Effect of Machining Parameters on Surface Roughness and Tool Flank Wear in Turning of Haynes 25 Alloy

2020 ◽  
pp. 679-686
Author(s):  
Atul B. Andhare ◽  
K. Kannathasan ◽  
Manoj Funde
Keyword(s):  
Surface Roughness ◽  
Flank Wear ◽  
Machining Parameters ◽  
Tool Flank Wear

scholarly journals Fuzzy-MOORA Based Optimization of Machining Parameters for Machinability Enhancement of Titanium

2021 ◽  
Vol 8 (2) ◽  
pp. 189-198
Author(s):  
Durwesh Jhodkar ◽  
Akhtar Khan ◽  
Kapil Gupta
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Process Parameters ◽  
Flank Wear ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Tool Flank Wear ◽  
Moora Method ◽  
Fuzzy Moora

The aim of this study is to determine the optimal combination of process parameters when machining commercially pure titanium grade 2. The unification of Multi objective optimization based on ratio analysis (MOORA) and fuzzy approach has applied to optimize the process parameters. Three process parameters i.e. cutting speed, tool overhang, and microhardness have been varied at three levels each and a total of twenty seven experiments have been conducted based on Taguchi’s L27 design of experiment technique. Cutting force, tool flank wear, and average surface roughness have been considered a machinability indicators to measure the process performance. Feed rate and depth of cut have been kept constant. Successful optimization is done and results show that machining titanium at higher cutting speed (140 m/min) and higher tool overhang length (65 mm) with medium hardness (1934 HV) results in lower cutting force, tool flank wear, and surface roughness. Outcomes of the present work reveal that the hybrid fuzzy-MOORA method is convincing enough to obtain the best process parameter combination for the best machinability while machining titanium type difficult-to-machine materials.

scholarly journals Analysis of Surface Roughness and Flank Wear Using the Taguchi Method in Milling of NiTi Shape Memory Alloy with Uncoated Tools

Coatings ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 1259
Author(s):  
Emre Altas ◽  
Hasan Gokkaya ◽  
Meltem Altin Karatas ◽  
Dervis Ozkan
Keyword(s):  
Surface Roughness ◽  
Shape Memory Alloy ◽  
Shape Memory ◽  
Flank Wear ◽  
Cutting Tools ◽  
Dominant Factor ◽  
Niti Shape Memory Alloy ◽  
Machining Parameters ◽  
Nose Radius ◽  
Dry Cutting

The aim of this study was to optimize machining parameters to obtain the smallest average surface roughness (Ra) and flank wear (Vb) values as a result of the surface milling of a nickel-titanium (NiTi) shape memory alloy (SMA) with uncoated cutting tools with different nose radius (rε) under dry cutting conditions. Tungsten carbide cutting tools with different rε (0.4 mm and 0.8 mm) were used in milling operations. The milling process was performed as lateral/surface cutting at three different cutting speeds (Vc) (20, 35 and 50 m/min), feed rates (fz) (0.03, 0.07 and 0.14 mm/tooth) and a constant axial cutting depth (0.7 mm). The effects of machining parameters in milling experiments were investigated based on the Taguchi L18 (21 × 32) orthogonal sequence, and the data obtained were analyzed using the Minitab 17 software. To determine the effects of processing parameters on Ra and Vb, analysis of variance (ANOVA) was used. The analysis results reveal that the dominant factor affecting the Ra is the cutting tool rε, while the main factor affecting Vb is the fz. Since the predicted values and measured values are very close to each other, it can be said that optimization is correct according to the validation test results.

Machining characteristics of Inconel 718 under several cutting conditions based on Taguchi method

2012 ◽  
Vol 227 (9) ◽  
pp. 1889-1897 ◽  
Author(s):  
R Thirumalai ◽  
JS Senthilkumaar ◽  
P Selvarani ◽  
S Ramesh
Keyword(s):  
Surface Roughness ◽  
Inconel 718 ◽  
Flank Wear ◽  
Optimization Technique ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Cutting Condition ◽  
Machining Parameters ◽  
Dry Machining ◽  
Noise Factors

