Green machining using graphene-based self-lubricating cutting tool – a preliminary investigation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Amrita M. ◽  
Rukmini Srikant Revuru ◽  
Sreeram Chatti ◽  
Sree Satya Bharati Sri Satya Moram ◽  
Chandu Byram ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Cutting Forces ◽  
Cutting Tool ◽  
Preliminary Investigation ◽  
Weight Ratio ◽  
Dip Coating ◽  
Cutting Fluid ◽  
Machining Time ◽  
Content Type ◽  
Tool Condition

Purpose Ti6Al4V is a commonly used titanium alloy with several applications in aerospace industry due to its excellent strength to weight ratio. But due to low thermal conductivity, it is categorized as “difficult to machine.” Though machinability can be improved with cutting fluids, it is not preferred due to associated problems. This study aims at eliminating the use of cutting fluid and finding an alternate solution to dry machining of Ti6Al4V. AlTiN coated tools provide good heat and oxidation resistance but have low lubricity. In the present work, graphene, which is known for lubricating properties, is added to the tools using five different methods (tool condition) to form graphene self-lubricated cutting tools. Design/methodology/approach Graphene-based self-lubricating tools are prepared by using five methods: dip coating (10 dips and 30 dips); drop casting; and filling of micro/macroholes. Performance of these tools is evaluated in terms of cutting forces, surface roughness and tool wear by machining Ti6Al4V and comparing with conventional coated cutting tool. Findings Self-lubricating tool with micro holes filled with graphene outperformed other tools and showed maximum decrease of 33.42% in resultant cutting forces, 35% in surface roughness (Ra) and 30% in flank wear compared to conventional cutting tool. Originality/value Analysis of variance for all forces show that tool condition and machining time have significant influence on all components of cutting forces and resultant cutting forces.

Performance evaluation of graphene added nanofluids and self-lubricating tools in machining Inconel 718

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Amrita Maddamasetty ◽  
Kamesh Bodduru ◽  
Siva Bevara ◽  
Rukmini Srikant Revuru ◽  
Sanjay Kumar
Keyword(s):  
Surface Roughness ◽  
Inconel 718 ◽  
Solid Lubricant ◽  
Cutting Tool ◽  
Cutting Temperature ◽  
Cutting Fluid ◽  
Superior Performance ◽  
Dry Machining ◽  
Inconel 718 Alloy ◽  
Content Type

Purpose Inconel 718 is difficult to machine due to its high toughness and study hardenability. Though the use of cutting fluids alleviates the problem, it is not sustainable. So, supply of a small quantity of specialized coolant to the machining zone or use of a solid lubricant is a possible solution. The purpose of the present work is to improve machinability of Inconel718 using graphene nanoplatelets. Design/methodology/approach In the present study, graphene is used in the machining of Inconel 718 alloy. Graphene is applied in the following two forms: as a solid lubricant and as an inclusion in cutting fluid. Graphene-based self-lubricating tool and graphene added nanofluids are prepared and applied to turning of Inconel 718 at varying cutting velocities. Performances are compared by measuring cutting forces, cutting temperature, tool wear and surface roughness. Findings Graphene, in both forms, showed superior performance compared to dry machining. In total, 0.3 Wt.% graphene added nanofluids showed the lowest cutting tool temperature and flank wear with 44.95% and 83.37% decrease, respectively, compared to dry machining and lowest surface roughness, 0.424 times compared to dry machining at 87 m/min. Originality/value Graphene could improve the machinability of Inconel 718 when used in tools as a solid lubricant and also when used as a dispersant in cutting fluid. Graphene used as a dispersant in cutting fluid is found to be more effective.

scholarly journals Using uniform design and regression methodology of turning parameters study of nickel alloy

2021 ◽  
Author(s):  
Shao-Hsien Chen ◽  
Chih-Hung Hsu
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Nickel Alloy ◽  
Design Methodology ◽  
Cutting Tool ◽  
Uniform Design ◽  
Machining Time ◽  
Variable Parameters ◽  
Cutting Test ◽  
Set Up

