Investigation of Trochoidal Milling in Nickel-Based Superalloy Inconel 738 and Comparison With End Milling

2014 ◽  
Author(s):  
Abram Pleta ◽  
Durul Ulutan ◽  
Laine Mears
Keyword(s):  
Tool Wear ◽  
Material Removal Rate ◽  
Material Removal ◽  
End Milling ◽  
Removal Rate ◽  
Extreme Environments ◽  
High Strength ◽  
Machining Time ◽  
Trochoidal Milling ◽  
Nickel Based Superalloy

Nickel-based superalloys are designed for use in extreme environments and are getting progressively better for these environments, therefore much harder to machine. They play a crucial role in elevated temperature applications where high strength, high resistance to corrosion and creep resistance are required. Machinability suffers as a result of these properties and harsh machining conditions occur, resulting in high cutting forces and tool wear. To combat the difficulties in the machining of nickel-based superalloys, such as poor thermal diffusivity and high levels of abrasive wear, trochoidal milling was introduced as an alternative method of milling. This method of milling combines linear motion with uniform circular motion, reducing chip load in exchange for increased machining time. Industry is averse to its widespread adoption due to increasing cycle times when compared to conventional milling methods, however it has been shown that overall productivity can be improved due to less tool wear with a more predictable behavior. This work characterizes the effects of trochoidal milling and provides a comparison of trochoidal milling with a traditional milling technique, end milling, for the machining of Inconel 738. In order to compare the trochoidal and conventional machining approaches directly, metrics of productivity normalized to tool wear are introduced. The normalized metrics introduced in this study aim to provide a more representative comparison of productivity and efficiency characteristics: volumetric material removal per unit tool wear (MR/VB) and the material removal rate per unit tool wear (MRR/VB). It was found that significantly higher volumetric material removal is possible using trochoidal milling, and fewer tools are needed; material removal rates that competitive with end milling can be achieved. When the amount of time spent on tool change for the same volume of material removal is considered, material removal rate of trochoidal milling can even be higher than end milling, indicating that better productivity and efficiency of the process is possible at reduced tooling costs.

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.

Effect of SiC-Cu Electrode on Material Removal Rate, Tool Wear and Surface Roughness in EDM Process

2020 ◽  
Vol 38 (9A) ◽  
pp. 1406-1413
Author(s):  
Yousif Q. Laibia ◽  
Saad K. Shather
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Material Removal Rate ◽  
Material Removal ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
304 Stainless Steel ◽  
Tool Electrode ◽  
Pulse Time ◽  
Edm Process

Electrical discharge machining (EDM) is one of the most common non-traditional processes for the manufacture of high precision parts and complex shapes. The EDM process depends on the heat energy between the work material and the tool electrode. This study focused on the material removal rate (MRR), the surface roughness, and tool wear in a 304 stainless steel EDM. The composite electrode consisted of copper (Cu) and silicon carbide (SiC). The current effects imposed on the working material, as well as the pulses that change over time during the experiment. When the current used is (8, 5, 3, 2, 1.5) A, the pulse time used is (12, 25) μs and the size of the space used is (1) mm. Optimum surface roughness under a current of 1.5 A and the pulse time of 25 μs with a maximum MRR of 8 A and the pulse duration of 25 μs.

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.

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.

Parametric Study of Micro Machining Three Dimensional Microstructure with the Tiny-Grinding Wheel Based on the EMR Effect

2010 ◽  
Vol 447-448 ◽  
pp. 193-197
Author(s):  
Wei Qiang Gao ◽  
Qiu Sheng Yan ◽  
Yi Liu ◽  
Jia Bin Lu ◽  
Ling Ye Kong
Keyword(s):  
Magnetic Field ◽  
Material Removal Rate ◽  
Feed Rate ◽  
Material Removal ◽  
Rotation Speed ◽  
Optical Glass ◽  
Removal Rate ◽  
Grinding Wheel ◽  
Machining Time ◽  
Fluctuation Phenomenon

Electro-magneto-rheological (EMR) fluids, which exhibit Newtonian behavior in the absence of a magnetic field, are abruptly transformed within milliseconds into a Bingham plastic under an applied magnetic field, called the EMR effect. Based on this effect, the particle-dispersed EMR fluid is used as a special instantaneous bond to cohere abrasive particles and magnetic particles together so as to form a dynamical, flexible tiny-grinding wheel to machine micro-groove on the surface of optical glass. Experiments were conducted to reveal the effects of process parameters, such as the feed rate of the horizontal worktable, feeding of the Z axis, machining time and machining gap, on material removal rate of glass. The results indicate that the feed rate of the worktable at horizontal direction has less effect on material removal rate, which shows a fluctuation phenomenon within a certain range. The feed rate of the Z axis directly influences the machining gap and leads to a remarkable change on material removal rate. Larger material removal rate can be obtained when the feeding frequency of Z direction is one time per processing. With the increase of rotation speed of the tool, material removal rate increases firstly and decreases afterwards, and it gets the maximum value with the rotation speed of 4800 rev/min. The machining time is directly proportional to material removal amount, but inversely proportional to material removal rate. Furthermore, material removal rate decreases with the increase of the machining gap between the tool and the workpiece. On the basis of above, the machining mode with the tiny-grinding wheel based on the EMR effect is presented.

