Rashid ali Laghari

Dr. Rashid ali Laghari

college of mechanical and electrical engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, China
orcid
Recognised World’s Top 2% scientists – Stanford/Elsevier

Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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14 July 2021 in Archives of Computational Methods in Engineering
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Journal Article
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Asif Ali LaghariAsif Ali Laghari
Asif Ali Laghari
KWKaishun Wu
Kaishun Wu
Rashid ali LaghariRashid ali Laghari
Rashid ali Laghari
MAMureed Ali
Mureed Ali
Abdullah Ayub KhanAbdullah Ayub Khan
Abdullah Ayub Khan

23 October 2018 in The International Journal of Advanced Manufacturing Technology
Verified
Journal Article
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JLJianguang Li
Jianguang Li
Rashid ali LaghariRashid ali Laghari
Rashid ali Laghari

1 February 2021 in Archives of Computational Methods in Engineering
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Journal Article
Closed access
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Asif Ali LaghariAsif Ali Laghari
Asif Ali Laghari
Awais Khan JumaniAwais Khan Jumani
Awais Khan Jumani
Rashid ali LaghariRashid ali Laghari
Rashid ali Laghari

29 April 2019 in Archives of Computational Methods in Engineering
Verified
Journal Article
Closed access
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Rashid ali LaghariRashid ali Laghari
Rashid ali Laghari
JLJianguang Li
Jianguang Li
Asif Ali LaghariAsif Ali Laghari
Asif Ali Laghari
SWShu-Qi Wang
Shu-Qi Wang

2 December 2021 in The International Journal of Advanced Manufacturing Technology
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Journal Article
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Muhammad JamilMuhammad Jamil
Muhammad Jamil
Ning HeNing He
Ning He
WZWei Zhao
Wei Zhao
Aqib Mashood KhanAqib Mashood Khan
Aqib Mashood Khan
Rashid ali LaghariRashid ali Laghari
Rashid ali Laghari

24 June 2020 in Metals
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Journal Article
Open access
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Rashid ali LaghariRashid ali Laghari
Rashid ali Laghari
JLJianguang Li
Jianguang Li
Mozammel MiaMozammel Mia
Mozammel Mia
Cutting force in the machining process of SiCp/Al particle reinforced metal matrix composite is affected by several factors. Obtaining an effective mathematical model for the cutting force is challenging. In that respect, the second-order model of cutting force has been established by response surface methodology (RSM) in this study, with different cutting parameters, such as cutting speed, feed rate, and depth of cut. The optimized mathematical model has been developed to analyze the effect of actual processing conditions on the generation of cutting force for the turning process of SiCp/Al composite. The results show that the predicted parameters by the RSM are in close agreement with experimental results with minimal error percentage. Quantitative evaluation by using analysis of variance (ANOVA), main effects plot, interactive effect, residual analysis, and optimization of cutting forces using the desirability function was performed. It has been found that the higher depth of cut, followed by feed rate, increases the cutting force. Higher cutting speed shows a positive response by reducing the cutting force. The predicted and experimental results for the model of SiCp/Al components have been compared to the cutting force of SiCp/Al 45 wt%—the error has been found low showing a good agreement.