S. C. Jayswal

891 total citations
38 papers, 668 citations indexed

About

S. C. Jayswal is a scholar working on Mechanical Engineering, Electrical and Electronic Engineering and Industrial and Manufacturing Engineering. According to data from OpenAlex, S. C. Jayswal has authored 38 papers receiving a total of 668 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Mechanical Engineering, 17 papers in Electrical and Electronic Engineering and 16 papers in Industrial and Manufacturing Engineering. Recurrent topics in S. C. Jayswal's work include Advanced Machining and Optimization Techniques (15 papers), Advanced machining processes and optimization (15 papers) and Advanced Surface Polishing Techniques (13 papers). S. C. Jayswal is often cited by papers focused on Advanced Machining and Optimization Techniques (15 papers), Advanced machining processes and optimization (15 papers) and Advanced Surface Polishing Techniques (13 papers). S. C. Jayswal collaborates with scholars based in India. S. C. Jayswal's co-authors include V.K. Jain, Prashant Dixit, Prashant Kumar, Sanjay Mishra, Rajesh Kumar Verma, V. K. Jain, Abhishek Kumar Singh, Kuldeep K. Saxena, Prateek Khare and J. Ramkumar and has published in prestigious journals such as International Journal of Production Research, Wear and The International Journal of Advanced Manufacturing Technology.

In The Last Decade

S. C. Jayswal

38 papers receiving 634 citations

Peers

S. C. Jayswal

EEE

IME

M. Adithan India

M. Sakthivel India

Subhas Chandra Mondal India

N.D. Chakladar India

Hartmut Weule Germany

N.S. Ong Singapore

Patrick Mattfeld Germany

Himadri Majumder India

Amauri Hassui Brazil

D. A. Dornfeld United States

M. Adithan India

S. C. Jayswal

262 ×0.7

582 ×1.8

379 ×1.5

EEE

151 ×0.7

IME

50 ×0.5

Citations per year, relative to S. C. Jayswal S. C. Jayswal (= 1×) peers M. Adithan

Countries citing papers authored by S. C. Jayswal

Since Specialization

Citations

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

Fields of papers citing papers by S. C. Jayswal

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S. C. Jayswal. 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 S. C. Jayswal. The network helps show where S. C. Jayswal may publish in the future.

Co-authorship network of co-authors of S. C. Jayswal

This figure shows the co-authorship network connecting the top 25 collaborators of S. C. Jayswal. A scholar is included among the top collaborators of S. C. Jayswal 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 S. C. Jayswal. S. C. Jayswal is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Jayswal, S. C., et al.. (2025). Deep learning approach for optimizing material removal rate in wire electrical discharge machining using neural networks. Engineering Research Express. 7(1). 15519–15519. 3 indexed citations

Verma, Rajesh Kumar, et al.. (2024). Improving the Efficiency of Single Lap Riveted Joints in the Carbon Nanofiller Reinforced Laminated Polymer Composites. Experimental Techniques. 49(2). 279–297. 1 indexed citations

Jayswal, S. C., et al.. (2024). Machining performance analysis of wire-EDM for machining of titanium alloy using multi-objective optimization and machine learning approach. Proceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical Engineering. 3 indexed citations

Verma, Rajesh Kumar, et al.. (2024). Production and machinability evaluation of reduced graphene oxide nanoparticles-reinforced polymer composites during abrasive water jet machining process. Journal of the Brazilian Society of Mechanical Sciences and Engineering. 46(10). 1 indexed citations

Gangwar, Swati, et al.. (2024). Experimental Analysis of the Mechanical Characteristics of Vinyl Ester Composites Reinforced with Sisal Fiber for Prosthetic Socket. Journal of Advanced Manufacturing Systems. 23(4). 885–908. 1 indexed citations

Verma, Rajesh Kumar, et al.. (2023). Investigation of physiochemical and mechanical properties of reduced graphene oxide (rGO) modified carbon fiber polymer composites. Journal of the Textile Institute. 115(2). 188–200. 3 indexed citations

Verma, Rajesh Kumar, et al.. (2023). Evaluation of the cutting force, burr formation, and surface quality during the machining of carbon nanoparticle modified polymer composites for structural applications. Materials Today Communications. 34. 105375–105375. 14 indexed citations

Mishra, Sanjay, et al.. (2022). Comparative analysis of DoE-based hybrid multiobjective optimization techniques for inclined laser drilling of glass fiber reinforced plastics. Multiscale and Multidisciplinary Modeling Experiments and Design. 5(3). 293–315. 1 indexed citations

Jayswal, S. C., et al.. (2021). Enhancing the performance parameters of flexible manufacturing system using decision-making techniques. International Journal of Process Management and Benchmarking. 11(2). 290–290. 1 indexed citations

10.

Mishra, Sanjay, et al.. (2021). Parametric analysis of hole circularity for laser percussion drilling of carbon fibre reinforced plastic using Nd: YAG laser. IOP Conference Series Materials Science and Engineering. 1136(1). 12056–12056. 3 indexed citations

11.

Jayswal, S. C., et al.. (2020). Magnetic abrasive flow finishing: A review. Materials Today Proceedings. 26. 3257–3264. 5 indexed citations

12.

Jayswal, S. C., et al.. (2020). Multi-Response Optimization of Magnetic Abrasive Flow Finishing Process on Aluminum (6061-T6) Using Utility Concept Embedded Firefly’s Algorithm. Journal of Advanced Manufacturing Systems. 20(1). 51–74. 1 indexed citations

13.

Jayswal, S. C., et al.. (2019). Reconfigurable manufacturing system – a new class of manufacturing system. Management and Production Engineering Review. 7 indexed citations

14.

Jayswal, S. C., et al.. (2019). Assessment of a reconfigurable manufacturing system. Benchmarking An International Journal. 28(5). 1558–1575. 18 indexed citations

15.

Jayswal, S. C., et al.. (2018). A Review on Flexibility and Reconfigurability in Manufacturing System. 187–200. 7 indexed citations

16.

Jayswal, S. C., et al.. (2017). Design of Reconfigurable Manufacturing System. HAL (Le Centre pour la Communication Scientifique Directe). 1 indexed citations

17.

Jayswal, S. C., et al.. (2017). Modelling of flexible manufacturing system: a review. International Journal of Production Research. 56(7). 2464–2487. 106 indexed citations

18.

Jayswal, S. C., et al.. (2013). Using Geometric Mean Method of Analytical Hierarchy Process for Decision Making in Functional Layout. 2(10). 14 indexed citations

19.

Jayswal, S. C., et al.. (2013). Analysis of Different Parameters on Tool Path for Machining Sculptured Surfaces. 2(10). 2 indexed citations

20.

Jain, V.K., et al.. (2001). Effect of working gap and circumferential speed on the performance of magnetic abrasive finishing process. Wear. 250(1-12). 384–390. 130 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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