T. Mohanraj

2.1k total citations · 1 hit paper
71 papers, 1.5k citations indexed

About

T. Mohanraj is a scholar working on Mechanical Engineering, Electrical and Electronic Engineering and Biomedical Engineering. According to data from OpenAlex, T. Mohanraj has authored 71 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Mechanical Engineering, 39 papers in Electrical and Electronic Engineering and 27 papers in Biomedical Engineering. Recurrent topics in T. Mohanraj's work include Advanced machining processes and optimization (36 papers), Advanced Machining and Optimization Techniques (32 papers) and Advanced Surface Polishing Techniques (20 papers). T. Mohanraj is often cited by papers focused on Advanced machining processes and optimization (36 papers), Advanced Machining and Optimization Techniques (32 papers) and Advanced Surface Polishing Techniques (20 papers). T. Mohanraj collaborates with scholars based in India, Australia and Türkiye. T. Mohanraj's co-authors include S. Shankar, Rajasekar Rathanasamy, Alokesh Pramanik, N.R. Sakthivel, P. Mohankumar, J. Ajayan, G. Sakthivel, R. Parameshwaran, A. Tamilvanan and R. Jegadeeshwaran and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Energy.

In The Last Decade

T. Mohanraj

66 papers receiving 1.4k citations

Hit Papers

Tool condition monitoring techniques in milling process —... 2019 2026 2021 2023 2019 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
T. Mohanraj India 20 1.0k 654 438 328 179 71 1.5k
K. Venkata Rao India 21 988 1.0× 594 0.9× 394 0.9× 249 0.8× 81 0.5× 89 1.4k
Xiaojian Zhang China 18 1.3k 1.3× 850 1.3× 1.4k 3.1× 286 0.9× 176 1.0× 90 2.0k
Pandu R. Vundavilli India 22 1.2k 1.2× 252 0.4× 375 0.9× 71 0.2× 455 2.5× 107 1.8k
Zhiqiang Liu China 19 852 0.9× 1.0k 1.5× 403 0.9× 55 0.2× 283 1.6× 91 1.6k
Ko-Ta Chiang Taiwan 22 1.3k 1.3× 793 1.2× 647 1.5× 254 0.8× 107 0.6× 39 1.6k
Ramesh Singh India 26 1.6k 1.6× 827 1.3× 910 2.1× 101 0.3× 282 1.6× 112 2.1k
M. Ramesh India 23 402 0.4× 724 1.1× 230 0.5× 76 0.2× 471 2.6× 63 1.5k
P. S. Sreejith India 15 1.2k 1.2× 737 1.1× 694 1.6× 129 0.4× 173 1.0× 34 1.4k
Guangming Zheng China 19 868 0.9× 393 0.6× 394 0.9× 129 0.4× 240 1.3× 105 1.1k
Ying Guo China 25 855 0.9× 694 1.1× 437 1.0× 56 0.2× 123 0.7× 127 2.0k

Countries citing papers authored by T. Mohanraj

Since Specialization
Citations

This map shows the geographic impact of T. Mohanraj'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 T. Mohanraj with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. Mohanraj more than expected).

Fields of papers citing papers by T. Mohanraj

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by T. Mohanraj. 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 T. Mohanraj. The network helps show where T. Mohanraj may publish in the future.