AbstractThe nickel alloy has good mechanical strength and corrosion resistance at high temperature; it is extensively used in aerospace and biomedical and energy industries, as well as alloy designs of different chemical compositions to achieve different mechanical properties. However, for high mechanical strength, low thermal conductivity, and surface hardening property, the nickel alloy has worse cutting tool life and machining efficiency than general materials. Therefore, how to select the optimum machining parameters will influence the workpiece quality, cost, and machining time. This research will be using a new experimental design methodology to the cutting parameter planning for nickel-based alloy cutting test, and used the uniform design methodology to cutting test to reduce the number of experiments. Three independent variable parameters are set up, including cutting speed, feed rate, and cutting depth, and four dependent variable parameters are set up, including cutting tool wear, surface roughness, machining time, and cutting force. A nickel alloy turning parameter model is built by using regression analysis to further predict the I/O relationship among various combinations of variables. The errors between actual values and prediction values are validated. When the cutting tool wear (VB) is 2.72~6.18%, the surface roughness (Ra) is 4.10~7.72%, the machining time (T) is 3.75~8.82%, and the cutting force (N) is 1.54~7.42%; the errors of various dependent variables are approximately less than 10%, so a high precision estimation model is obtained through a few experiments of uniform design method.

Sustainable machining. Modeling and optimization of temperature and surface roughness in the milling of AISI D2 steel

2019 ◽  
Vol 71 (2) ◽  
pp. 267-277 ◽  
Author(s):  
Aqib Mashood Khan ◽  
Muhammad Jamil ◽  
Ahsan Ul Haq ◽  
Salman Hussain ◽  
Longhui Meng ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Empirical Modeling ◽  
Cutting Fluid ◽  
Depth Of Cut ◽  
Aisi D2 Steel ◽  
Content Type ◽  
Sustainable Machining ◽  
Aisi D2 ◽  
D2 Steel

Purpose Sustainable machining is a global consensus and the necessity to cope up the serious environmental threats. Minimum quantity lubrication (MQL) and nanofluids-based MQL(NFMQL) are state-of-the-art sustainable lubrication modes. The purpose of this study is to investigate the effect of process parameters, such as feed rate, depth of cut and cutting fluid flow rate, on temperature and surface roughness of the manufactured pieces during face milling of the AISI D2 steel. Design/methodology/approach A statistical technique called response surface methodology with Box–Behnken Design was used to design experimental runs, and empirical modeling was presented. Analysis of variance was carried out to evaluate the model’s accuracy and the validation of the applied technique. Findings A comprehensive analysis revealed the superiority of implementing NFMQL in comparison to MQL within the levels of process parameters. The comparison has shown a significant reduction of temperature under NFMQL at the tool-workpiece interface from 16.2 to 34.5 per cent and surface roughness from 11.3 to 12 per cent. Practical implications This research is useful for practitioners to predict the responses in workshop and select appropriate cutting parameters. Moreover, this research will be helpful to reduce the resource which will ultimately save energy consumption and cost. Originality/value To cope with the industrial challenges and tribological issues associated with the milling of AISI D2 steel, experiments were conducted in a distinct machining mode with innovative cooling/lubrication. Until now, few studies have addressed the key lubrication effects of Al2O3-based nanofluid on the machinability of D2 steel under NFMQL lubrication condition.

scholarly journals OPTIMUM PERFORMANCE OF GREEN MACHINING ON THIN WALLED TI6AL4V USING RSM AND ANN IN TERMS OF CUTTING FORCE AND SURFACE ROUGHNESS

2019 ◽  
Vol 81 (6) ◽  
Author(s):  
Muhammad Yanis ◽  
Amrifan Saladin Mohruni ◽  
Safian Sharif ◽  
Irsyadi Yani
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Cutting Speed ◽  
Weight Ratio ◽  
Cutting Fluid ◽  
Depth Of Cut ◽  
Ann Model ◽  
Green Machining ◽  
Radial Depth ◽  
Thin Walled

Thin walled titanium alloys are mostly applied in the aerospace industry owing to their favorable characteristic such as high strength-to-weight ratio. Besides vibration, the friction at the cutting zone in milling of thin-walled Ti6Al4V will create inconsistencies in the cutting force and increase the surface roughness. Previous researchers reported the use of vegetable oils in machining metal as an effort towards green machining in reducing the undesirable cutting friction. Machining experiments were conducted under Minimum Quantity Lubrication (MQL) using coconut oil as cutting fluid, which has better oxidative stability than other vegetable oil. Uncoated carbide tools were used in this milling experiment. The influence of cutting speed, feed and depth of cut on cutting force and surface roughness were modeled using response surface methodology (RSM) and artificial neural network (ANN). Experimental machining results indicated that ANN model prediction was more accurate compared to the RSM model. The maximum cutting force and surface roughness values recorded are 14.89 N, and 0.161 µm under machining conditions of 125 m/min cutting speed, 0.04 mm/tooth feed, 0.25 mm radial depth of cut (DOC) and 5 mm axial DOC. 

