N. Muthukrishnan

1.4k total citations
34 papers, 1.1k citations indexed

About

N. Muthukrishnan is a scholar working on Mechanical Engineering, Electrical and Electronic Engineering and Biomedical Engineering. According to data from OpenAlex, N. Muthukrishnan has authored 34 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Mechanical Engineering, 29 papers in Electrical and Electronic Engineering and 23 papers in Biomedical Engineering. Recurrent topics in N. Muthukrishnan's work include Advanced machining processes and optimization (31 papers), Advanced Machining and Optimization Techniques (29 papers) and Advanced Surface Polishing Techniques (23 papers). N. Muthukrishnan is often cited by papers focused on Advanced machining processes and optimization (31 papers), Advanced Machining and Optimization Techniques (29 papers) and Advanced Surface Polishing Techniques (23 papers). N. Muthukrishnan collaborates with scholars based in India, Nigeria and Portugal. N. Muthukrishnan's co-authors include M. Naresh Babu, J. Paulo Davim, K. Prahlada Rao, M. Murugan, R. Ramanujam, K. Palanikumar, M. Santhanakumar, Thandavamoorthy Raja, K. Ganesan and Dinesh Babu Munuswamy and has published in prestigious journals such as Journal of Materials Processing Technology, The International Journal of Advanced Manufacturing Technology and Measurement.

In The Last Decade

N. Muthukrishnan

33 papers receiving 1.0k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
N. Muthukrishnan India 18 945 605 400 130 89 34 1.1k
Raviraj Shetty India 15 885 0.9× 298 0.5× 213 0.5× 150 1.2× 42 0.5× 88 1.0k
P.K. Brahmankar India 17 1.1k 1.2× 701 1.2× 610 1.5× 147 1.1× 54 0.6× 39 1.3k
Diptikanta Das India 16 779 0.8× 306 0.5× 191 0.5× 31 0.2× 71 0.8× 86 904
H. S. Shan India 21 1.1k 1.2× 717 1.2× 840 2.1× 121 0.9× 18 0.2× 49 1.3k
Sabino Ayvar-Soberanis United Kingdom 18 1.0k 1.1× 637 1.1× 617 1.5× 34 0.3× 44 0.5× 35 1.2k
P. Marimuthu India 14 714 0.8× 216 0.4× 129 0.3× 42 0.3× 22 0.2× 46 837
Meltem Altın Karataş Türkiye 11 522 0.6× 249 0.4× 241 0.6× 99 0.8× 120 1.3× 17 782
Sezer Morkavuk Türkiye 18 854 0.9× 472 0.8× 388 1.0× 19 0.1× 80 0.9× 25 988
Hassan El-Hofy Egypt 16 657 0.7× 373 0.6× 438 1.1× 116 0.9× 16 0.2× 60 898
Rendi Kurniawan South Korea 19 907 1.0× 557 0.9× 622 1.6× 37 0.3× 35 0.4× 76 1.1k

Countries citing papers authored by N. Muthukrishnan

Since Specialization
Citations

This map shows the geographic impact of N. Muthukrishnan's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by N. Muthukrishnan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites N. Muthukrishnan more than expected).

Fields of papers citing papers by N. Muthukrishnan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by N. Muthukrishnan. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by N. Muthukrishnan. The network helps show where N. Muthukrishnan may publish in the future.

