scholarly journals Machinability, Modelling and Statistical Analysis of In-Situ Al–Si–TiB2 Composites

2019 ◽  
Vol 3 (1) ◽  
pp. 28 ◽  
Author(s):  
Jimmy Karloopia ◽  
Shaik Mozammil ◽  
Pradeep Jha
Keyword(s):  
Surface Roughness ◽  
Statistical Analysis ◽  
Tool Wear ◽  
Cutting Forces ◽  
Elevated Temperatures ◽  
Optimization Technique ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Conventional Machining

Aluminum and its alloys have numerous applications in manufacturing, aerospace, and automotive industries. At elevated temperatures, they start to fail in fulfilling their roles and functions. Aluminum-based metal matrix composites (MMCs) are good alternatives for metal and alloys due to their excellent properties. However, the conventional machining of several composites shows complications for a number of reasons, such as high tool wear, poor surface roughness, high machining cost, cutting forces, etc. Numerous studies have already been conducted on the machinability of various MMCs, but the machinability of Al–Si–TiB2 composite is still not well studied. It is of utmost importance that several process parameters of conventional machining are precisely controlled as well as optimized. In this study an effort was made to optimize input parameters such as cutting speed, depth of cut, and feed to obtain well-finished final components with the minimum cutting force and tool wear. These progressions are involved with multiple response characteristics, therefore the exploration of an appropriate multi-objective optimization technique was indeed essential. The performance characteristics of cutting forces and surface roughness were considered for optimization of the machining parameters. Analysis of variance (ANOVA) was employed for the optimization and statistical analysis.

scholarly journals Optimization of Machining Parameters on 7075 Aluminum Alloy using Taguchi and ANOVA for Surface Roughness

2020 ◽  
Vol 8 (5) ◽  
pp. 90-95
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Electrical Discharge Machining ◽  
Optimization Technique ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Anova Analysis ◽  
Tool Wear Rate ◽  
Made In

Optimization of the parameter to provide best solution to reduce the tool wear , surface roughness, cutting forces presented using optimization technique .In present work an experimental study is made. In this Taguchi design of experiment methodology for optimization of parameters on 7075Aluminium alloy using tungsten coated electrode . Experiments were conducted based on L27 standard orthogonal array with three processes parameters are cutting speed, feed, depth of cut . Electrical discharge machining is generally calculated on the basis of Surface Roughness (SR),Tool wear rate (TWR) and cutting force (CF) .The ANOVA(Analysis Of Variance) is used to study the performance characteristics in turning operation . ANOVA placed an important role for producing higher roughness . Finally the software ,MINITAB 17 was used and results obtained

Multiobjective Optimization of End Milling HCHCr Using AlCrN PVD Coated Cutters With MOGA and RSMO

2014 ◽  
Author(s):  
Shantisagar K. Biradar ◽  
Geeta S. Lathkar
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Multiobjective Optimization ◽  
End Milling ◽  
Dominant Role ◽  
Optimization Technique ◽  
Cutting Speed ◽  
Optimization Techniques ◽  
Depth Of Cut ◽  
Machining Parameters

Here the End milling is studied for optimization of responses such as surface roughness and tool wear while machining HCHCr. These two conflicting responses decide the quality of process; therefore the multiobjective optimization technique is used. The Response Surface Optimizer (RSMO) and Multiobjective Genetic Algorithm (MOGA) were used as the multiobjective optimization techniques. The PVD coating of 2.5 micron AlCrN was used on four flute HSS End milling cutter. Input machining parameters were cutting speed, feed rate, depth of cut and percentage concentration of the solid lubricant MoS2 mixed with SAE-20 base oil. The experimentation was carried out using two level full factorial design concept while ANOVA technique has been used to verify the adequacy of mathematical model. It was found that the cutting speed (V) is having most dominant role on surface roughness and tool wear. The sensitivity analysis was carried out for studying sensitivity of input parameters for the responses.

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.

scholarly journals Statistical analysis of energy consumption, tool wear and surface roughness in machining of Titanium alloy (Ti-6Al-4V) under dry, wet and cryogenic conditions

2019 ◽  
Vol 10 (2) ◽  
pp. 561-573 ◽  
Author(s):  
Muhammad Ali Khan ◽  
Syed Husain Imran Jaffery ◽  
Mushtaq Khan ◽  
Muhammad Younas ◽  
Shahid Ikramullah Butt ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Effective Means ◽  
Sustainable Manufacturing ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Specific Cutting Energy ◽  
Cutting Energy ◽  
Positive Effect

Abstract. Productivity and economy are key elements of any sustainable manufacturing system. While productivity is associated to quantity and quality, economy focuses on energy efficient processes achieving an overall high output to input ratio. Machining of hard-to-cut materials has always posed a challenge due to increased tool wear and energy loss. Cryogenics have emerged as an effective means to improve sustainability in the recent past. In the present research the use of cooling conditions has been investigated as an input variable to analyze its effect on tool wear, specific cutting energy and surface roughness in combination with other input machining parameters of feed rate, cutting speed and depth of cut. Experimental design was based on Taguchi design of experiment. Analysis of Variance (ANOVA) was carried out to ascertain the contribution ratio of each input. Results showed the positive effect of coolant usage, particularly cryogenic, on process responses. Tool wear was improved by 33 % whereas specific cutting energy and surface roughness were improved by 10 % and 9 % respectively by adapting the optimum machining conditions.

