Multi-Objective Optimization of ECG Process Applying Soft Computing Techniques

2019 ◽  
pp. 68-98
Author(s):  
Pritam Pain ◽  
Goutam Kumar Bose
Keyword(s):  
Soft Computing ◽  
Removal Rate ◽  
Research Work ◽  
Lower Surface ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Soft Computing Techniques ◽  
Response Optimization ◽  
Grey Relational ◽  
Electrochemical Grinding

The present research work focuses on the selection of significant machining parameters depending on the nature-inspired algorithm while machining alumina-aluminum interpenetrating phase composites during electrochemical grinding. Control parameters like electrolyte concentration (C), voltage (V), depth of cut (D) and electrolyte flow rate (F) have been considered for experimentation. The response data are initially trained and tested by using Artificial Neural Network. The contradictory responses like higher material removal rate (MRR), lower surface roughness (Ra), lower overcut (OC) and lower cutting force (Fc) are ensured individually by employing Firefly Algorithm. A multi-response optimization for all the responses is done initially by using the Genetic algorithm. Finally, in order to obtain a single set of parametric combination for all the output simultaneously fuzzy based Grey Relational Analysis technique is adopted. These natures driven soft computing techniques corroborates well during the parametric optimization of the electrochemical grinding process.

Optimization Through Nature-Inspired Soft-Computing and Algorithm on ECG Process

2017 ◽  
pp. 489-519 ◽  
Author(s):  
Goutam Kumar Bose ◽  
Pritam Pain
Keyword(s):  
Soft Computing ◽  
Search Algorithm ◽  
Removal Rate ◽  
Research Work ◽  
Cuckoo Search ◽  
Lower Surface ◽  
Cuckoo Search Algorithm ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Response Optimization

In the present research work selection of significant machining parameters depending on nature-inspired algorithm is prepared, during machining alumina-aluminum interpenetrating phase composites through electrochemical grinding process. Here during experimentation control parameters like electrolyte concentration (C), voltage (V), depth of cut (D) and electrolyte flow rate (F) are considered. The response data are initially trained and tested applying Artificial Neural Network. The paradoxical responses like higher material removal rate (MRR), lower surface roughness (Ra), lower overcut (OC) and lower cutting force (Fc) are accomplished individually by employing Cuckoo Search Algorithm. A multi response optimization for all the response parameters is compiled primarily by using Genetic algorithm. Finally, in order to achieve a single set of parametric combination for all the outputs simultaneously fuzzy based Grey Relational Analysis technique is adopted. These nature-driven soft computing techniques corroborates well during the parametric optimization of ECG process.

Surface Response Methodology Approach for Multi-Objective Optimization During Electrochemical Grinding of Al2O3/Al Interpenetrating Phase Composite

2017 ◽  
pp. 162-192
Author(s):  
Goutam Kumar Bose ◽  
Pritam Pain
Keyword(s):  
Removal Rate ◽  
Research Work ◽  
Lower Surface ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Multi Objective ◽  
Soft Computing Techniques ◽  
Contour Plots ◽  
Electrochemical Grinding ◽  
Single Objective

Now a day the advances in the material science lead to the development of advanced engineering materials like super alloys. The current research work focus on the selection of significant machining parameters initially depending on single objective and then multi objective responses, while machining alumina-aluminum interpenetrating phase composites during electrochemical grinding. Control parameters such electrolyte concentration (C), voltage (V), depth of cut (D) and electrolyte flow rate (F) have been considered for experimentation. Initially single objective optimal parametric setting is generated from Taguchi Methodology and Regression analysis. Further it is optimize using Response Surface Methodology. The contradictory responses like higher material removal rate (MRR), lower surface roughness (Ra), lower overcut (OC) and lower cutting force (Fc) are ensured by using Overlaid contour plots and Desirability functions. These soft computing techniques corroborates well during the parametric optimization of electrochemical grinding process.

Optimization Through Nature-Inspired Soft-Computing and Algorithm on ECG Process

2020 ◽  
pp. 784-813
Author(s):  
Goutam Kumar Bose ◽  
Pritam Pain
Keyword(s):  
Soft Computing ◽  
Search Algorithm ◽  
Removal Rate ◽  
Research Work ◽  
Cuckoo Search ◽  
Lower Surface ◽  
Cuckoo Search Algorithm ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Response Optimization

In the present research work selection of significant machining parameters depending on nature-inspired algorithm is prepared, during machining alumina-aluminum interpenetrating phase composites through electrochemical grinding process. Here during experimentation control parameters like electrolyte concentration (C), voltage (V), depth of cut (D) and electrolyte flow rate (F) are considered. The response data are initially trained and tested applying Artificial Neural Network. The paradoxical responses like higher material removal rate (MRR), lower surface roughness (Ra), lower overcut (OC) and lower cutting force (Fc) are accomplished individually by employing Cuckoo Search Algorithm. A multi response optimization for all the response parameters is compiled primarily by using Genetic algorithm. Finally, in order to achieve a single set of parametric combination for all the outputs simultaneously fuzzy based Grey Relational Analysis technique is adopted. These nature-driven soft computing techniques corroborates well during the parametric optimization of ECG process.

