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eISSN: 2581-9615 || CODEN: WJARAI || Impact Factor 8.2 ||  CrossRef DOI

Research and review articles are invited for publication in March 2026 (Volume 29, Issue 3) Submit manuscript

Optimization of machining parameters for turning process by using grey relational analysis

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  • Optimization of machining parameters for turning process by using grey relational analysis

Nagwa Mejid Ibrahim Elsiti 1, * and Mohamed Handawi Saad Elmunafi 2

1 Department of Industrial and Manufacturing System Engineering, Benghazi University, Benghazi, Libya.
2 Faculty of Mechanical Engineering, University Teknologi Malaysia, UTM Skudai, Johor 81310, Malaysia.
 
Research Article
World Journal of Advanced Research and Reviews, 2023, 17(01), 756-761
Article DOI: 10.30574/wjarr.2023.17.1.0080
DOI url: https://doi.org/10.30574/wjarr.2023.17.1.0080
 
Received on 08 December 2022; revised on 19 January 2023; accepted on 21 January 2023
 
This paper presents an optimization of process parameters of turning operation using multi-response optimization Grey Relational Analysis (GRA) method instead of single response optimization. These parameters were optimized based on a three level two factor factorial design with three center points was used for the experimental design with Grey Relational Analysis. The machining parameters such as cutting speed, feed rate, and depth of cut were chosen for experimentation. The performance characteristics chosen for this study are material removal rate (MRR), tool life, and surface roughness. Experiments were conducted using coated carbide tool (KC5010) as the tool and martensitic stainless steel (AISI 420) as the workpiece. Experimental results have been improved through this approach.
 
GRA; MRR; Tool life; Surface roughness
 
https://wjarr.com/sites/default/files/fulltext_pdf/WJARR-2023-0080.pdf

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Nagwa Mejid Ibrahim Elsiti and Mohamed Handawi Saad Elmunafi. Optimization of machining parameters for turning process by using grey relational analysis. World Journal of Advanced Research and Reviews, 2023, 17(1), 756-761. Article DOI: https://doi.org/10.30574/wjarr.2023.17.1.0080

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