Co-authorship network of co-authors of N. Muthukrishnan

This figure shows the co-authorship network connecting the top 25 collaborators of N. Muthukrishnan. A scholar is included among the top collaborators of N. Muthukrishnan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with N. Muthukrishnan. N. Muthukrishnan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Babu, M. Naresh, et al.. (2020). Performance of silver nanofluids with minimum quantity lubrication in turning on titanium: a phase to green manufacturing. Journal of the Brazilian Society of Mechanical Sciences and Engineering. 42(4). 13 indexed citations
2.
Muthukrishnan, N., et al.. (2018). Experimental process to evaluate the minimum quantity lubrication technique using copper nanofluids in turning process. International Journal of Machining and Machinability of Materials. 20(6). 497–497. 3 indexed citations
3.
Babu, M. Naresh & N. Muthukrishnan. (2018). Experimental analysis in drilling of AA 5052 using copper nanofluids under minimum quantity lubrication. Australian Journal of Mechanical Engineering. 18(sup1). S15–S24. 16 indexed citations
4.
Santhanakumar, M., M. Naresh Babu, & N. Muthukrishnan. (2018). Copper nanofluids under minimum quantity lubrication during drilling of AISI 4140 steel. Australian Journal of Mechanical Engineering. 18(sup1). S151–S164. 21 indexed citations
5.
Babu, M. Naresh, et al.. (2018). Experimental process to evaluate the minimum quantity lubrication technique using copper nanofluids in turning process. International Journal of Machining and Machinability of Materials. 20(6). 497–497. 2 indexed citations
6.
Babu, M. Naresh, G. Manimaran, & N. Muthukrishnan. (2017). Experimental estimation of minimum quantity lubrication in turning on AISI 410 stainless steel. International Journal of Machining and Machinability of Materials. 19(6). 522–522. 5 indexed citations
7.
Babu, M. Naresh, et al.. (2015). Analysis on surface roughness in abrasive water jet machining of aluminium. Progress in Industrial Ecology An International Journal. 9(2). 200–200. 7 indexed citations
8.
Muthukrishnan, N., et al.. (2013). Optimization of Machinability of Polyester/Modified Jute Fabric Composite Using Grey Relational Analysis (GRA). Procedia Engineering. 64. 1003–1012. 45 indexed citations
9.
Muthukrishnan, N., et al.. (2013). Optimization of Machining Parameters on Turning of Hybrid Metal Matrix Composite. Applied Mechanics and Materials. 315. 113–116. 1 indexed citations
10.
Muthukrishnan, N., et al.. (2012). Fabrication and turning of Al/SiC/B4C hybrid metal matrix composites optimization using desirability analysis. Journal of the Chinese Institute of Industrial Engineers. 29(8). 515–525. 19 indexed citations
11.
Muthukrishnan, N., et al.. (2012). Investigation on the Characteristics of Surface Quality on Machining of Hybrid Metal Matrix Composite (Al-SiC-B4C). Procedia Engineering. 38. 2617–2624. 22 indexed citations
12.
Muthukrishnan, N. & J. Paulo Davim. (2011). An investigation of the effect of work piece reinforcing percentage on the machinability of Al-SiC metal matrix composites. 3(1). 15–24. 27 indexed citations
13.
Muthukrishnan, N., et al.. (2011). Performance Evaluation of PCD 1300 and 1500 Grade Inserts on Turning A356 Alloy with 20% Reinforcement of SiC Particles. Applied Mechanics and Materials. 110-116. 1855–1861. 5 indexed citations
14.
Ramanujam, R., et al.. (2011). OPTIMIZATION OF MACHINING PARAMETERS FOR TURNING AL-SIC (10P) MMC USING TAGUCHI GREY RELATIONAL ANALYSIS. 18(11). 1 indexed citations
15.
16.
Muthukrishnan, N. & J. Paulo Davim. (2008). Optimization of machining parameters of Al/SiC-MMC with ANOVA and ANN analysis. Journal of Materials Processing Technology. 209(1). 225–232. 221 indexed citations
17.
18.
Muthukrishnan, N., M. Murugan, & K. Prahlada Rao. (2007). An investigation on the machinability of Al-SiC metal matrix composites using pcd inserts. The International Journal of Advanced Manufacturing Technology. 38(5-6). 447–454. 71 indexed citations
19.
Muthukrishnan, N., M. Murugan, & K. Prahlada Rao. (2007). Machinability issues in turning of Al-SiC (10p) metal matrix composites. The International Journal of Advanced Manufacturing Technology. 39(3-4). 211–218. 128 indexed citations
20.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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