P. J. Pawar

973 total citations
32 papers, 745 citations indexed

About

P. J. Pawar is a scholar working on Mechanical Engineering, Industrial and Manufacturing Engineering and Electrical and Electronic Engineering. According to data from OpenAlex, P. J. Pawar has authored 32 papers receiving a total of 745 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Mechanical Engineering, 14 papers in Industrial and Manufacturing Engineering and 10 papers in Electrical and Electronic Engineering. Recurrent topics in P. J. Pawar's work include Advanced machining processes and optimization (19 papers), Advanced Surface Polishing Techniques (10 papers) and Advanced Machining and Optimization Techniques (10 papers). P. J. Pawar is often cited by papers focused on Advanced machining processes and optimization (19 papers), Advanced Surface Polishing Techniques (10 papers) and Advanced Machining and Optimization Techniques (10 papers). P. J. Pawar collaborates with scholars based in India, Portugal and Nepal. P. J. Pawar's co-authors include R. Venkata Rao, J. Paulo Davim, Ravi Shankar, T.P. Singh, Priyanka Paliwal and Vinayak Deshpande and has published in prestigious journals such as SHILAP Revista de lepidopterología, Applied Soft Computing and The International Journal of Advanced Manufacturing Technology.

In The Last Decade

P. J. Pawar

30 papers receiving 683 citations

Peers

P. J. Pawar

EEE

IME

Mourad Nouioua Algeria

P. Dhiraj India

Tatjana Šibalija Serbia

Sankha Deb India

G. Prabhaharan India

Franci Čuš Slovenia

Uroš Župerl Slovenia

Manas Ranjan Singh India

Lenka Čepová Czechia

Abdulaziz M. El-Tamimi Saudi Arabia

Mourad Nouioua Algeria

P. J. Pawar

496 ×1.0

370 ×1.1

EEE

100 ×0.4

IME

198 ×0.9

56 ×0.4

Citations per year, relative to P. J. Pawar P. J. Pawar (= 1×) peers Mourad Nouioua

Countries citing papers authored by P. J. Pawar

Since Specialization

Citations

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

Fields of papers citing papers by P. J. Pawar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by P. J. Pawar. 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 P. J. Pawar. The network helps show where P. J. Pawar may publish in the future.

Co-authorship network of co-authors of P. J. Pawar

This figure shows the co-authorship network connecting the top 25 collaborators of P. J. Pawar. A scholar is included among the top collaborators of P. J. Pawar 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 P. J. Pawar. P. J. Pawar 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

Pawar, P. J., et al.. (2025). Investigations into effect of waiting time in integrated machine scheduling and automated guided vehicles scheduling. International Journal on Interactive Design and Manufacturing (IJIDeM). 19(9). 6707–6724.

Pawar, P. J., et al.. (2024). Research Progress on Industrial Robots: A Review. Recent Patents on Mechanical Engineering. 19(1). 27–61. 1 indexed citations

Pawar, P. J., et al.. (2023). Minimizing cycle time and energy consumption for a multi-degree serial manipulator using teaching–learning-based optimization. Journal of the Brazilian Society of Mechanical Sciences and Engineering. 45(5). 4 indexed citations

Pawar, P. J., et al.. (2022). Flexible Job Shop Scheduling for Press Working Industries with Operation Precedence Constraint. Process Integration and Optimization for Sustainability. 6(2). 409–430. 4 indexed citations

Pawar, P. J., et al.. (2021). Experimental Investigation and Optimization of Wire Drawing Process Parameters. SSRN Electronic Journal.

Pawar, P. J., et al.. (2020). Determination of optimal tool path in drilling operation using Modified Shuffled Frog Leaping Algorithm. 32(2-4). 2 indexed citations

Pawar, P. J., et al.. (2020). A Novel Approach for Improving Quality of Learning Environment in Technical Institutions. Journal of Engineering Education/Journal of engineering education transformations/Journal of engineering education transformation. 34(1). 93–93. 1 indexed citations

Pawar, P. J., et al.. (2018). Material Flow Optimisation of Flexible Manufacturing System using Real Coded Genetic Algorithm (RCGA). Materials Today Proceedings. 5(2). 7160–7167. 11 indexed citations

Deshpande, Vinayak, et al.. (2017). An application of TOPSIS for selection of appropriate e-Governance practices to improve cus-tomer satisfaction. SHILAP Revista de lepidopterología. 2(3). 93–106. 2 indexed citations

10.

Pawar, P. J., et al.. (2017). Improving the quality characteristics of abrasive water jet machining of marble material using multi-objective artificial bee colony algorithm. Journal of Computational Design and Engineering. 5(3). 319–328. 33 indexed citations

11.

Pawar, P. J., et al.. (2016). Optimal sequence of hole-making operations using particle swarm optimization and modified shuffled frog leaping algorithm. Engineering review. 36(2). 187–196. 14 indexed citations

12.

Pawar, P. J., et al.. (2016). Review on Optimization of Hole-Making Operations for Injection Mould Using Non-Traditional Algorithms. International Journal of Industrial Engineering and Management. 7(1). 9–14. 7 indexed citations

13.

Pawar, P. J., et al.. (2016). Tool path planning of hole-making operations in ejector plate of injection mould using modified shuffled frog leaping algorithm. Journal of Computational Design and Engineering. 3(3). 266–273. 23 indexed citations

14.

Pawar, P. J., et al.. (2013). Multi-objective optimisation of grinding process parameters using NSGA-II. 2(2). 123–123. 2 indexed citations

15.

Pawar, P. J. & R. Venkata Rao. (2012). Parameter optimization of machining processes using teaching–learning-based optimization algorithm. The International Journal of Advanced Manufacturing Technology. 67(5-8). 995–1006. 101 indexed citations

16.

Rao, R. Venkata, P. J. Pawar, & J. Paulo Davim. (2010). Parameter Optimization of Ultrasonic Machining Process Using Nontraditional Optimization Algorithms. Materials and Manufacturing Processes. 25(10). 1120–1130. 59 indexed citations

17.

Rao, R. Venkata & P. J. Pawar. (2009). Parameter optimization of a multi-pass milling process using non-traditional optimization algorithms. Applied Soft Computing. 10(2). 445–456. 125 indexed citations

18.

Rao, R. Venkata & P. J. Pawar. (2009). Modelling and optimization of process parameters of wire electrical discharge machining. Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture. 223(11). 1431–1440. 96 indexed citations

19.

Rao, R. Venkata & P. J. Pawar. (2009). Grinding process parameter optimization using non-traditional optimization algorithms. Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture. 224(6). 887–898. 41 indexed citations

20.

Rao, R. Venkata, P. J. Pawar, & Ravi Shankar. (2008). Multi-objective optimization of electrochemical machining process parameters using a particle swarm optimization algorithm. Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture. 222(8). 949–958. 85 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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