Selecting Significant Process Parameters of ECG Process Using Fuzzy-MCDM Technique

2015 ◽  
Vol 2 (1) ◽  
pp. 38-53 ◽  
Author(s):  
Goutam Kumar Bose
Keyword(s):  
Surface Roughness ◽  
Removal Rate ◽  
Multiple Criteria Decision Making ◽  
Lower Surface ◽  
Substantial Improvement ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Machining Performance ◽  
Grey Relational Grade ◽  
Grey Relational

The present paper highlights selection of significant machining parameters during Electrochemical grinding while machining alumina-aluminum interpenetrating phase composites by MCDM techniques. The conflicting responses like higher material removal rate, lower surface roughness, lower overcut and lower cutting force are ensured simultaneously by a single parametric combination. Control parameters like electrolyte concentration, voltage, depth of cut and electrolyte flow rate have been considered for experimentation. VIKOR is one of the multiple criteria decision making (MCDM) models to determine the reference ranking from a set of alternatives in the presence of conflicting criteria. Finally Grey Relational Analysis is performed to optimize multiple performances in which different levels combinations of the factors are ranked based on grey relational grade. Surface roughness is given more importance than other responses, using Fuzzy Set Theory considering basic objective of the process. It is observed that substantial improvement in machining performance takes place following this technique. The study highlights the effects of different process variables on multiple performances for complex process like ECG.

scholarly journals Multi-Response Optimization of Face Milling Performance Considering Tool Path Strategies in Machining of Al-2024

Materials ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 1013 ◽  
Author(s):  
Raneen Ali ◽  
Mozammel Mia ◽  
Aqib Khan ◽  
Wenliang Chen ◽  
Munish Gupta ◽  
...  
Keyword(s):  
Tool Path ◽  
Removal Rate ◽  
Cutting Speed ◽  
Milling Process ◽  
Face Milling ◽  
Depth Of Cut ◽  
Cutter Path ◽  
Response Optimization ◽  
Grey Relational ◽  
Al 2024

It is hypothesized that the orientation of tool maneuvering in the milling process defines the quality of machining. In that respect, here, the influence of different path strategies of the tool in face milling is investigated, and subsequently, the best strategy is identified following systematic optimization. The surface roughness, material removal rate and cutting time are considered as key responses, whereas the cutting speed, feed rate and depth of cut were considered as inputs (quantitative factors) beside the tool path strategy (qualitative factor) for the material Al 2024 with a torus end mill. The experimental plan, i.e., 27 runs were determined by using the Taguchi design approach. In addition, the analysis of variance is conducted to statistically identify the effects of parameters. The optimal values of process parameters have been evaluated based on Taguchi-grey relational analysis, and the reliability of this analysis has been verified with the confirmation test. It was found that the tool path strategy has a significant influence on the end outcomes of face milling. As such, the surface topography respective to different cutter path strategies and the optimal cutting strategy is discussed in detail.

Modelling and Optimization of Machining parameters for Turning Automotive Shafts using RSM and Grey Relational Analysis

2020 ◽  
Vol 12 (4) ◽  
Author(s):  
S. Dinesh ◽  
K. Rajaguru ◽  
K. Saravanan ◽  
R. Yokeswaran ◽  
V. Vijayan
Keyword(s):  
Surface Roughness ◽  
Grey Relational Analysis ◽  
Removal Rate ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Relational Analysis ◽  
Input Parameters ◽  
Grey Relational ◽  
Central Composite ◽  
Modelling And Optimization

Automotive shafts require maximum strength with regard to axial, bending and torsional loading to transmit power to various parts of a vehicle. Hence, it is very critical to analyse the manufacturing process and its governing parameters to exercise control over the surface properties of the shaft as it needs to be precisely manufactured in terms of dimensions and the surface roughness. The effect of three input parameters over two responses are considered as two major criteria's for production of shaft. The input parameters are speed, feed and depth of cut whereas the responses are material removal rate and surface roughness. Central Composite design was used and experimental results were analysed with Response Surface Methodology. ANOVA analysis was carried out to identify the most contributing parameter for MRR and SR. Grey Relational Analysis was adopted to identify the most feasible combination of machining parameters for turning process. The optimized parameter is identified as speed of 1000 rpm, 0.15 mm of feed and 0.35 mm of depth of cut using Grey Relational Analysis.

