scholarly journals EVALUATION OF SURFACE ROUGHNESS AND MATERIAL REMOVAL RATE IN ELECTRICAL DISCHARGE MACHINING OF AL-ALLOY WITH 10%SIC

2022 ◽  
Vol 23 (1) ◽  
pp. 349-357
Author(s):  
Abbas Fadhil
Keyword(s):  
Surface Roughness ◽  
Silicon Carbide ◽  
Aluminum Alloy ◽  
Material Removal Rate ◽  
Electrical Discharge ◽  
Material Removal ◽  
Removal Rate ◽  
Al Alloy ◽  
Aluminum Alloy 6061 ◽  
Alloy 6061

Aluminum-based metallic matrix compounds are widely used in industrial and aircraft manufacturing due to their advanced characteristics, such as toughness and high strength resistance to weight ratio, etc. Silicon carbide is an important industrial ceramic and it is the fourth hardest ceramic after diamond, boron nitride, and boron carbide. Owing to its low fracture toughness, it is difficult to machine silicon carbide using traditional machining processes. Electrical discharge machine can machine such materials irrespective of their hardness. Aluminum alloy 6061 and 10% SiC based-metal matrix composite were used as a workpiece that was produced by stir casting. In the experimental investigation, pulse current Pc (10, 20, and 30 A), pulse on (Pon) duration (100, 150, and 200 ?sec), and pulse off (Poff) duration (6, 12, and 24 ?sec) were treated as the input variables. The output responses were surface roughness (SR) and material removal rate (MRR). The best value for surface roughness (Ra) reached (1.032 µm) at Pc (10 A), Pon duration (100 ?sec) and Poff (15 ?sec). Also, the best result for the productivity of the process (MRR) reached (69.49 × 10-3 g/min) at Pc (30 A) Pon, (200 ?sec) and (6 ?sec) Poff. Therefore, the experimental outcomes were optimized for surface roughnes and material removal rate by adding 10% SiC to aluminum alloy 6061. ABSTRAK: Sebatian matrik logam berasaskan aluminium telah digunakan secara meluas dalam industri pembuatan dan pesawat kerana ciri-cirinya yang canggih, seperti ketahanan dan daya rintangan yang tinggi kepada nisbah berat, dan lain-lain. Silikon karbida adalah seramik industri yang penting dan ia merupakan seramik keempat terkuat setelah berlian, boron nitrida dan boron karbida. Disebabkan ketahanan frakturnya yang rendah, adalah sukar bagi menghasilkan mesin silikon karbida menggunakan proses pemesinan tradisional. Mesin pelepasan elektrik mampu menghasilkan mesin menggunakan bahan tersebut tanpa mengira kekerasan. Aloi aluminium 6061 dan komposit matrik logam berasaskan SiC 10% telah digunakan sebagai bahan kerja yang terhasil melalui tuangan kacauan. Melalui penyelidikan eksperimen, detik arus Pc (10, 20, dan 30 A), detik hadir (Pon) berdurasi (100, 150, dan 200 ?sec), dan detik henti (Poff) berdurasi (6, 12, dan 24 ?sec) dirawat sebagai pemboleh ubah input. Respon pengeluaran adalah kekasaran permukaan (SR) dan kadar penyingkiran bahan (MRR). Nilai terbaik bagi kekasaran permukaan (Ra) telah mencapai (1.032 µm) pada Pc (10 A), berdurasi Pon (100 ?sec) dan Poff (15 ?sec). Tambahan, hasil terbaik bagi proses produktiviti (MRR) mencapai (69.49 × 10-3 g/min) pada Pc (30 A) Pon, (200 ?sec) dan (6 ?sec) Poff. Oleh itu, hasil eksperimen dioptimumkan bagi permukaan kasar dan kadar penyingkiran bahan dengan tambahan 10% SiC ke aloi aluminium 6061.

An Orthogonal Experimental Analysis of WEDM-HS of Al2O3 Particle-Reinforced Aluminum Alloy 6061 with 10-Vol% Al2O3

2014 ◽  
Vol 910 ◽  
pp. 61-64 ◽  
Author(s):  
Jiang Wen Liu ◽  
Yong Zhong Wu
Keyword(s):  
Aluminum Alloy ◽  
Pulse Duration ◽  
Material Removal Rate ◽  
Duty Cycle ◽  
Experimental Analysis ◽  
Material Removal ◽  
Removal Rate ◽  
Machining Parameters ◽  
Aluminum Alloy 6061 ◽  
Alloy 6061

In wire electro-discharge machining with an extremely high travelling speed of wire electrode (WEDM-HS), the emulsion is used as working liquid. Because there exists a functional electrolyte, the EDM spark can operate under a relatively large spark gap size condition, and this would facilitate the removal of machined debris. An investigation has been made into the machining feasibility when WEDM-HS has been employed to process Al2O3particle reinforced aluminum alloy 6061 with 10-vol% Al2O3(10ALO). And the material removal rate (MRR) has been examined in this study. Since there are many factors that can influence the MRR in the WEDM-HS process, in order to determine which is the most important factor and to optimize the machining parameters, the relative importance of the various machining parameters on material removal rate was established by utilizing an orthogonal experimental analysis. The results of the analysis suggest that to achieve a high MRR for particulate reinforced aluminum 6061 with 10-vol% Al2O3, the duty cycle is the most influential factor among current, pulse duration and duty cycle. And the impact of the different factors follows the sequence of duty cycle > current > pulse duration.

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 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.

scholarly journals Experimental Study During Electrical Discharge Machining of Reinforced Carbon Fiber Plastic Material

2021 ◽  
Vol 9 (8) ◽  
pp. 1445-1451
Author(s):  
Gaurav Pandey
Keyword(s):  
Surface Roughness ◽  
Carbon Fiber ◽  
Wear Rate ◽  
Material Removal Rate ◽  
Electrical Discharge ◽  
Material Removal ◽  
Removal Rate ◽  
Fiber Composite ◽  
Electrode Wear ◽  
Machining Parameters

Abstract: The proper selection of machining conditions and machining parameter is an important aspect, before going to machine a carbon-fiber composite material by Die sinking electrical discharge machining (EDM). Because these conditions will determine such important characteristics as; Material removal rate (MRR), Electrode wears rate (EWR), and Surface roughness (R). The purpose of this work is to determine the optimal values of machining parameters of electrical discharge machine, while machining carbon-fiber-composite with copper electrode. The work has been based on the affect of four design factors: pulse current(Ip) supplied by power supply system of electrical discharge machine (EDM), pulse-on-time(TON), gap voltage(Vg) and duty cycle () on such characteristic like material removal rate (MRR), electrode wear rate(EWR), and surface roughness(Ra) on work-piece surface. This work has been done by means of the technique of design of experiment (DOE), which provides us to perform the above-mentioned analysis with small number of experiments. In this work, a L9 orthogonal array is used to design the experiment. The adequate selection of machining parameters is very important in manufacturing system, because these parameters determine the surface quality and dimensional accuracy of the manufactured part. The optimal setting of the parameters are determined through experiments planned, conducted and analyzed using the Taguchi method. It is found that material removal rate (MRR) reduces substantially, within the region of experimentation, if the parameters are set at their lowest values, while the parameters set at their highest values increases electrode wear rate (EWR). Keywords: EDM, Material removal rate, Surface roughness, Tool wear rate,

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