Technological Investigation of Effect of Machining Parameter on Tool Life

2020 ◽  
Vol 22 (4) ◽  
pp. 41-53
Author(s):  
Manojkumar Sheladiya ◽  
◽  
Shailee Acharya ◽  
Ghanshyam Acharya ◽  
◽  
...  
Keyword(s):  
Surface Roughness ◽  
Mild Steel ◽  
Tool Life ◽  
Flank Wear ◽  
Cutting Speed ◽  
Numerical Control ◽  
Cutting Fluid ◽  
Depth Of Cut ◽  
Machining Time ◽  
Machining Parameter

Introduction. The machinability is typical criteria to be investigated and different authors suggested different parameters describing its quantification. Different parameters i. e. speed, feed, depth of cut, tool work-piece combination, machine types and its condition, cutting fluid, machinist expertise, etc. are contributing directly to the tool life. The selection of the tool for the machining impacts greatly on the economic viability of the machining in terms of energy usage and tooling costs. The method of investigation. The current research emphasis mainly on tool life investigation when machining the mild steel specimens ISRO 50, BIS 1732:1989 at constant cutting speed i.e. 200 m / min. In the industries the mild steel material is commonly used for various products manufacturing. Considering the high demands on productivity and surface finish, machining at 200 m / min is the preferred. The computerized numerical control machine (CNC DX-150) is used for the turning. The four corner insert (TNMG 120408) is used for different machining times i.e. 10, 15, 20 and 25 minutes respectively. The flank wear of the tool is measured with calibrated optical microscope. The temperature of the tool corner during machining is continuously measured for possible impact of temperature on bonding properties of the tool insert and impact on red hardness. Results and discussion. The plot of flank wear vs. machining time will give the value of tool life. The other quality output parameter, such as surface roughness, is measured after machining, indicating surface irregularities in root means square value. Efforts have been made to identify the relationship of tool life, machining time, the quantity of metal removed, surface roughness, and tool bit temperature.

Experimental Investigation to Predict Tool Wear and Vibration Displacement in Turning – A Base for Tool Condition Monitoring

2016 ◽  
Vol 16 (2) ◽  
pp. 103-114
Author(s):  
M. Prakash Babu ◽  
Balla Srinivasa Prasad
Keyword(s):  
Mathematical Model ◽  
Tool Wear ◽  
Condition Monitoring ◽  
Cutting Forces ◽  
Cutting Tool ◽  
Tool Condition Monitoring ◽  
Depth Of Cut ◽  
Vibration Displacement ◽  
Tool Condition ◽  
Tool Vibrations

AbstractIn the present work investigation primarily focuses on identifying the presence of cutting tool vibrations during face turning process. For this purpose an online non-contact vibration transducer i. e. laser Doppler Vibrometer is used as part of a novel approach. The revisions in the values of cutting forces, vibrations and acoustic optic emission signals with cutting tool wear are recorded and analyzed. This paper presents a mathematical model in an attempt to understand tool lifeunder vibratory cutting conditions. Tool wear and cutting force data are collected in the dry machiningof AISI 1040 steel at different vibrationinduced test conditions. Identifying the correlation among tool wear, cutting forces and displacement due to vibration is a critical task in the present study. These results are used to predict the evolution of displacement and tool wear in the experiment. Specifically, the research tasks include: to provide an appropriate experimental data to prove the mathematical model of tool wear based on the influence of cutting tool vibrations in turning.The modeling is focused on demonstrating the scientific relationship between the process variables such as vibration displacement, vibration amplitude, feedrate, depth of cut and spindle speed while getting into account machine dynamics effect and the effects such as surface roughness and tool wear generated in the operation. Present work also concentrates on the improvement in machinability during vibration assisted turning with different cutting tools. The effect of work piece displacement due to vibration on the tool wear is critically analyzed. Finally, tool wear is established on the basis of the maximum displacement that can be tolerated in a process for an effective tool condition monitoring system.