Extensive researchers have conducted several experiments in the past for selecting the optimum parameters in machining nickel based alloy – Inconel 718. These experiments conducted so far are dealt with dry machining and flooded coolant machining of nickel alloy Inconel 718. In this research study, the usage of refrigerated coolant is also dealt with and it is compared with dry machining and flooded coolant machining. Cutting speed, feed and depth of cut are considered as the machining parameters. The effectiveness of the refrigerated coolant in machining the heat resistant super alloy material Inconel 718 with respect to these machining parameters are described in this article. The machinability studies parameters were generated with surface roughness and flank wear. The performance of uncoated carbide cutting tool was investigated at various cutting condition under dry, flooded coolant and refrigerated coolant machining. The relationship between the machining parameters and the performance measures were established and using analysis of variance significant machining parameters determined. This article made an attempt to Taguchi optimization technique to study the machinability performances of Inconel 718. Taguchi approach is an efficient and effective experimental method in which a response variable can be optimized, given various control and noise factors, using fewer experiments than a factorial design. Taguchi’s optimization analysis indicates that the factors level, its significance to influence the surface roughness and flank wear for the machining processes. Confirmation tests were conducted at an optimal condition to make a comparison between the experimental results foreseen from the mentioned correlations.

Gravitational Search Algorithm - Based Optimization of Process Parameters in Micro Turning Process

2014 ◽  
Vol 592-594 ◽  
pp. 391-394
Author(s):  
M. Durairaj ◽  
S. Gowri
Keyword(s):  
Flank Wear ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Turning Process ◽  
Tool Flank Wear ◽  
Conflicting Objectives ◽  
Micro Turning ◽  
Gravitational Search

Micro turning is a scaled down version of conventional turning process, but operating on the micro scale of machining parameters to produce micro components. This paper deals with CNC Micro turning of Inconel 600 alloy with titanium carbide coated tool. Two conflicting objectives, surface roughness and tool flank wear, are simultaneously optimized. Full factorial experiments were taken with several combinations of cutting speed, feed and depth of cut. In this report, a new optimization algorithm based on the law of gravitation and mass interactions, namely Gravitational Search Algorithm (GSA) is aimed to predict the optimal parameter conditions for controlling tool flank wear and better surface finish.

Machinability Investigation of HSLA Steel in Hard Turning with Coated Ceramic Tool: Assessment, Modeling, Optimization and Economic Aspects

2019 ◽  
Vol 18 (04) ◽  
pp. 625-655 ◽  
Author(s):  
Asutosh Panda ◽  
Sudhansu Ranjan Das ◽  
Debabrata Dhupal
Keyword(s):  
Surface Roughness ◽  
Tool Life ◽  
Hard Turning ◽  
Flank Wear ◽  
Desirability Function ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Ceramic Tool ◽  
Life Estimation

The present study addresses the machinability investigation in finish dry hard turning of high strength low alloy steel with coated ceramic tool by considering cutting speed, feed and depth of cut as machining parameters. The technological parameters like surface roughness, flank wear, chip morphology and economical feasibility have been considered to investigate the machinability performances. Twenty seven set of trials according to full factorial design of experiments are performed and analysis of variance, multiple regression method, Taguchi method, desirability function approach and finally Gilbert’s approach are subsequently applied for parametric influence study, mathematical modeling, multi-response optimization, tool life estimation and economic analysis. Results indicated that feed and cutting speed are the most significant controlled as well as dominant factors for hard turning operation if the minimization of the machined surface roughness and tool flank wear is considered. Abrasions, adhesion followed by plastic deformation have been observed to be the principal wear mechanism for tool life estimation and observed tool life for coated ceramic insert is 47[Formula: see text]min under optimum cutting conditions. The total machining cost per part is ensued to be lower ($0.29 only) as a consequence of higher tool life, reduction in downtime and enhancement in savings, which finds economical benefits in hard turning. The current work demonstrates the substitution of conventional, expensive and slow cylindrical grinding process, and proposes the most expensive CBN tool alternative using coated ceramic tools in hard turning process considering techno-economical and ecological aspects.

Study on Tool Life of Surface Textured Tool in Dry Cutting of Ti-6Al-4V Alloys

2012 ◽  
Vol 538-541 ◽  
pp. 1245-1249 ◽  
Author(s):  
Ze Wu ◽  
Jian Xin Deng ◽  
Jun Zhao
Keyword(s):  
Surface Roughness ◽  
Laser Beam ◽  
Tool Life ◽  
Flank Wear ◽  
Cutting Temperature ◽  
Dry Cutting ◽  
Laser Beam Machining ◽  
Tool Flank Wear

Surface textured tools were fabricated by laser beam machining. Dry cutting of Ti-6Al-4V alloys was carried out with these surface textured tools and conventional tools for comparison. The cutting temperature, tool flank wear and surface roughness of processed workpiece were measured. The experimental formulas of tool life based on DOT method were developed. Results show that the surface textured tool can reduce the surface roughness of workpiece, and the tool life of surface textured tool is improved by 15% or so compared with the conventional one.

scholarly journals Effects of Tool Wear on Machined Surface Integrity During Milling of Inconel 718

