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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM25701

Analysis of Machining Parameters for Turning of AL-6061 and Optimization

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM25701

Volume:

7 |

9 |

Sep 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

DQM

Dr. Qasim Murtaza

BK

Baibhav Kumar

AV

Anant Vohra

AP

Anshuman Piyush

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Abstract

The paper shows and includes targeted supervision of optimizing machining parameters. Material Removal Rate and surface roughness being integral to machining efficacy of any workpiece , simulation based modeling helps in failure mitigation.The potential of ANN-GA mathematical approach for prediction and optimization of MRR and surface roughness of AL 6061 , a analysis based statistical study has been discussed. The computational model between the desired output and the inputs have been configured using Multiple Regression- Genetic Algorithm and Artificial Neural Network(ANN) methods. The closeness in predicted and optimized data sets were mapped using integrational ANN with GA to interpolate efficacy in optimality.

KEYWORDS

Artificial Neural Network(ANN)k Material Removal Rate(MRR) Genetic algorithm(GA) Surface roughness depth of cut feed rate Regression analysis ANOVA

Cite This Article

Dr. Qasim Murtaza, Baibhav Kumar, Anant Vohra, Anshuman Piyush, "Analysis of Machining Parameters for Turning of AL-6061 and Optimization," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 9, Sep 2023. https://doi.org/10.55041/IJSREM25701

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Publication Date

9/15/2023

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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