The Effect of Cutting Speed and Feed Rate on Surface Roughness and Tool Wear when Machining Machining D2 Steel

2017 ◽  
Vol 909 ◽  
pp. 80-85 ◽  
Author(s):  
Mohd Rasidi Ibrahim ◽  
Tharmaraj Sreedharan ◽  
Nurul Aisyah Fadhlul Hadi ◽  
Mohammad Sukri Mustapa ◽  
Al Emran Ismail ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Surface Quality ◽  
Feed Rate ◽  
Input Parameter ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
D2 Steel

Machining parameters is a main aspect in performing turning operations using lathe machines. Cutting parameters such as cutting speed, feed rate and depth of cut gives big influence on the dynamic behavior of the machining system. In machining parts, surface quality and tool wear are the most crucial customer requirements. This is because the major indication of surface quality on machined part is the surface roughness and the value of tool wear. Hence, to improve the surface roughness and minimize the forming of tool wear, the optimum feed rate and cutting speed will be determined. The input parameter such as cutting speed, feed rate and depth of cut always influence the tool wear, surface roughness, cutting force, cutting temperature, tool life and dimensional accuracy. The D2 steel was being investigated from the perspective of the effect of cutting speed and feed rate on its surface roughness and tool wear. The results show that cutting speed is the main parameter which affects the surface roughness where the most optimum parameter would be at cutting speed of 173, 231 and 288 m/min with feed rate of 0.15 mm/rev. The tool wear strongly affected by feed rate where at 0.15 mm/rev the tool wear value is the lowest. The combination of high cutting speed and low feed rate was the best parameter to achieve smooth surface roughness.

scholarly journals Analysis of Surface Roughness and Cutting Forces in Hard Turning of 42CrMo4 Steel using Taguchi and RSM Method

Mechanika ◽  
2020 ◽  
Vol 26 (3) ◽  
pp. 231-241 ◽  
Author(s):  
Mustafa ÖZDEMİR ◽  
Mehmet Tuncay KAYA ◽  
Hamza Kemal AKYILDIZ
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Cutting Forces ◽  
Tangential Force ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Radial Force ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Feed Force

In this study, effects of cutting speed (V), feed rate (f), depth of cut (a) and tool tip radius (R) on  surface roughness (Ra, Rz, and Rt) and cutting forces (radial force (Fx), tangential force (Fy), and feed force (Fz)) in hard finish turning processes of hardened 42CrMo4 (52 HRC) material was investigated experimentally. Taguchi’s mixed level parameter design (L18) is used for the experimental design (2x1,3x3). The signal-to-noise ratio (S/N) was used in the evaluation of test results.  By using Taguchi method, cutting parameters giving optimum surface roughness and cutting forces were determined. Regression analyses are applied to predict surface roughness and cutting forces. Analysis of variance (ANOVA) is used to determine the effects of the machining parameters on surface roughness and cutting forces. According to ANOVA analysis, the most important cutting parameters were found to be feed rate for surface roughness and depth of cut among cutting forces.  By conducting validation experiments, optimization was seen to be applied successfully.

Experimental investigations of cutting parameters’ influence on cutting forces and surface roughness in turning of Inconel alloy X-750 with biodegradable vegetable oil

2015 ◽  
Vol 231 (9) ◽  
pp. 1516-1527 ◽  
Author(s):  
Ahmadreza Hosseini Tazehkandi ◽  
Mohammadreza Shabgard ◽  
Farid Pilehvarian ◽  
Nakisa Farshfroush
Keyword(s):  
Surface Roughness ◽  
Vegetable Oil ◽  
Feed Rate ◽  
Cutting Forces ◽  
Cutting Speed ◽  
Cutting Fluid ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Inconel Alloy ◽  
Coated Carbide

Nickel-based Inconel X-750 superalloy is widely applied in aerospace industry and manufacturing of gas turbine blades, power generators and heat exchangers due to its exclusive properties. As a consequence of low heat transfer coefficient and work-hardening properties, this alloy is known as a poorly machinable alloy. In this work, effect of machining parameters (cutting speed, feed rate and depth of cut) on cutting forces and surface roughness was investigated during turning of Inconel alloy X-750 with coated carbide tool. In order to meet the demands of the environment-friendly cutting processes and human health, biodegradable vegetable oil (BioCut 4600) was selected as the cutting fluid. The results were analyzed using response surface methodology and statistical analysis of variance, and mathematical models for cutting forces and surface roughness were proposed. Results indicated that feed rate and cutting speed were the most effective parameters on the surface roughness. However, depth of cut was the most effective parameter on cutting forces in comparison with cutting speed and feed rate. Eventually, in order to achieve the main aims of industrial production in large amounts and green manufacturing, the ranges for the best cutting conditions were presented.

