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.

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.

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.

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.

Multi-Objective Optimization of Die-Sinking EDM Process on AISI P-20 Tool Steel Using Cuckoo Search and Genetic Algorithm

2017 ◽  
pp. 111-129
Author(s):  
Goutam Kumar Bose ◽  
Pritam Pain ◽  
Sayak Mukhopadhyay
Keyword(s):  
Genetic Algorithm ◽  
Tool Steel ◽  
Process Parameters ◽  
Electrical Discharge Machining ◽  
Search Algorithm ◽  
Removal Rate ◽  
Research Work ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Machining Processes

Electrical Discharge Machining (EDM) is nontraditional machining processes applied for precise machining and developing intricate geometries on work materials which are difficult to machine by conventional process. The present research work emphases on the die sinking EDM of AISI P20 tool steel, to study the effect of machining parameters such as pulse on time (POT), pulse off time (POF), discharge current (GI) and spark gap (SG) on performance response like Material removal rate (MRR), Surface Roughness (Ra) and Overcut (OC) using square-shaped Cu tool with Lateral flushing. The experimentation is performed using L27 orthogonal array and significant process parameters are ascertained using Regression analysis. The influence of the important process parameters on individual responses are detected using Cuckoo search algorithm. The present chapter is aimed at multi-response optimization i.e. higher MRR, lower Ra and minimum OC, which is conceded out using Genetic Algorithm.

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.

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.

scholarly journals Optimization of Roundness Error in Deep Hole Drilling using Cuckoo Search Algorithm

2019 ◽  
Vol 18 (3) ◽  
pp. 44-48
Author(s):  
Azizah Mohamad ◽  
Azlan Mohd Zain ◽  
Razana Alwee ◽  
Noordin Mohd Yusof ◽  
Farhad Najarian
Keyword(s):  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Machining Process ◽  
Hole Drilling ◽  
Machining Parameters ◽  
Deep Hole ◽  
Roundness Error ◽  
Deep Hole Drilling ◽  
Minimum Value

In the manufacturing industry, machining is a part of all manufacture in almost all metal products. Machining of holes is one of the most common processes in the manufacturing industries. Deep hole drilling,  DHD is classified as a complex machining process .This study presents an optimization of machining parameters in DHD using Cuckoo Search algorithm, CS comprising feed rate (f), spindle speed (s), depth of hole (d) and Minimum Quantity Lubrication MQL, (m). The machining performance measured is roundness error, Re. The real experimentation was designed based on Design of Experiment, DoE which is two levels full factorial with an added centre point. The experimental results were used to develop the mathematical model using regression analysis that used in the optimization process. Analysis of variance (ANOVA) and Fisher‘s statistical test (F-test) are used to check the significant of the model developed.  According to the results obtained by experimental the minimum value of Re  is 0.0222µm and by CS is 0.0198µm. For the conclusion, it was found that CS is capable of giving the minimum value of Re as it outperformed the result from the experimental.

Enhanced packet reordering procedure to improve TCP communication

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sai Prasanthi Kasimsetti ◽  
Asdaque Hussain
Keyword(s):  
Wireless Network ◽  
Search Algorithm ◽  
Research Work ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Support Vector ◽  
Linear Network ◽  
Content Type ◽  
Packet Reordering ◽  
Linear Network Coding

Purpose The research work is attained by Spurious Transmission–based Enhanced Packet Reordering Method (ST-EPRM). The packet reordering necessity is evaded by presenting random linear network coding process on wireless network physical layer which function on basis of sequence numbers. The spurious retransmission happening over wireless network is obtained by presenting monitoring concept for reducing number of spurious retransmissions because it might need more than three DUPACKs for triggering fast retransmit. This monitoring node performs as centralized node as well variation amid buffer length and number of packets being sent can be predicted. This information helps in differentiating spurious retransmission from the packet loss. Design/methodology/approach Based on transmission detection, action is accomplished whether to retransmit or evade transmission. Monitoring node selection is achieved by presenting improved cuckoo search algorithm. The modified support vector machine algorithm is greatly used for variation-based spurious transmission. Findings The research work which is attained by ST-EPRM. The packet reordering necessity is evaded by presenting random linear network coding process on wireless network physical layer which function on basis of sequence numbers. The spurious retransmission happening over wireless network is obtained by presenting monitoring concept for reducing number of spurious retransmissions because it might need more than three DUPACKs for triggering fast retransmit. This monitoring node performs as centralized node as well variation amid buffer length and number of packets being sent can be predicted. This information helps in differentiating spurious retransmission from the packet loss. Originality/value Based on transmission detection, action is accomplished whether to retransmit or evade transmission. Monitoring node selection is achieved by presenting improved cuckoo search algorithm. The modified support vector machine algorithm is greatly used for variation-based spurious transmission.

Sign in / Sign up

Export Citation Format

Share Document