Optimal flank wear in turning of Inconel 625 super-alloy using ceramic tool

2016 ◽  
Vol 232 (2) ◽  
pp. 208-216 ◽  
Author(s):  
M Jahanbakhsh ◽  
A Akhavan Farid ◽  
Mohammad Lotfi
Keyword(s):  
Tool Wear ◽  
Material Removal Rate ◽  
Material Removal ◽  
Flank Wear ◽  
Removal Rate ◽  
Cutting Parameters ◽  
Optical Microscope ◽  
Inconel 625 ◽  
Depth Of Cut ◽  
Cutting Condition

Rapid tool wear is one of the major machinability aspects of nickel-based super alloys. In this article, the effect of cutting parameters on material removal rate and tool wear of a whisker ceramic insert in turning of Inconel 625 was examined. Optical microscope and scanning electron microscope were applied to measure and study tool wear mechanism. Response surface method was used to develop a mathematical model which confirmed by experimental tests. The statistical analysis done by analysis of variance showed that depth of cut is the most effective factor on the tool wear. Experiments showed that increment of feed rate had an insignificant effect on the progress of flank wear, and it is an important controlling factor when material removal rate is considered as a desired output. Finally, optimized cutting condition is presented in this work.

OPTIMUM FLANK WEAR OF TiAlN-COATED TOOL: TOWARD PRODUCTIVE ROUGH CUTTING OF INCONEL 625

2019 ◽  
Vol 26 (08) ◽  
pp. 1850230
Author(s):  
A. AKHAVAN FARID ◽  
MOHAMMAD LOTFI ◽  
M. JAHANBAKHSH
Keyword(s):  
Tool Wear ◽  
Tool Life ◽  
Flank Wear ◽  
Removal Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Inconel 625 ◽  
Depth Of Cut ◽  
Cutting Condition ◽  
Optimum Cutting

Long tool life and high material removal rate (MRR) are the two essential requirements in rough cutting of materials. The rapid rate of the flank wear propagation in machining of nickel-based superalloys has induced the utilization of low cutting parameters when the goal was set to maximize the tool life based on the machining time or cutting length. However, this method may not provide an effective rate for the material being cut. This work presents two mathematical models to find the optimum cutting parameters results for the minimum flank wear and maximum MRR. Experimental tests were carried out based on the central composite design (CCD) in rough cutting of Inconel 625 by using TiAlN-coated insert. Maximum flank wear was measured to determine the tool wear propagation. The wear mechanisms which contribute in the tool wear were analyzed by using scanning electron microscope (SEM) to evaluate the effects of cutting parameters on the flank wear propagation. The results showed that cutting speed and depth of cut had the most significant effect on the tool wear. However, optimum cutting condition was achieved by reducing the cutting speed when feed rate and depth of cut maintained at the highest level. This was associated to the interaction of cutting speed and depth of cut, and predominant of abrasion and notching at their highest levels, respectively.

Optimization of Cutting Parameters in Milling Process Using Genetic Algorithm and ANOVA (March 2020)

2020 ◽  
Vol 38 (10A) ◽  
pp. 1489-1503
Author(s):  
Marwa Q. Ibraheem
Keyword(s):  
Genetic Algorithm ◽  
Tool Wear ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Optimal Value ◽  
Optimization Of Cutting Parameters

In this present work use a genetic algorithm for the selection of cutting conditions in milling operation such as cutting speed, feed and depth of cut to investigate the optimal value and the effects of it on the material removal rate and tool wear. The material selected for this work was Ti-6Al-4V Alloy using H13A carbide as a cutting tool. Two objective functions have been adopted gives minimum tool wear and maximum material removal rate that is simultaneously optimized. Finally, it does conclude from the results that the optimal value of cutting speed is (1992.601m/min), depth of cut is (1.55mm) and feed is (148.203mm/rev) for the present work.

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.

