scholarly journals Study on Kerosene-submerged Jet Electrochemical Machining and Optimization of the Electrochemical Machining Parameters

2021 ◽  
pp. 151030
Author(s):  
Xinchao Li ◽  
Keyword(s):  
Electrochemical Machining ◽  
Machining Parameters ◽  
Submerged Jet ◽  
Jet Electrochemical Machining

Optimization of laser-assisted jet electrochemical machining parameters by grey relational analysis and fuzzy logic

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anup Malik ◽  
Neel Sanghvi
Keyword(s):  
Fuzzy Logic ◽  
Grey Relational Analysis ◽  
Removal Rate ◽  
Electrochemical Machining ◽  
Machining Parameters ◽  
Taper Angle ◽  
Content Type ◽  
Relational Analysis ◽  
Grey Relational ◽  
Jet Electrochemical Machining

Purpose The purpose of this paper is to optimize the laser-assisted jet electrochemical machining parameters, namely, supply voltage, inter-electrode gap, duty cycle and electrolyte concentration during machining of WC-Co composite using grey relational analysis and fuzzy logic. Design/methodology/approach In this work, experiments were carried out as per the Taguchi methodology and an L16 orthogonal array was used to study the influence of various combinations of process parameters on material removal rate, hole taper angle and surface roughness height. As a dynamic approach, the multiple response optimization was carried out using grey relational analysis and fuzzy logic. Findings The process parameters were optimized using grey relational analysis and fuzzy logic for different machining conditions such as balanced manufacturing, high-speed manufacturing and high-quality manufacturing. The research documented in this paper can be scaled up for case studies regarding industrial applications to compare optimization methods for manufacturing processes that are already being carried out. Originality/value An attempt to optimize material removal rate, hole taper angle and surface roughness height together by a combined approach of grey relational analysis and fuzzy logic has not been previously done.

Electrochemical Micro Machining of Stainless Steel with Voltage Pulses

2009 ◽  
Vol 69-70 ◽  
pp. 219-224
Author(s):  
Hui Chen ◽  
Zhen Long Wang ◽  
Zi Long Peng ◽  
Ying Huai Dong ◽  
Wan Sheng Zhao
Keyword(s):  
Stainless Steel ◽  
Oxide Layer ◽  
Electrochemical Machining ◽  
Electrolyte Composition ◽  
Machining Parameters ◽  
Micro Machining ◽  
Short Pulses ◽  
Is Research ◽  
Micro Holes ◽  
Voltage Pulses

The purpose of this paper is to study electrochemical micro machining (ECM) technology on stainless steel. The micro machining of stainless steel is difficult by electrochemical machining, especially in machining deep micro holes, because of an oxide layer formed on the surface. To machining stainless steel, HF is usually used in electrolyte to destabilize the oxide layer. In this paper, ECM of stainless steel by applying short pulses in less toxic and corrosive electrolyte is research. The influence of electrochemical machining parameters such as voltage, current, electrolyte composition to machine stainless steel was investigated. The results showed that the oxide layer can be reduced by adding chloride and complex.

Multi-Response Optimization of Electrochemical Machining of Al-Si/B4C Composites Using RSM

2013 ◽  
Vol 3 (3) ◽  
pp. 42-56 ◽  
Author(s):  
Sadineni Rama Rao ◽  
G. Padmanabhan
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Feed Rate ◽  
Electrolyte Concentration ◽  
Electrochemical Machining ◽  
Casting Process ◽  
Stir Casting ◽  
Machining Parameters ◽  
Electron Microscopic ◽  
Sem Images

The present work reports the electrochemical machining (ECM) of the aluminium-silicon alloy/boron carbide (Al-Si /B4C) composites, fabricated by stir casting process with different weight % of B4C particles. The influence of four machining parameters including applied voltage, electrode feed rate, electrolyte concentration and percentage of reinforcement on the responses surface roughness (SR) and radial over cut (ROC) were investigated. The process parameters are optimized based on the response surface methodology (RSM) and the optimum values for minimizing surface roughness and radial over cut are voltage 15.25 V, feed rate 1.0 mm/min, electrolyte concentration 13.56g/lit and percentage of reinforcement 7.36 wt%. The quality of the machined surfaces is studied by using scanning electron microscopic (SEM) images. The surface plots are generated to study the effect of process parameters and their interaction on the surface roughness and radial over cut, for the machined Al-Si/B4C composites.

Fabrication of Micro Structures by Ultra Short Voltage Pulse Electrochemical Machining

2009 ◽  
Vol 419-420 ◽  
pp. 813-816 ◽  
Author(s):  
Hui Chen ◽  
Zhen Long Wang ◽  
Zi Long Peng ◽  
Wan Sheng Zhao
Keyword(s):  
Voltage Pulse ◽  
Electrochemical Machining ◽  
Pulse Frequency ◽  
Machining Accuracy ◽  
Machining Parameters ◽  
Stray Current ◽  
Micro Fabrication ◽  
Micro Hole ◽  
Micro Structures ◽  
Machining Localization

. The purpose of this paper is to study the application of electrochemical machining (ECM) technology for the fabrication of micro structures. The stray current corrosion, i.e. machining localization is a critical obstacle to micro fabrication for ECM. To machine micro structures by electrochemical machining ultra short voltage pulse is used. The effects of electrochemical machining parameters such as voltage, pulse duration, pulse frequency, and electrolyte composition on the machining accuracy were studied. In experiments, a micro hole was machined on stainless steel with cylindrical and square electrodes to investigate these effects.

Machining Parameter Optimization of Aero-Engine Blade in Electrochemical Machining Based on BP Neural Network

2010 ◽  
Vol 121-122 ◽  
pp. 893-899 ◽  
Author(s):  
Zhi Yong Li ◽  
Hua Ji ◽  
Hong Li Liu
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Electrochemical Machining ◽  
Machining Accuracy ◽  
Machining Parameters ◽  
Parameter Combination ◽  
Aero Engine ◽  
Engine Blade ◽  
Blade Machining ◽  
Machining Parameter

Because the process of blade in electrochemical machining(EMC) can be effected by many factors, such as blade shapes, machining electrical field, electrolyte fluid field and anode electrochemical dissolution, different ECM machining parameters maybe result in great affections on blade machining accuracy. Regard some type of aero-engine blade as research object, five main machining parameters, applied voltage, initial machining gap, cathode feed rate, electrolyte temperature and pressure difference between electrolyte inlet and outlet, have been evaluated and optimized based on BP neural network technique. From 3125 possible machining parameter combinations, 657 optimized parameter combinations are discovered. To verify the validity of the optimized ECM parameter combination, a serial of machining experiments have been conducted on an industrial scale ECM machine, and the experiment results demonstrates that the optimized ECM parameter combination not only can satisfy the manufacturing requirements of blade fully but has excellent ECM process stability.

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