scholarly journals Experimental Determination of Cutting Power for Turning and Material Removal Rate for Drilling of AA 6061-T6 Using Vegetable Oils as Cutting Fluid

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Y. M. Shashidhara ◽  
S. R. Jayaram
Keyword(s):  
Vegetable Oils ◽  
Material Removal Rate ◽  
Cutting Forces ◽  
Material Removal ◽  
Removal Rate ◽  
Mineral Oil ◽  
Cutting Fluid ◽  
Cutting Fluids ◽  
Cutting Power ◽  
Thrust Forces

The raw and modified versions of two nonedible vegetable oils, Pongam (Pogammia pinnata) and Jatropha (Jatropha curcas), and a commercially available branded mineral oil are used as straight cutting fluids for turning AA 6061 to assess cutting forces. Minimum quantity lubrication is utilized for the supply of cutting fluids. Cutting and thrust forces are measured. Cutting power is determined for various cutting speeds, depths of cut, and feed rates. Also, drilling is performed on the material to understand the material removal rate (MRR) under these oils. The performances of vegetable oils are compared to mineral oil. A noticeable reduction in cutting forces is observed under the Jatropha family of oils compared to mineral oil. Further, better material removal rate is seen under both the vegetable oils and their versions compared to under petroleum oil for the range of thrust forces.

scholarly journals Performance Evaluation of Jatropha and Pongamia Oil Based Environmentally Friendly Cutting Fluids for Turning AA 6061

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
T. P. Jeevan ◽  
S. R. Jayaram
Keyword(s):  
Vegetable Oils ◽  
Cutting Forces ◽  
Mineral Oil ◽  
Cutting Fluid ◽  
Cutting Fluids ◽  
Taguchi’S Technique ◽  
Minimal Quantity Lubrication ◽  
Minimal Quantity ◽  
Pongamia Oil ◽  
Effective Design

Owing to the desirable properties of vegetable oils as cutting fluids, an attempt is made to explore the potentiality of plentifully available vegetable oils as a cutting fluid for turning AA 6061. Two nonedible vegetable oils, Jatropha and Pongamia, in their chemically modified (epoxidized) versions are used as straight cutting fluids. Cutting fluids are introduced to the machining zone with the aid of Minimal Quantity Lubrication (MQL) method. Taguchi’s technique of orthogonal arrays is used to develop an effective design of experiments. The results obtained under epoxidized versions of Jatropha and Pongamia oils are compared with the results of mineral oil in terms of cutting forces and surface roughness. Experimental observations and statistical analysis show that, compared to mineral oil, the modified versions of vegetable oil-based cutting fluids are more effective in reducing the cutting forces and increasing surface finish. It is also observed that the modified Pongamia oil showed lesser flank wear compared to the other two tested oils.

Performance Analysis of Trihexyltetradecylphosphonium Chloride Ionic Fluid under MQL Condition in Hard turning

2020 ◽  
Vol 17 (1) ◽  
pp. 7629-7647
Author(s):  
A. Pandey ◽  
R. Kumar ◽  
A. K. Sahoo ◽  
A. Paul ◽  
A. Panda
Keyword(s):  
Material Removal Rate ◽  
Feed Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Coconut Oil ◽  
Chip Morphology ◽  
Weight Fraction ◽  
Cutting Fluid ◽  
Depth Of Cut

The current research presents an overall performance-based analysis of Trihexyltetradecylphosphonium Chloride [[CH3(CH2)5]P(Cl)(CH2)13CH3] ionic fluid mixed with organic coconut oil (OCO) during turning of hardened D2 steel. The application of cutting fluid on the cutting interface was performed through Minimum Quantity Lubrication (MQL) approach keeping an eye on the detrimental consequences of conventional flood cooling. PVD coated (TiN/TiCN/TiN) cermet tool was employed in the current experimental work. Taguchi’s L9 orthogonal array and TOPSIS are executed to analysis the influences, significance and optimum parameter settings for predefined process parameters. The prime objective of the current work is to analyze the influence of OCO based Trihexyltetradecylphosphonium Chloride ionic fluid on flank wear, surface roughness, material removal rate, and chip morphology. Better quality of finish (Ra = 0.2 to 1.82 µm) was found with 1% weight fraction but it is not sufficient to control the wear growth. Abrasion, chipping, groove wear, and catastrophic tool tip breakage are recognized as foremost tool failure mechanisms. The significance of responses have been studied with the help of probability plots, main effect plots, contour plots, and surface plots and the correlation between the input and output parameters have been analyzed using regression model. Feed rate and depth of cut are equally influenced (48.98%) the surface finish while cutting speed attributed the strongest influence (90.1%). The material removal rate is strongly prejudiced by cutting speed (69.39 %) followed by feed rate (28.94%) whereas chip reduction coefficient is strongly influenced through the depth of cut (63.4%) succeeded by feed (28.8%). TOPSIS significantly optimized the responses with 67.1 % gain in closeness coefficient.