Process Design and Optimization of end Milling Parameters of Al 7075 Metal Matrix Composite

2021 ◽  
pp. 929-937
Author(s):  
D. S. Sai Ravi Kiran ◽  
Alavilli Sai Apparao ◽  
Vempala GowriSankar ◽  
Shaik Faheem ◽  
Sheik Abdul Mateen ◽  
...  
Keyword(s):  
Tool Wear ◽  
Material Removal Rate ◽  
Metal Matrix ◽  
Material Removal ◽  
Hybrid Composites ◽  
End Milling ◽  
Removal Rate ◽  
Spindle Speed ◽  
Depth Of Cut ◽  
Weight Percentage

This paper investigates the machinability characteristics of end milling operation to yield minimum tool wear with the maximum material removal rate using RSM. Twenty-seven experimental runs based on Box-Behnken Design of Response Surface Methodology (RSM) were performed by varying the parameters of spindle speed, feed and depth of cut in different weight percentage of reinforcements such as Silicon Carbide (SiC-5%, 10%,15%) and Alumina (Al2O3-5%) in alluminium 7075 metal matrix. Grey relational analysis was used to solve the multi-response optimization problem by changing the weightages for different responses as per the process requirements of quality or productivity. Optimal parameter settings obtained were verified through confirmatory experiments. Analysis of variance was performed to obtain the contribution of each parameter on the machinability characteristics. The result shows that spindle speed and weight percentage of SiC are the most significant factors which affect the machinability characteristics of hybrid composites. An appropriate selection of the input parameters such as spindle speed of 1000 rpm, feed of 0.02 mm/rev, depth of cut of 1 mm and 5% of SiC produce best tool wear outcome and a spindle speed of 1838 rpm, feed of 0.04 mm/rev, depth of cut of 1.81 mm and 6.81 % of SiC for material removal rate.

Modelling and Optimization of End Milling Process Using TLBO and TOPSIS Algorithm

2017 ◽  
pp. 54-81 ◽  
Author(s):  
Atul Tiwari ◽  
Mohan Kumar Pradhan
Keyword(s):  
Material Removal Rate ◽  
Material Removal ◽  
Metal Cutting ◽  
End Milling ◽  
Removal Rate ◽  
Cutting Parameters ◽  
Optimization Method ◽  
Depth Of Cut ◽  
Multi Objective ◽  
Order Preference

To assure desire quality of machined products at minimum machining costs and maximum material removal rate, it is very important to select optimum parameters when metal cutting machine tool are used. Minimum Surface Roughness (Ra) is commonly desirable for the component; however Material Removal Rate (MRR) should be maximized. This chapter presents an approach for determination of the best cutting parameters precede to minimum Ra and maximum MRR simultaneously by integrating Response Surface Methodology with Multi-Objective Technique for Order Preference by Similarity to Ideal Solution and Teaching and learning based optimization algorithm in face milling of Al-6061 alloy. 30 experiments have been conducted based on RSM with 4 parameters, namely Speed, Feed, Depth of Cut and Coolant Speed and three levels each. ANOVA is performed to find the most influential input parameters for both MRR and Ra. Later the multi-objective attribution selection method TOPSIS and multi objective optimization method TLBO is used to optimize the responses.

Research on Microscopic Grain-Workpiece Interaction in Grinding through Micro-Cutting Simulation, Part 2: Factorial Study

2009 ◽  
Vol 76-78 ◽  
pp. 15-20 ◽  
Author(s):  
Lan Yan ◽  
Xue Kun Li ◽  
Feng Jiang ◽  
Zhi Xiong Zhou ◽  
Yi Ming Rong
Keyword(s):  
Cutting Force ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Shear Angle ◽  
Depth Of Cut ◽  
Specific Cutting Force ◽  
Single Grain