2021 ◽  
Author(s):  
Liang Tan ◽  
Changfeng Yao ◽  
Dinghua Zhang ◽  
Minchao Cui ◽  
Xuehong Shen
Keyword(s):  
Residual Stress ◽  
Surface Roughness ◽  
Tool Wear ◽  
Surface Integrity ◽  
Inconel 718 ◽  
Flank Wear ◽  
Cutting Temperature ◽  
Machined Surface ◽  
Tool Flank Wear ◽  
Machined Surface Integrity

Abstract This paper investigates the effects of tool wear on the machined surface integrity characteristics, including the surface roughness, surface topography, residual stress, microhardness and microstructure, during ball-end milling of Inconel 718. Tool wear, tool lifetime, and cutting force are measured. In addition, a two-dimensional finite element-based model is developed to investigate the cutting temperature distribution in the chip–tool–workpiece contact area. Results show that the ball nose end mill achieves tool lifetime of approximately 350 min. The cutting forces increase sharply with a greater tool flank wear width, while the highest cutting temperature has a decreasing tend at a flank wear width of 0.3 mm. Higher tool flank wear width produces larger surface roughness and deteriorative surface topography. A high-amplitude (approximately −700 MPa) and deep layer (approximately 120 mm) of compressive residual stress are induced by a worn tool with 0.3 mm flank wear width. The surface microhardness induced by new tool is larger than that induced by worn tool. Plastic deformation and strain streamlines are observed within 10 mm depth beneath the surface. The results in this paper provide an optimal tool wear criterion which integrates the surface integrity requirements and the tool lifetime for ball-end finish milling of Inconel 718.

scholarly journals Modeling and optimization of flank wear and surface roughness of Monel-400 during hot turning using artificial intelligence techniques

10.30544/473 ◽  
2020 ◽  
Vol 26 (1) ◽  
pp. 57-69
Author(s):  
M. Hanief ◽  
M. S. Charoo
Keyword(s):  
Surface Roughness ◽  
Power Law ◽  
Close Agreement ◽  
Flank Wear ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Power Law Model ◽  
Objective Functions ◽  
Monel 400 ◽  
Hot Turning

This work aims to model and investigate the effect of cutting speed, feed rate, depth of cut and the workpiece temperature on surface roughness and flank wear (responses) of Monel-400 during turning operation. It also aims to optimize the machining parameters of the above operation. A power-law model is developed for this purpose and is corroborated by comparing the results with the artificial neural network (ANN) model. Based on the coefficient of determination (R2), mean square error (MSE), and mean absolute percentage error (MAPE) the results of the power-law model are found to be in close agreement with that of ANN. Also, the proposed power law and ANN models for surface roughness and flank wear are in close agreement with the experiment results. For the power-law model R2, MSE, and MAPE were found to be 99.83%, 9.9×10-4, and 3.32×10-2, and that of ANN were found to be 99.91%, 5.4×10-4, and 5.96×10-2, respectively for surface roughness and flank wear. An error of 0.0642% (minimum) and 8.7346% (maximum) for surface roughness and 0.0261% (minimum) and 4.6073% (maximum) for flank wear were recorded between the observed and experimental results, respectively. In order to optimize the objective functions obtained from power-law models of the surface roughness and flank wear, GA (genetic algorithm) was used to determine the optimal values of the operating parameters and objective functions thereof. The optimal value of 2.1973 µm and 0.256 mm were found for surface roughness and flank wear, respectively.

Progressive tool flank wear and surface roughness when turning AISI 1017 mild steel using reduced thickness inserts in finishing cutting conditions

2017 ◽  
Author(s):  
Saiful Anwar Che Ghani ◽  
Mohd Hafizu Zakaria ◽  
Wan Sharuzi Wan Harun ◽  
Zakri Ghazalli
Keyword(s):  
Surface Roughness ◽  
Mild Steel ◽  
Flank Wear ◽  
Cutting Conditions ◽  
Tool Flank Wear

Modeling and optimization of hard turning of X38CrMoV5-1 steel with CBN tool: Machining parameters effects on flank wear and surface roughness

2011 ◽  
Vol 25 (11) ◽  
pp. 2843-2851 ◽  
Author(s):  
Hamdi Aouici ◽  
Mohamed Athmane Yallese ◽  
Brahim Fnides ◽  
Kamel Chaoui ◽  
Tarek Mabrouki
Keyword(s):  
Surface Roughness ◽  
Hard Turning ◽  
Flank Wear ◽  
Machining Parameters ◽  
Modeling And Optimization ◽  
Cbn Tool
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