Arunkumar Bongale

1.3k total citations
77 papers, 828 citations indexed

About

Arunkumar Bongale is a scholar working on Mechanical Engineering, Materials Chemistry and Electrical and Electronic Engineering. According to data from OpenAlex, Arunkumar Bongale has authored 77 papers receiving a total of 828 indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Mechanical Engineering, 19 papers in Materials Chemistry and 18 papers in Electrical and Electronic Engineering. Recurrent topics in Arunkumar Bongale's work include Advanced machining processes and optimization (20 papers), Advanced Machining and Optimization Techniques (14 papers) and Aluminum Alloys Composites Properties (14 papers). Arunkumar Bongale is often cited by papers focused on Advanced machining processes and optimization (20 papers), Advanced Machining and Optimization Techniques (14 papers) and Aluminum Alloys Composites Properties (14 papers). Arunkumar Bongale collaborates with scholars based in India, Russia and Saudi Arabia. Arunkumar Bongale's co-authors include Satish Kumar, Ketan Kotecha, Shruti Patil, Pooja Kamat, Anupkumar M. Bongale, Nitin Khedkar, Ajith Abraham, Chander Prakash, Ganeshsree Selvachandran and Atef Zaguia and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Access.

In The Last Decade

Arunkumar Bongale

70 papers receiving 790 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Arunkumar Bongale India 17 405 203 196 141 132 77 828
Ján Piteľ Slovakia 17 369 0.9× 217 1.1× 145 0.7× 135 1.0× 67 0.5× 98 971
Shahid Ikramullah Butt Pakistan 16 346 0.9× 250 1.2× 133 0.7× 38 0.3× 66 0.5× 60 863
Connor Jennings United States 6 360 0.9× 265 1.3× 191 1.0× 129 0.9× 32 0.2× 10 684
Ahmed Chebak Morocco 19 352 0.9× 129 0.6× 568 2.9× 299 2.1× 108 0.8× 123 1.3k
Vimal Kumar Pathak India 18 506 1.2× 123 0.6× 200 1.0× 49 0.3× 121 0.9× 92 877
Sasan Sattarpanah Karganroudi Canada 15 301 0.7× 202 1.0× 73 0.4× 118 0.8× 43 0.3× 52 712
Rakesh Kumar Phanden India 13 252 0.6× 307 1.5× 76 0.4× 57 0.4× 68 0.5× 63 715
R. Parameshwaran India 20 555 1.4× 92 0.5× 120 0.6× 77 0.5× 152 1.2× 66 1.0k
Rui He China 17 203 0.5× 116 0.6× 197 1.0× 226 1.6× 61 0.5× 36 851

Countries citing papers authored by Arunkumar Bongale

Since Specialization
Citations

This map shows the geographic impact of Arunkumar Bongale'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 Arunkumar Bongale with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arunkumar Bongale more than expected).

Fields of papers citing papers by Arunkumar Bongale

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Arunkumar Bongale

This figure shows the co-authorship network connecting the top 25 collaborators of Arunkumar Bongale. A scholar is included among the top collaborators of Arunkumar Bongale 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 Arunkumar Bongale. Arunkumar Bongale 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.
Kumar, Satish, et al.. (2024). Application of the Nadaraya-Watson estimator based attention mechanism to the field of predictive maintenance. MethodsX. 12. 102754–102754. 3 indexed citations
2.
Kumar, Satish, et al.. (2024). Enhancement of tool life using magneto-rheological fluid damping and tool wear prediction through deep learning model in milling. Engineering Applications of Artificial Intelligence. 137. 109265–109265. 4 indexed citations
3.
Bongale, Arunkumar, et al.. (2024). Milling Tool Wear Estimation Using Machine Learning with Feature Extraction Approach. 1–7. 2 indexed citations
4.
Kumar, Satish, et al.. (2024). Tool Wear Estimation Using Few-Shot Learning in Deep Neural Network Architectures. 1–6. 1 indexed citations
5.
Sonawane, Chandrakant, et al.. (2024). Advancement in CFD and Responsive AI to Examine Cardiovascular Pulsatile Flow in Arteries: A Review. Computer Modeling in Engineering & Sciences. 141(3). 2021–2064.
6.
Kumar, Satish, et al.. (2024). Robust Tool Wear Prediction using Multi-Sensor Fusion and Time-Domain Features for the Milling Process using Instance-based Domain Adaptation. Knowledge-Based Systems. 288. 111454–111454. 19 indexed citations
7.
8.
Kumar, Satish, et al.. (2023). Remaining Useful-Life Prediction of the Milling Cutting Tool Using Time–Frequency-Based Features and Deep Learning Models. Sensors. 23(12). 5659–5659. 16 indexed citations
9.
Bongale, Arunkumar, et al.. (2023). An intelligent method for supply chain finance selection using supplier segmentation: A payment risk portfolio approach. Cleaner Logistics and Supply Chain. 8. 100115–100115. 6 indexed citations
10.
Bongale, Arunkumar, et al.. (2023). Tribological and Hardness Analyses of Friction-Stir-Processed Composites Using the Taguchi Approach. Materials. 16(1). 420–420. 5 indexed citations
11.
Bongale, Arunkumar, et al.. (2023). Microstructural and sensor data analysis of friction stir processing in fabricating Al6061 surface composites. Engineering Research Express. 5(1). 15065–15065. 1 indexed citations
12.
Mohan, Nanjangud, et al.. (2023). Evaluation of Surface Delamination in Drilled Fiber-Reinforced Polymer Composites Using Digital Image Processing. Journal of The Institution of Engineers (India) Series D. 105(1). 297–304. 2 indexed citations
13.
Bongale, Arunkumar, et al.. (2021). Bibliometric of Feature Selection Using Optimization Techniques in Healthcare using Scopus and Web of Science Databases. Library philosophy and practice. 2021.
14.
Bongale, Anupkumar M., et al.. (2021). Design and Implementation of EOICHD Based Clustered Routing Protocol Variants for Wireless Sensor Networks. Applied System Innovation. 4(2). 25–25. 4 indexed citations
15.
Doreswamy, Deepak, Anupkumar M. Bongale, Arunkumar Bongale, et al.. (2021). Optimization and Modeling of Material Removal Rate in Wire-EDM of Silicon Particle Reinforced Al6061 Composite. Materials. 14(21). 6420–6420. 32 indexed citations
16.
Bongale, Arunkumar, et al.. (2021). The effects of processing parameters on the formation of oxide layers in aluminium alloys using plasma electrolytic oxidation technique. Journal of the Mechanical Behavior of Materials. 30(1). 118–129. 5 indexed citations
17.
Bongale, Arunkumar, et al.. (2020). Minimum quality lubrication: A comprehensive review. AIP conference proceedings. 2313. 20019–20019. 3 indexed citations
18.
Kumar, Satish, et al.. (2019). Influence of deep cryogenic cooling on tool wear and surface roughness of coated tungsten carbide inserts using statistical techniques. Materials Research Express. 6(7). 76517–76517. 7 indexed citations
19.
Mohan, Nanjangud, et al.. (2019). Impact of silane treated basalt fibers and montmorillonite nano-clay on polypropylene composites. Materials Research Express. 6(12). 125325–125325. 5 indexed citations
20.
Kumar, Satish, et al.. (2018). Influence of deep cryogenic treatment on dry sliding wear behaviour of AISI D3 die steel. Materials Research Express. 5(11). 116525–116525. 13 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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