The grinding process can be considered as micro-cutting processes with irregular abrasive grains on the surface of grinding wheel. Single grain cutting simulation of AISI D2 steel with a wide range of cutting parameters is carried out with AdvantEdgeTM. The effect of cutting parameters on cutting force, chip formation, material removal rate, and derived parameters such as the specific cutting force, critical depth of cut and shear angle is analyzed. The formation of chip, side burr and side flow is observed in the cutting zone. Material removal rate increases with the increase of depth of cut and cutting speed. Specific cutting force decreases with the increase of depth of cut resulting in size effect. The shear angle increases as the depth of cut and cutting speed increase. This factorial analysis of single grain cutting is adopted to facilitate the calculation of force consumption for each single abrasive grain in the grinding zone.

scholarly journals Multi-Response Optimization of process Parameter in Vertical Milling Machine of EN 31 Using Taguchi Method

2021 ◽  
Vol 23 (11) ◽  
pp. 228-235
Author(s):  
Sunil Kumar ◽  
◽  
P.N . Rao ◽  
Keyword(s):  
Surface Roughness ◽  
Wear Rate ◽  
Tool Wear ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Depth Of Cut ◽  
Tool Wear Rate ◽  
Vertical Milling Machine ◽  
En 31

The purpose of this experimental research is to compare the effectiveness of using Taguchi approaches for multi-response optimization of process parameters in Vertical Milling Machine of EN 31 Material intending to minimize surface roughness and tool wear rate while maximizing material removal rate to improve the productivity of the process with coated carbide insert. Taguchi L9 and Annova have been applied for experimental design and analysis. This experiment shows that feed and depth of cut are factors that are important for tool wear, Depth of cut is a notable factor for Material Removal Rate and feed is the most notable factor for surface roughness. Spindle speed has little effect on tool wear rate, surface roughness, and material removal rate. Mathematical models for three response parameters i.e. tool wear rate, surface roughness, and material removal rate were obtained by regression analysis

scholarly journals Towards Optimization of Surface Roughness and Productivity Aspects during High-Speed Machining of Ti–6Al–4V

Materials ◽  
2019 ◽  
Vol 12 (22) ◽  
pp. 3749 ◽  
Author(s):  
Adel T. Abbas ◽  
Neeraj Sharma ◽  
Saqib Anwar ◽  
Faraz H. Hashmi ◽  
Muhammad Jamil ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Titanium Alloys ◽  
Material Removal Rate ◽  
Material Removal ◽  
High Speed ◽  
Removal Rate ◽  
Depth Of Cut ◽  
Optimization Approach ◽  
High Speed Machining

Nowadays, titanium alloys are achieving a significant interest in the field of aerospace, biomedical, automobile industries especially due to their extremely high strength to weight ratio, corrosive resistance, and ability to withstand higher temperatures. However, titanium alloys are well known for their higher chemical reactive and low thermal conductive nature which, in turn, makes it more difficult to machine especially at high cutting speeds. Hence, optimization of high-speed machining responses of Ti–6Al–4V has been investigated in the present study using a hybrid approach of multi-objective optimization based on ratio analysis (MOORA) integrated with regression and particle swarm approach (PSO). This optimization approach is employed to offer a balance between achieving better surface quality with maintaining an acceptable material removal rate level. The position of global best suggested by the hybrid optimization approach was: Cutting speed 194 m/min, depth of cut of 0.1 mm, feed rate of 0.15 mm/rev, and cutting length of 120 mm. It should be stated that this solution strikes a balance between achieving lower surface roughness in terms of Ra and Rq, with reaching the highest possible material removal rate. Finally, an investigation of the tool wear mechanisms for three studied cases (i.e., surface roughness based, productivity-based, optimized case) is presented to discuss the effectiveness of each scenario from the tool wear perspective.