scholarly journals A surrogate-assisted optimization approach for multi-response end milling of aluminum alloy AA3105

2020 ◽  
Vol 111 (9-10) ◽  
pp. 2419-2439
Author(s):  
Tamal Ghosh ◽  
Yi Wang ◽  
Kristian Martinsen ◽  
Kesheng Wang
Keyword(s):  
Surface Roughness ◽  
Aluminum Alloy ◽  
Material Removal Rate ◽  
Cutting Forces ◽  
Material Removal ◽  
End Milling ◽  
Removal Rate ◽  
Cutting Parameters ◽  
Data Driven ◽  
Optimal Cutting Parameters

Abstract Optimization of the end milling process is a combinatorial task due to the involvement of a large number of process variables and performance characteristics. Process-specific numerical models or mathematical functions are required for the evaluation of parametric combinations in order to improve the quality of the machined parts and machining time. This problem could be categorized as the offline data-driven optimization problem. For such problems, the surrogate or predictive models are useful, which could be employed to approximate the objective functions for the optimization algorithms. This paper presents a data-driven surrogate-assisted optimizer to model the end mill cutting of aluminum alloy on a desktop milling machine. To facilitate that, material removal rate (MRR), surface roughness (Ra), and cutting forces are considered as the functions of tool diameter, spindle speed, feed rate, and depth of cut. The principal methodology is developed using a Bayesian regularized neural network (surrogate) and a beetle antennae search algorithm (optimizer) to perform the process optimization. The relationships among the process responses are studied using Kohonen’s self-organizing map. The proposed methodology is successfully compared with three different optimization techniques and shown to outperform them with improvements of 40.98% for MRR and 10.56% for Ra. The proposed surrogate-assisted optimization method is prompt and efficient in handling the offline machining data. Finally, the validation has been done using the experimental end milling cutting carried out on aluminum alloy to measure the surface roughness, material removal rate, and cutting forces using dynamometer for the optimal cutting parameters on desktop milling center. From the estimated surface roughness value of 0.4651 μm, the optimal cutting parameters have given a maximum material removal rate of 44.027 mm3/s with less amplitude of cutting force on the workpiece. The obtained test results show that more optimal surface quality and material removal can be achieved with the optimal set of parameters.

scholarly journals EFFECT OF PROCESS PARAMETERS FOR OPTIMUM MATERIAL REMOVAL RATE OF CYLINDRICAL GRINDING OF AISI 1045 STEEL

2015 ◽  
Vol 44 (2) ◽  
pp. 100-104
Author(s):  
Taranveer Singh ◽  
Khushdeep Goyal ◽  
Parlad Kumar
Keyword(s):  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Wheel Speed ◽  
Cutting Fluid ◽  
Depth Of Cut ◽  
Input Parameters ◽  
Aisi 1045 ◽  
1045 Steel ◽  
Number Of Passes

In this experimental work, the effect of various input parameters viz. work speed, wheel speed,abrasive material, depth of cut, concentration of cutting fluid and number of passes has been studied on thematerial removal rate of cylindrical grinded AISI. For experimentation, three levels of each variable have beenselected except wheel speed. Two levels of wheel speed have been taken. Heat treated AISI 1045 has beenconsidered as work piece material. The result reveals that number of passes followed by the type of abrasivematerial is the most significant to influence material removal rate. The optimum set of input parameters formaximizing the material removal rate has also been found.