Multiresponse Optimization of Al Alloy-SiC Composite Machining Parameters for Minimum Tool Wear and Maximum Metal Removal Rate

2013 ◽  
Vol 135 (2) ◽  
Author(s):  
Rajesh Kumar Bhushan
Keyword(s):  
Tool Wear ◽  
Metal Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Al Alloy ◽  
Machining Parameters ◽  
Metal Removal Rate ◽  
Nose Radius ◽  
Multiresponse Optimization

Optimization in turning means determination of the optimal set of the machining parameters to satisfy the objectives within the operational constraints. These objectives may be the minimum tool wear, the maximum metal removal rate (MRR), or any weighted combination of both. The main machining parameters which are considered as variables of the optimization are the cutting speed, feed rate, depth of cut, and nose radius. The optimum set of these four input parameters is determined for a particular job-tool combination of 7075Al alloy-15 wt. % SiC (20–40 μm) composite and tungsten carbide tool during a single-pass turning which minimizes the tool wear and maximizes the metal removal rate. The regression models, developed for the minimum tool wear and the maximum MRR were used for finding the multiresponse optimization solutions. To obtain a trade-off between the tool wear and MRR the, a method for simultaneous optimization of the multiple responses based on an overall desirability function was used. The research deals with the optimization of multiple surface roughness parameters along with MRR in search of an optimal parametric combination (favorable process environment) capable of producing desired surface quality of the turned product in a relatively lesser time (enhancement in productivity). The multi-objective optimization resulted in a cutting speed of 210 m/min, a feed of 0.16 mm/rev, a depth of cut of 0.42 mm, and a nose radius of 0.40 mm. These machining conditions are expected to respond with the minimum tool wear and maximum the MRR, which correspond to a satisfactory overall desirability.

scholarly journals Milling Inconel 718 Workpiece With Cryogenically Treated And Untreated Cutting Tools

2021 ◽  
Author(s):  
Hüseyin Gürbüz ◽  
Şehmus Baday
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Abrasive Wear ◽  
Inconel 718 ◽  
Cutting Tool ◽  
Cutting Tools ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Cutting Tool Wear ◽  
Feed Force

Abstract Although Inconel 718 is an important material for modern aircraft and aerospace, it is a kind material, which is known to have low machinability. Especially, while these types of materials are machined, high cutting temperatures, BUE on cutting tool, high cutting forces and work hardening occur. Therefore, in recent years, instead of producing new cutting tools that can withstand these difficult conditions, cryogenic process, which is a heat treatment method to increase the wear resistance and hardness of the cutting tool, has been applied. In this experimental study, feed force, surface roughness, vibration, cutting tool wear, hardness and abrasive wear values that occurred as a result of milling of Inconel 718 material by means of cryogenically treated and untreated cutting tools were investigated. Three different cutting speeds (35-45-55 m/min) and three different feed rates (0.02-0.03-0.04 mm/tooth) at constant depth of cut (0.2 mm) were used as cutting parameters in the experiments. As a result of the experiments, lower feed forces, surface roughness, vibration and cutting tool wear were obtained with cryogenically treated cutting tools. As the feed rate and cutting speed were increased, it was seen that surface roughness, vibration and feed force values increased. At the end of the experiments, it was established that there was a significant relation between vibration and surface roughness. However, there appeared an inverse proportion between abrasive wear and hardness values. While BUE did not occur during cryogenically treated cutting tools, it was observed that BUE occurred in cutting tools which were not cryogenically treated.

Statistical Analysis of Process Parameters in Drilling of Al/Al2O3p Metal Matrix Composites

2014 ◽  
Vol 14 (3) ◽  
pp. 171-175 ◽  
Author(s):  
Yashvir Singh ◽  
Amneesh Singla ◽  
Ajay Kumar
Keyword(s):  
Surface Roughness ◽  
Statistical Analysis ◽  
Process Parameters ◽  
Metal Matrix ◽  
Design Method ◽  
Experimental Studies ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Signal To Noise ◽  
Drilling Parameters

AbstractThis paper presents a statistical analysis of process parameters for surface roughness in drilling of Al/Al2O3p metal matrix composite. The experimental studies were conducted under varying spindle speed, feed rate, point angle of drill. The settings of drilling parameters were determined by using Taguchi experimental design method. The level of importance of the drilling parameters is determined by using analysis of variance. The optimum drilling parameter combination was obtained by using the analysis of signal-to-noise ratio. Through statistical analysis of response variables and signal-to-noise ratios, the determined significant factors are depth of cut and drill point angle with the contributions of 87% and 12% respectively, whereas the cutting speed is insignificant contributing by 1% only. Confirmation tests verified that the selected optimal combination of process parameter through Taguchi design was able to achieve desired surface roughness.

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