Surface Roughness Prediction in End Milling of Machinable Glass Ceramic and Optimization by Response Surface Methodology

2011 ◽  
Vol 189-193 ◽  
pp. 1376-1381
Author(s):  
Moola Mohan Reddy ◽  
Alexander Gorin ◽  
Khaled A. Abou El Hossein
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Glass Ceramic ◽  
End Milling ◽  
Removal Rate ◽  
Cutting Speed ◽  
Lower Surface ◽  
Depth Of Cut ◽  
Machining Parameters

This paper presents the prediction of a statistically analyzed model for the surface roughness,R_a of end-milled Machinable glass ceramic (MGC). Response Surface Methodology (RSM) is used to construct the models based on 3-factorial Box-Behnken Design (BBD). It is found that cutting speed is the most significant factor contributing to the surface roughness value followed by the depth of cut and feed rate. The surface roughness value decreases for higher cutting speed along with lower feed and depth of cut. Additionally, the process optimization has also been done in terms of material removal rate (MRR) to the model’s response. Ideal combinations of machining parameters are then suggested for common goal to achieve lower surface roughness value and higher MRR.

Optimisation of Machining Parameters for High Feed End Milling on Inconel 718 Super Alloy

2014 ◽  
Vol 592-594 ◽  
pp. 584-590 ◽  
Author(s):  
Vinay Varghese ◽  
K. Annamalai ◽  
K. Santhosh Kumar
Keyword(s):  
Inconel 718 ◽  
End Milling ◽  
Removal Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Milling Operation ◽  
High Feed ◽  
Grey Relational ◽  
Super Alloy

This study investigates about machining practices used worldwide for machining of Inconel 718 super alloy. The effect of machining parameters like cutting speed, feed and depth of cut on machining responses like surface roughness and material removal rate when end milling Inconel 718 is studied using nine trials carried out based on L9 orthogonal array. A Taguchi based grey relational analysis was used for optimisation of machining parameters for high feed end milling operation on Inconel 718. An analysis of variance (ANOVA) was used to find the most significant factor. Validation of results through confirmation tests was performed and experimental results show that surface quality and productivity can be improved efficiently with this approach.

scholarly journals Optimization of Turning Parameter of Composite Materials Using Response Surface Method in Minitab

2021 ◽  
Author(s):  
S. S Kulkarni ◽  
Sarika Sharma
Keyword(s):  
Surface Roughness ◽  
Composite Material ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Research Work ◽  
Machining Process ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Rsm Optimization

This paper represents the optimization method utilized in machining process for figuring out the most advantageous manner design. Typically, the technique layout parameters in machining procedures are noticeably few turning parameters inclusive of reducing velocity, feed and depth. The optimization of speed, feed depth of cut is very tough because of several other elements associated with processing situations and form complexities like surface Roughness, material removal rate (MRR) that are based Parameters. On this task a new fabric glass fibre composite is introduced through which could lessen costing of manufacturing and time and additionally it will boom the technique of productiveness. Composite substances have strength, stiffness, light weight, which gives the large scope to engineering and technology. The proposed research work targets to analyze turning parameters of composite material. The machining parameters are very important in manufacturing industries. The present research work is optimized surface roughness of composite material specifically in turning procedure with the aid of changing parameter including intensity of reduce, slicing velocity and feed price and additionally expect the mechanical houses of composite material. The RSM optimization is important because it evaluates the effects of multiple factors and their interactions on one or more responsive variables. It is observed that the material removal rate increases and surface roughness decreases as per the increase of Spindle speed and feed rate.

The Use of the Taguchi-Grey Based to Optimize High Speed End Milling with Multiple Performance Characteristics

2006 ◽  
Vol 505-507 ◽  
pp. 835-840 ◽  
Author(s):  
Shen Jenn Hwang ◽  
Yunn Lin Hwang ◽  
B.Y. Lee
Keyword(s):  
High Speed ◽  
End Milling ◽  
Removal Rate ◽  
Cutting Speed ◽  
Performance Characteristics ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Machining Performance ◽  
Grey Relational Grade ◽  
Grey Relational

This paper presents a new approach for the optimization of the high speed machining (HSM) process with multiple performance characteristics based on the orthogonal array with the grey relational analysis has been studied. Optimal machining parameters can then be determined by the grey relational grade as the performance index. In this study, the machining parameters such as cutting speed, feed rate and axial depth of cut are optimized under the multiple performance characteristics including, tool life, surface roughness, and material removal rate(MMR). As shown experimental results, machining performance in the HSM process can be improved effectively through this approach.

Sign in / Sign up

Export Citation Format

Share Document