Experimental Analysis and Forecasting of Material Removal Rate and Cutting Force in End Milling on A356 Alloy-SiC Metal Matrix Composites

2015 ◽  
Vol 787 ◽  
pp. 637-642
Author(s):  
K. Jayakumar ◽  
Jose Mathew ◽  
M.A. Joseph
Keyword(s):  
Cutting Force ◽  
Metal Matrix Composites ◽  
Material Removal Rate ◽  
Cutting Forces ◽  
Metal Matrix ◽  
Material Removal ◽  
End Milling ◽  
Removal Rate ◽  
A356 Alloy ◽  
Matrix Composites

By considering several applications of aluminum based particle reinforced composites especially in automobile, aerospace and electronic industries, in this work, prediction of machinability responses of A356 alloy-SiC particles (5, 10, 15 and 20 vol%) reinforced metal matrix composites is described. Composites were synthesized by vacuum hot pressing (VHP) assisted powder metallurgy (P/M) process. Effect of cutting speed (Vc), feed (f), depth of cut (d) and quantity of SiC (vol %) on machinability of composites in terms of material removal rate (MRR) and resultant cutting forces (FR) during end milling were investigated. Milling experiments were carried in dry condition based on central composite design and KISTLER dynamometer was used to measure cutting forces. Resultant cutting force values were increased from 21 to 105 N with an increase in ‘f’ and ‘d’, but decreased with increase in ‘Vc’. Increase in machining parameters increased the MRR from 2.3 to 8.6 × 103 mm3/min and increase in SiC reduced the MRR. Statistical modeling with cubic response equations were used to predict the results and predicted results were closely matching with experimental values.

scholarly journals An Experimental Investigation on Vegetable Oils as a Cutting Fluid under Minimum Quantity Lubrication: A Sustainable Machining Approach

2021 ◽  
Vol 23 (04) ◽  
pp. 143-155
Author(s):  
Shrikant U. Gunjal ◽  
◽  
Sudarshan B. Sanap ◽  
Nilesh C. Ghuge ◽  
Satish Chinchanikar ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Tool Life ◽  
Vegetable Oils ◽  
Cutting Forces ◽  
Minimum Quantity Lubrication ◽  
Machining Process ◽  
Cutting Fluid ◽  
Interface Temperature ◽  
Cutting Fluids ◽  
Minimum Quantity

Cutting fluid is a vital part of the machining process. Cutting fluid is significantly applied tolower the friction and heat generated in the machining zone. It also helps in easy chip removal, protection against oxidation, tool life improvement, and an overall improvement in the quality of the product. The current industrial practices are majorly emphasized on mineral-based oil application under flood lubrication to achieve superior quality. However, these oils and techniques are toxic and environmentally unfriendly. Machining under dry or with minimum quantity lubrication (MQL) has been mostly preferred to eliminate the use of abundant oil. The current research work has established the promising potential for vegetable oils as a cutting fluid under MQL during turning of AISI 4130 steel. The results inferred that vegetable-based cutting fluids performed better over mineral-based cutting fluids in terms of lower values of machined surface roughness, tool wear, cutting forces, and chip-tool interface temperature. The MQL machining performance in terms of cutting forces, surface roughness and tool life has been observed better in comparison to machining under flood and dry cutting conditions.

Influences of Grit Shape and Cutting Edge on Material Removal Mechanism of a Single Abrasive in Flexible Robotic Grinding

2013 ◽  
Author(s):  
Amir Masoud Tahvilian ◽  
Henri Champliaud ◽  
Zhaoheng Liu ◽  
Bruce Hazel
Keyword(s):  
Material Removal Rate ◽  
Cutting Forces ◽  
Material Removal ◽  
Position Control ◽  
Removal Rate ◽  
Element Model ◽  
Rake Angle ◽  
Work Piece ◽  
Force Model ◽  
Robotic Grinding

