Selection of the optimal electrochemical machining process parameters using biogeography-based optimization algorithm

2012 ◽  
Vol 64 (5-8) ◽  
pp. 781-791 ◽  
Author(s):  
Rajarshi Mukherjee ◽  
Shankar Chakraborty
Keyword(s):  
Process Parameters ◽  
Optimization Algorithm ◽  
Electrochemical Machining ◽  
Machining Process ◽  
Selection Of

scholarly journals Parametric analysis of dry machining process using a novel integrated multi-attribute decision making approach

2022 ◽  
Vol 11 (2) ◽  
pp. 193-202
Author(s):  
G. Venkata Ajay Kumar ◽  
A. Ramaa ◽  
M. Shilpa
Keyword(s):  
Decision Making ◽  
Process Parameters ◽  
Machining Process ◽  
Machining Parameters ◽  
Machining Processes ◽  
Order Preference ◽  
Dry Conditions ◽  
Criteria Importance ◽  
The Right ◽  
Selection Of

In most of the machining processes, the complexity arises in the selection of the right process parameters, which influence the machining process and output responses such as machinability and surface roughness. In such situations, it is important to estimate the inter-relationships among the output responses. One such method, Decision-Making Trial and Evaluation Laboratory (DEMATEL) is applied to study the inter-relationships of the output responses. Estimation of proper weights is also crucial where the output responses are conflicting in nature. In the current study, DEMATEL technique is used for estimating the inter-relationships for output responses in machining of EN 24 alloy under dry conditions. CRiteria Importance Through Inter-criteria Correlation (CRITIC) method is used to estimate the weights and finally the optimal selection of machining parameters is carried out using Techniques for Order Preference by Similarity to an Ideal Solution (TOPSIS) method. The model developed guides the decision maker in selection of precise weights, estimation of the inter relationships among the responses and selection of optimal process parameters.

Off-Line Feedrate Optimization Based on Simulation of Cutting Forces

2009 ◽  
Vol 407-408 ◽  
pp. 408-411
Author(s):  
Chen Zhang
Keyword(s):  
Cutting Force ◽  
Optimization Algorithm ◽  
Cutting Forces ◽  
Machining Process ◽  
Machining Time ◽  
Set Constraints ◽  
Machining Quality ◽  
Feedrate Optimization ◽  
Nc Program ◽  
Selection Of

The strategies of selection of feedrate are studied in the ball-end machining process. The optimization algorithm utilizes the objective requirements of a line of NC program to set constraints relation between cutting force and feedrate and optimizes feedrate by controlling the variety ranges of the instantaneous cutting force specified in the cutting forces simulation. Off-line feedrate optimization software for complex sculptured is developed. For a line of NC program, the developed software calculates instantaneous cutting force and an optimization algorithm is used to acquire desired feedrate. The machining experimental results show that the proposed algorithms are satisfying in reduction of machining time and improvement of machining quality.

MCDM Model for Selection of Optimum Machining Process

2013 ◽  
Vol 773-774 ◽  
pp. 348-354 ◽  
Author(s):  
Sriram Srinivasan ◽  
Lakshmikanthan Srivatsan ◽  
Rajaram Sathyanarayan ◽  
B. Vijaya Ramnath
Keyword(s):  
Automobile Industry ◽  
Material Removal ◽  
Removal Rate ◽  
Electrochemical Machining ◽  
Machining Process ◽  
Machining Processes ◽  
Electric Discharge Machining ◽  
Analytical Hierarchical Process ◽  
Laser Beam Machining ◽  
Selection Of

The work of manufacturing engineers is to utilize the minimum amount of energy or resources in bringing out a product without compromising on quality. Hence, to achieve this, the engineers must figure out the optimum or the best possible method to fabricate a product. This paper uses a multi criteria decision making (MCDM) model namely Analytical Hierarchical Process (AHP) to determine the best possible machining process to achieve the optimum results for an engraving operation on gear face in an automobile industry which uses five nontraditional machining processes viz; Laser Beam Machining (LBM), Ultrasonic Machining (USM), Electric Discharge Machining (EDM), Electrochemical Machining (ECM) and Electron Beam Machining (EBM). The five criteria considered in this paper are Material Removal Rate (MRR), Surface Finish, Depth Damage, Tolerance and Toxicity. The AHP result shows that ECM is the most suitable machining process as compared to others.

Study on the Shaping Law of Precision Numerical Controlled Electrochemical Contour Evolution Machining

2008 ◽  
Vol 375-376 ◽  
pp. 72-76 ◽  
Author(s):  
Min Kang ◽  
Jia Wen Xu
Keyword(s):  
Differential Equations ◽  
Process Parameters ◽  
Electrochemical Machining ◽  
Machining Process ◽  
Machining Accuracy ◽  
Planar Surface ◽  
Important Development ◽  
Contour Evolution ◽  
Change Trend ◽  
Side Gap

Numerical Controlled Electrochemical Contour Evolution Machining (NC-ECCEM) is one of the most important development in Electrochemical Machining (ECM). In order to improve the machining accuracy of NC-ECCEM technology, the research works on precision NC-ECCEM technology are needed, and especially the study on its shaping law is significant for improving the machining accuracy of workpiece profile. In this paper, the shaping law of machining the planar surface by use of a kind of inner-spraying cathode with rectangle section was studied. First, the basic differential equations of shaping law in the case of cathode movement were established. Then, considering the structure of the cathode, the methods for calculating the side gap in machining the planar surface was given. Finally, the experiments of machining the planar surface were carried out. Experiments show that the calculated side gaps are bigger than the actual values, but the change trend of calculated side gaps with machining process parameters is coincident with the actual side gap change trend.

Surface roughness study of polyamide in nano-metric polishing using low-frequency acoustic energy

2021 ◽  
pp. 095440542110573
Author(s):  
Sajjad Beigmoradi ◽  
Mehrdad Vahdati
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Electrochemical Machining ◽  
Low Frequency ◽  
Acoustic Energy ◽  
Machining Process ◽  
Surface Topology ◽  
Vibration Source ◽  
Before And After ◽  
Process Factors

Polymers have gained the attention of manufacturers due to their significant advantages such as low density, high corrosion resistance, and high humidity resistance. Producing high-precision polymeric components is one the most challenging issues especially in fabricating complex or micro-scale systems. Some of the machining techniques such as electro discharge machining (EDM) and electrochemical machining (ECM) cannot be employed for machining the non-conductive parts. Using abrasive particles is one of the best options for machining these types of materials. In this work, the capability of the acoustic energy for machining polyamide (PA) workpieces is studied. To this end, an experimental setup is installed and design of experiment (DoE) algorithm is employed to survey the effect of process parameters on surface roughness. Three parameters at three levels are considered as the effective factors of the process and the sensitivity of the surface roughness on the process factors is investigated. In the next step, a hybrid finite element/boundary element approach was used to discuss the relation of process parameters to the vibrational characteristics of the container, then the mechanism of the process was investigated employing the discrete element method. Finally, the surface topology of the optimal workpiece before and after the process was presented and compared. It was observed that acoustic energy can be considered as a vibration source of the container’s floor to provide kinetic energy for machining PA parts on the nano-metric scale. Moreover, it was found that the initial roughness of the workpiece and the chosen parameters play a crucial role in the machining process. Experimental results show that in this technique by selecting appropriate process factors the surface roughness can be reduced up to 50%.

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