Co-authorship network of co-authors of T. Mohanraj

This figure shows the co-authorship network connecting the top 25 collaborators of T. Mohanraj. A scholar is included among the top collaborators of T. Mohanraj 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 T. Mohanraj. T. Mohanraj 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.
Mohanraj, T., et al.. (2025). Optimization of tail beam configurations in pressure vessel skirts for enhanced structural integrity. Results in Engineering. 27. 106087–106087.
2.
Prabhu, B.S., et al.. (2025). Cleaner production of performance-enhanced hybrid composites using agro-industrial wastes: A sustainable waste management strategy. Journal of Environmental Management. 381. 125116–125116.
3.
Thangavelu, Praveenkumar, Dinesh Kumar Madheswaran, Edwin Geo Varuvel, et al.. (2025). Battery fault diagnosis methods for electric vehicle lithium-ion batteries: Correlating codes and battery management system. Process Safety and Environmental Protection. 196. 106919–106919. 10 indexed citations
4.
Tamilvanan, A., T. Mohanraj, Rajendran Prabakaran, et al.. (2025). Enhancing biodiesel yield from high free fatty acid paradise seed oil via two-stage acid-base esterification: Implications for CI engine application. Case Studies in Thermal Engineering. 71. 106092–106092. 1 indexed citations
5.
Madheswaran, Dinesh Kumar, T. Mohanraj, Ram Krishna, G. Suresh, & Edwin Geo Varuvel. (2024). Enhanced oxidation resistance and electrochemical performance of PEMFC gas diffusion layer through [EMIM][TFSI] ionic liquid coating. Renewable Energy. 235. 121303–121303. 3 indexed citations
6.
Sakthivel, G., et al.. (2024). Machine-Learning- and Internet-of-Things-Driven Techniques for Monitoring Tool Wear in Machining Process: A Comprehensive Review. Journal of Sensor and Actuator Networks. 13(5). 53–53. 18 indexed citations
7.
Mohanraj, T., et al.. (2024). Tool Condition Monitoring in the Milling Process Using Deep Learning and Reinforcement Learning. Journal of Sensor and Actuator Networks. 13(4). 42–42. 17 indexed citations
8.
Suresh, G., et al.. (2024). A Tribological investigation of fly ash particulate‐loaded E‐glass fiber reinforced interpenetrating polymer network composites. Polymer Composites. 45(14). 13348–13358. 13 indexed citations
9.
Mohanraj, T., et al.. (2024). Review of advances in tool condition monitoring techniques in the milling process. Measurement Science and Technology. 35(9). 92002–92002. 19 indexed citations
10.
Tamilvanan, A., et al.. (2023). Modeling and Optimization of Electrodeposition Process for Copper Nanoparticle Synthesis Using ANN and Nature-Inspired Algorithms. Journal of Nanomaterials. 2023. 1–10. 5 indexed citations
12.
Mohanraj, T., et al.. (2023). Digital Twin-Driven Tool Condition Monitoring for the Milling Process. Sensors. 23(12). 5431–5431. 27 indexed citations
14.
Mohanraj, T., et al.. (2023). Prediction of Flank Wear during Turning of EN8 Steel with Cutting Force Signals Using a Deep Learning Approach. Mathematical Problems in Engineering. 2023(1). 3 indexed citations
15.
Sambathkumar, M., et al.. (2023). A Systematic Review on the Mechanical, Tribological, and Corrosion Properties of Al 7075 Metal Matrix Composites Fabricated through Stir Casting Process. Advances in Materials Science and Engineering. 2023. 1–17. 46 indexed citations
16.
Parameshwaran, R., et al.. (2022). Optimization of FSP parameters to fabricate AA7075-based surface composites using Taguchi technique and TOPSIS approach. Journal of Adhesion Science and Technology. 37(5). 817–841. 22 indexed citations
17.
Sakthivel, G., T. Mohanraj, M. Senthil Kumar, et al.. (2022). Condition Monitoring of an All-Terrain Vehicle Gear Train Assembly Using Deep Learning Algorithms with Vibration Signals. Applied Sciences. 12(21). 10917–10917. 6 indexed citations
18.
19.
Parameshwaran, R., et al.. (2021). Assessment of erosion rate on AA7075 based surface hybrid composites fabricated through friction stir processing by taguchi optimization approach. Journal of Adhesion Science and Technology. 36(6). 584–605. 41 indexed citations
20.
Shankar, S., T. Mohanraj, & K. Ponappa. (2017). Influence of vegetable based cutting fluids on cutting force and vibration signature during milling of aluminium metal matrix composites. SHILAP Revista de lepidopterología. 17 indexed citations

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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