A flexible robotic grinding system has been used for in situ maintenance of large hydro turbine runners by Hydro-Quebec. Field trials for more than 20 years have proven the reliability and efficiency of the technology for hydropower equipment maintenance and repair. This portable robot named SCOMPI, is developed by IREQ, Research Institute of Hydro-Quebec and can perform high material removal rate grinding on hardly accessible areas of turbine runner blades. Due to the light weight and low rigidity of the robot, traditional position control of conventional grinding is not applicable in this process. Instead a hybrid force/position controller is employed to ensure the accuracy of the predefined material removal rate. Therefore, having a good force model for a specific removal rate is a prerequisite for controlling the grinding task. Understanding the grinding process as the cutting action of several single grits participating in the material removal process provides an insight to predict the needed forces. This paper presents an investigation of the effects of grits shape on cutting forces in single abrasive cutting mechanism during high removal rate grinding by SCOMPI robot. A three-dimensional finite element model is developed to simulate the chip formation process with different grit shapes. Thermal results from our previous study of temperature distribution in the contact zone for this special robotic grinding are imposed to the un-deformed chips. Then, Johnson-Cook plasticity model is employed to investigate effects of hardening and thermal softening of work piece material in cutting forces. It is also found that, rake angle and cutting edges of the grit can have significant effects on the cutting and normal forces.

scholarly journals Parametric Optimization for Cutting Forces and Material Removal Rate in the Turning of AISI 5140

Machines ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 90
Author(s):  
Mustafa Kuntoğlu ◽  
Osman Acar ◽  
Munish Kumar Gupta ◽  
Hacı Sağlam ◽  
Murat Sarikaya ◽  
...  
Keyword(s):  
Material Removal Rate ◽  
Cutting Forces ◽  
Material Removal ◽  
Removal Rate ◽  
Cutting Parameters ◽  
Industrial Applications ◽  
Optimization Approach ◽  
Regression Equations ◽  
Dry Cutting ◽  
Optimum Parameters

The present paper deals with the optimization of the three components of cutting forces and the Material Removal Rate (MRR) in the turning of AISI 5140 steel. The Harmonic Artificial Bee Colony Algorithm (H-ABC), which is an improved nature-inspired method, was compared with the Harmonic Bee Algorithm (HBA) and popular methods such as Taguchi’s S/N ratio and the Response Surface Methodology (RSM) in order to achieve the optimum parameters in machining applications. The experiments were performed under dry cutting conditions using three cutting speeds, three feed rates, and two depths of cuts. Quadratic regression equations were identified as the objective function for HBA to represent the relationship between the cutting parameters and responses, i.e., the cutting forces and MRR. According to the results, the RSM (72.1%) and H-ABC (64%) algorithms provide better composite desirability compared to the other techniques, namely Taguchi (43.4%) and HBA (47.2%). While the optimum parameters found by the H-ABC algorithm are better when considering cutting forces, RSM has a higher success rate for MRR. It is worth remarking that H-ABC provides an effective solution in comparison with the frequently used methods, which is promising for the optimization of the parameters in the turning of new-generation materials in the industry. There is a contradictory situation in maximizing the MRR and minimizing the cutting power simultaneously, because the affecting parameters have a reverse effect on these two response parameters. Comparing different types of methods provides a perspective in the selection of the optimum parameter design for industrial applications of the turning processes. This study stands as the first paper representing the comparative optimization approach for cutting forces and MRR.

Effects of Process Parameters on Surface Roughness and MRR in the hard turning of EN 36 steel

2018 ◽  
pp. 102-110
Author(s):  
Amritpal Singh ◽  
Rakesh Kumar
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Material Removal ◽  
Hard Turning ◽  
Control Parameter ◽  
Removal Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Cutting Condition ◽  
Dry Cutting

In the present study, Experimental investigation of the effects of various cutting parameters on the response parameters in the hard turning of EN36 steel under the dry cutting condition is done. The input control parameters selected for the present work was the cutting speed, feed and depth of cut. The objective of the present work is to minimize the surface roughness to obtain better surface finish and maximization of material removal rate for better productivity. The design of experiments was done with the help of Taguchi L9 orthogonal array. Analysis of variance (ANOVA) was used to find out the significance of the input parameters on the response parameters. Percentage contribution for each control parameter was calculated using ANOVA with 95 % confidence value. From results, it was observed that feed is the most significant factor for surface roughness and the depth of cut is the most significant control parameter for Material removal rate.

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