The Effect of Cutting Force Vibration on Machining Quality for Reaming ZL102 Alloy with PCD Step Reamer

2018 ◽  
Vol 764 ◽  
pp. 279-290
Author(s):  
X.D. Wang ◽  
W.L. Ge ◽  
Y.G. Wang
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Cutting Forces ◽  
Thrust Force ◽  
Maximum Amplitude ◽  
Spindle Speed ◽  
Machining Process ◽  
Cutting Fluid ◽  
Hole Quality ◽  
Force Vibration

The characteristics of cutting forces vibration and its effects to the hole quality in reaming aluminum cast alloy using a poly-crystalline diamond (PCD) step reamer in dry and wet conditions were studied. First, centrifugal force vibration model of the PCD step reamer during machining process was established and through the analysis of the model, it can be concluded that the maximum amplitude of the vibration is positively related to the angular velocity of the reamer. Then, thrust force and cutting torque were measured by a Kistler Dynamometer during reaming process and these vibration frequency and amplitude were analyzed by fast Fourier transformation (FFT). Hole quality was evaluated by hole diameter and surface roughness. Results show that, as the spindle speed increases, the stability of thrust force and cutting torque deteriorates gradually, and there was a severe vibration in the cutting force and the surface roughness when the spindle speed reached 10000 rpm in wet and 7000 rpm in dry cutting conditions. Compared the variation of hole surface roughness and vibration characteristic of cutting forces, it can be observed that the trends are very consistent, the surface roughness deteriorates when cutting forces become unstable. Therefore,the cutting forces stability was an important factor that influence the hole quality. Cutting fluid has a positive effect to stabilize the reaming process and was beneficial to improve the hole quality.

scholarly journals Modeling Cutting Forces in High-Speed Turning using Artificial Neural Networks

TecnoLógicas ◽  
2021 ◽  
Vol 24 (51) ◽  
pp. e1671
Author(s):  
Luis W. Hernández-González ◽  
Dagnier A. Curra-Sosa ◽  
Roberto Pérez-Rodríguez ◽  
Patricia D.C. Zambrano-Robledo
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Energy Consumption ◽  
Cutting Forces ◽  
High Speed ◽  
Cutting Tool ◽  
Cutting Speed ◽  
Machining Time ◽  
High Speed Turning ◽  
Artificial Neural

Cutting forces are very important variables in machining performance because they affect surface roughness, cutting tool life, and energy consumption. Reducing electrical energy consumption in manufacturing processes not only provides economic benefits to manufacturers but also improves their environmental performance. Many factors, such as cutting tool material, cutting speed, and machining time, have an impact on cutting forces and energy consumption. Recently, many studies have investigated the energy consumption of machine tools; however, only a few have examined high-speed turning of plain carbon steel. This paper seeks to analyze the effects of cutting tool materials and cutting speed on cutting forces and Specific Energy Consumption (SEC) during dry high-speed turning of AISI 1045 steel. For this purpose, cutting forces were experimentally measured and compared with estimates of predictive models developed using polynomial regression and artificial neural networks. The resulting models were evaluated based on two performance metrics: coefficient of determination and root mean square error. According to the results, the polynomial models did not reach 70 % in the representation of the variability of the data. The cutting speed and machining time associated with the highest and lowest SEC of CT5015-P10 and GC4225-P25 inserts were calculated. The lowest SEC values of these cutting tools were obtained at a medium cutting speed. Also, the SEC of the GC4225 insert was found to be higher than that of the CT5015 tool.

Evaluation of the cutting forces, the surface roughness, and the tool wear characteristics during machining of cobalt-based superalloy Haynes 188 with ceramic cutting tool

2021 ◽  
pp. 095440892110480
Author(s):  
Abdullah Altin
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Cutting Forces ◽  
Cutting Tool ◽  
Signal To Noise Ratio ◽  
Cutting Tools ◽  
Cutting Speed ◽  
Signal To Noise ◽  
Ceramic Cutting Tool ◽  
Cutting Speeds

In this research, we had studied the sensitivity for machining of cobalt-based superalloy Haynes 188 with ceramic cutting tool. The investigation had focused on the effects of the cutting speed, on the cutting forces, and on the surface roughness based on Taguchi’s experimental design. The effects of machining parameters were determined using Taguchi’s L27 orthogonal array. The signal-to-noise ratio was calculated for the average of surface roughness and the cutting forces, and the smaller were used to determine the optimal cutting conditions. The analysis of variance and the signal-to-noise ratio had effects on the parameters on both surface roughness and cutting. Three different types of cutting tools had been used in the experiment, namely KYON 4300, KYS 25, and KYS 30. The cutting force of Fz was considered to be the main cutting force. Depending on the material which had been used as cutting tool, the Fz had the lowest cutting speed and the lowest surface roughness with the KYS25 ceramic tool. The cutting force and the surface roughness of KYON 4300 cutting tool had shown better performance than other cutting tools. The flank wear and notch were found to be more effective in the experiments. The long chips were removed at low and medium cutting speeds, while the sawdust with one edge and narrow pitch at high cutting speeds was obtained.

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