investigated, with the ratio also used as an evaluating level of tool wear. Afterwards, the effects of the work hardening layer depth and the work hardening degree on the cutting speed and temperature were discussed in order to evaluate the machined surface quality. The results indicate that while the minimum tool wear occurred, the tool tip temperature at the cutting zone stayed the same with the minimum degree of work hardening appearing, which was defined as the optimal cutting temperature. An empirical formula for the cutting temperature and cutting parameters is explored using regression orthogonal experiment design, and then combined with optimum temperature. As a result, a coupling equation to cutting parameters is determined. Meanwhile, the mechanism of the minimal cutter wear is analyzed in accordance with the characteristics of cutting tool wear under several different machining conditions. The coupling equation could be put into an optimization model as a constraint. The results of this research would be beneficial to application of cooling liquids and cooling method to achieve cleaner production as well as the construction of a cutting database of metal materials.