Optimization of Multi-Responses in Hot Turning of Inconel 625 Alloy Using DEA-Taguchi Approach

2016 ◽  
Vol 24 ◽  
pp. 57-63 ◽  
Author(s):  
A.K. Parida ◽  
K.P. Maity
Keyword(s):  
Taguchi Method ◽  
Material Removal Rate ◽  
Surface Finish ◽  
Material Removal ◽  
Removal Rate ◽  
Machining Process ◽  
Inconel 625 ◽  
Depth Of Cut ◽  
Machining Parameter ◽  
Hot Turning

In the present work DEA (data envelopment analysis) coupled with Taguchi method has used for optimization in process parameters of hot turning operation. An experimental investigation has been carried out to study the effect of cutting parameters such as speed, feed and depth of cut during. The material removal rate and surface finish, are to be studied with respect to machining at 450 temperature by heating Inconel 625. In order to achieve both quality and productivity, optimization of both is necessary simultaneously. DEA –Taguchi method can employed for solving in multi-response problem. LINGO software was used to find out the relative efficiency and converted to S/N ratio using MINITAB software. The optimization of the machining parameter found at 100 m/min cutting speed, 0.15 mm/rev feed rate and 1 mm depth of cut. Depth of cut is the most influencing parameter which affect both surface finish and material removal rate in the machining process.

Study of the Cutting Parameters on Surface Roughness and Material Removal Rate in Hard Turning of UHMWPE

2020 ◽  
Author(s):  
César Oswaldo Aguilera-Ojeda ◽  
Alberto Saldaña-Robles ◽  
Agustín Vidal-Lesso ◽  
Israel Martínez-Ramírez ◽  
Eduardo Aguilera-Gómez
Keyword(s):  
Surface Roughness ◽  
Predictive Model ◽  
Material Removal Rate ◽  
Surface Finish ◽  
Material Removal ◽  
Removal Rate ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Feed Speed ◽  
Turning Process

Abstract The surface finish of industrial components has an important role in their performance and lifetime. Therefore, it is crucial to find the cutting parameters that provide the best surface finish. In this work, an experimental study of the effect of cutting parameters on ultra-high molecular weight polyethylene (UHMWPE) by a turning process was carried out. Today, the UHMWPE polymer continues to find applications mainly in the automotive industry and biomechanics because it is resistant to impact and corrosive materials to use. A face-centered Central Composite Design (CCD) and Response Surface Methodology (RSM) were applied to evaluate the influence of the cutting speed (Vc), feed rate (f) and depth of cut (ap) of the turning operation on the Average Surface Roughness (Ra) and Material Removal Rate (MRR). Results allowed obtaining an adjusted multivariable regression model that describes the behavior of the Ra that depends on the cutting parameters in the turning process. The predictive model of Ra showed that it fits well with a correlation coefficient (R2) around 0.9683 to the experimental data for Ra. The ANOVA results for Ra showed that the feed is the most significant factor with a contribution of 42.3 % for the term f 2, while the speed and depth of cut do not affect Ra with contributions of 0.19% and 0.18%, respectively. A reduction of feed from 0.30 to 0.18 mm·rev−1 produces a decrease in surface roughness from 6.68 to 3.81 μm. However, if the feed continued to reduce an increase in surface roughness, a feed of 0.05 mm·rev−1 induces a surface roughness of 14.93 μm. Feeds less than 0.18 mm·rev−1 cause a heat generation during turning that increases the temperature in the process zone, producing surface roughness damage of the UHMWPE polymer. Also, the results for MRR demonstrated that all of the cutting parameters are significant with contributions of 31.4%, 27.4% and 15.4% to feed, speed, and depth of cut, respectively. The desirability function allowed optimizing the cutting parameters (Vc = 250 m·min−1, ap = 1.5 mm y f = 0.27 mm·rev−1) to obtain a minimum surface roughness (Ra = 4.3 μm) with a maximum material removal rate (MMR = 97.1 cm3·min−1). Finally, the predictive model of Ra can be used in the industry to obtain predictions on the experimental range analyzed, reducing the surface roughness and the manufacturing time of UHMWPE cylindrical components.

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