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<p class="Author">Application of Artificial Neural Networks and Genetic Algorithm for Optimizing Process Parameters in Pocket Milling of AA7075</p>

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Title Statement <p class="Author">Application of Artificial Neural Networks and Genetic Algorithm for Optimizing Process Parameters in Pocket Milling of AA7075</p>
 
Added Entry - Uncontrolled Name Mellacheruvu, Rajyalakshmi ; Acharya Nagarjuna University, Guntur 522 510, Andhra Pradesh, India PVP Siddhartha Institute of Technology, Vijayawada 520 007, Andhra Pradesh, India
Venkateswara Rao, M ; Department of Mechanical Engineering, Bapatla Engineering College, Bapatla 522 102, Andhra Pradesh, India
 
Uncontrolled Index Term Aluminium, ANN, Multi objective genetic algorithms, RSM, Tool trajectory
 
Summary, etc. <p><em>Received 06 October 2021; revised 23 August 2022; accepted 24 August 2022</em></p> <p>Mould preparation is an important phase in the injection moulding process. The surface roughness of the mould affects the surface finish of the final plastic product. Quality product with a better production rate is required to meet the competition in the present market. To achieve this objective, manufacturers try to select the best combination of parameters. Multi-objective optimization is one such technique to obtain the optimal process parameters that give better quality with a good production rate. The current paper describes the application of Multi-Objective Genetic Algorithms (MOGA) on the Artificial Neural Network (ANN) model for pocket milling on AA7075. Through the application of ANN with MOGA minimum Surface Roughness (SR) is achieved with a better Material Removal Rate (MRR). From the confirmation experiments, it is evident that follow-periphery tool path gives a better surface finish with higher MRR and the percentage error observed is 1.9553 and 1.8282 respectively.</p>
 
Publication, Distribution, Etc. Journal of Scientific & Industrial Research
2022-09-07 19:53:04
 
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http://op.niscair.res.in/index.php/JSIR/article/view/55874
 
Data Source Entry Journal of Scientific & Industrial Research; ##issue.vol## 81, ##issue.no## 09 (2022): Journal of Scientific & Industrial Research
 
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Nonspecific Relationship Entry http://op.niscair.res.in/index.php/JSIR/article/download/55874/465581521
http://op.niscair.res.in/index.php/JSIR/article/download/55874/465581522