Investigation of Surface Roughness and Material Removal Rate for High Speed Micro End Milling on PMMA

2015 ◽  
Vol 1115 ◽  
pp. 12-15
Author(s):  
Nur Atiqah ◽  
Mohammad Yeakub Ali ◽  
Abdul Rahman Mohamed ◽  
Md. Sazzad Hossein Chowdhury
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Feed Rate ◽  
Material Removal ◽  
High Speed ◽  
End Milling ◽  
Removal Rate ◽  
Spindle Speed ◽  
Depth Of Cut ◽  
Micro End Milling

Micro end milling is one of the most important micromachining process and widely used for producing miniaturized components with high accuracy and surface finish. This paper present the influence of three micro end milling process parameters; spindle speed, feed rate, and depth of cut on surface roughness (Ra) and material removal rate (MRR). The machining was performed using multi-process micro machine tools (DT-110 Mikrotools Inc., Singapore) with poly methyl methacrylate (PMMA) as the workpiece and tungsten carbide as its tool. To develop the mathematical model for the responses in high speed micro end milling machining, Taguchi design has been used to design the experiment by using the orthogonal array of three levels L18 (21×37). The developed models were used for multiple response optimizations by desirability function approach to obtain minimum Ra and maximum MRR. The optimized values of Ra and MRR were 128.24 nm, and 0.0463 mg/min, respectively obtained at spindle speed of 30000 rpm, feed rate of 2.65 mm/min, and depth of cut of 40 μm. The analysis of variance revealed that spindle speeds are the most influential parameters on Ra. The optimization of MRR is mostly influence by feed rate. Keywords:Micromilling,surfaceroughness,MRR,PMMA

CHARACTERIZATION OF ZrB2-SiC COMPOSITES WITH AN ANALYTICAL STUDY ON MATERIAL REMOVAL RATE AND TOOL WEAR RATE DURING ELECTRICAL DISCHARGE MACHINING

2016 ◽  
Vol 40 (3) ◽  
pp. 331-349 ◽  
Author(s):  
S. Sivasankar ◽  
R. Jeyapaul
Keyword(s):  
Wear Rate ◽  
Tool Wear ◽  
Relative Density ◽  
Material Removal Rate ◽  
Electrical Discharge ◽  
Material Removal ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Tool Wear Rate ◽  
Tool Materials

This research work concentrates on Electrical Discharge Machining (EDM) performance evaluation of ZrB2- SiC ceramic matrix composites with different tool materials at various machining parameters. Monolithic ZrB2 possesses lower relative density (98.72%) than composites. ZrB2 with 20 Vol.% of SiC possesses 99.74% of the relative density with improved hardness values. Bend strength and Young’s modulus increase with SiC addition until it reaches 20 Vol% and then decreasing. EDM performance on tool materials of tungsten, niobium, tantalum, graphite and titanium at various levels of pulse on time and pulse off time are analyzed. Graphite produces the best Material removal rate (MRR) for all the workpieces. Tool wear rate decreases with melting point and thermal conductivity of the tool material.

scholarly journals Investigation an assisting electrode powder mixed electrical discharge machining of nonconductive ceramic

2021 ◽  
Author(s):  
Dragan Rodic ◽  
Marin Gostimirovic ◽  
Milenko Sekulic ◽  
Borislav Savkovic ◽  
Branko Strbac
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Material Removal Rate ◽  
Electrical Discharge ◽  
Material Removal ◽  
Metal Removal ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Positive Effects ◽  
Assisting Electrode

Abstract It is well known that electrical discharge machining can be used in the processing of nonconductive materials. In order to improve the efficiency of machining modern engineering materials, existing electrical discharge machines are constantly being researched and improved or developed. The current machining of non-conductive materials is limited due to the relatively low material removal rate and high surface roughness. A possible technological improvement of electrical discharge machining can be achieved by innovations of existing processes. In this paper, a new approach for machining zirconium oxide is presented. It combines electrical discharge machining with assisting electrode and powder-mixed dielectric. The assisting electrode is used to enable electrical discharge machining of nonconductive material, while the powder-mixed dielectric is used to increase the material removal rate, reduce surface roughness, and decrease relative tool wear. The response surface method was used to generate classical mathematical models, analyzing the output performances of surface roughness, material removal rate and relative tool wear. Verification of the obtained models was performed based on a set of new experimental data. By combining these latest techniques, positive effects on machining performances are obtained. It was found that the surface roughness was reduced by 18%, the metal removal rate was increased by about 12% and the relative tool wear was reduced by up to 6% compared to electrical discharge machining with supported electrode without powder.

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