Mukund Subramaniyan

635 total citations
16 papers, 422 citations indexed

About

Mukund Subramaniyan is a scholar working on Industrial and Manufacturing Engineering, Management Information Systems and Medical Laboratory Technology. According to data from OpenAlex, Mukund Subramaniyan has authored 16 papers receiving a total of 422 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Industrial and Manufacturing Engineering, 4 papers in Management Information Systems and 4 papers in Medical Laboratory Technology. Recurrent topics in Mukund Subramaniyan's work include Scheduling and Optimization Algorithms (9 papers), Assembly Line Balancing Optimization (8 papers) and Advanced Manufacturing and Logistics Optimization (6 papers). Mukund Subramaniyan is often cited by papers focused on Scheduling and Optimization Algorithms (9 papers), Assembly Line Balancing Optimization (8 papers) and Advanced Manufacturing and Logistics Optimization (6 papers). Mukund Subramaniyan collaborates with scholars based in Sweden, Germany and Italy. Mukund Subramaniyan's co-authors include Anders Skoogh, Jon Bokrantz, Maheshwaran Gopalakrishnan, Azam Sheikh Muhammad, Peter Almström, Christoph Roser, Björn Johansson, Matthias Thürer, Dan Lämkull and Pramod Bangalore and has published in prestigious journals such as Computers & Industrial Engineering, Journal of Manufacturing Systems and Production Planning & Control.

In The Last Decade

Mukund Subramaniyan

15 papers receiving 404 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mukund Subramaniyan Sweden 12 279 128 51 36 35 16 422
Alessandro Pozzetti Italy 14 498 1.8× 119 0.9× 78 1.5× 69 1.9× 31 0.9× 36 668
Hung-da Wan United States 11 139 0.5× 140 1.1× 117 2.3× 63 1.8× 14 0.4× 21 351
P. Venkumar India 10 149 0.5× 85 0.7× 110 2.2× 110 3.1× 24 0.7× 30 361
Alexandros Xanthopoulos Greece 12 189 0.7× 80 0.6× 54 1.1× 64 1.8× 40 1.1× 31 372
A. Andijani Saudi Arabia 11 151 0.5× 134 1.0× 66 1.3× 60 1.7× 13 0.4× 16 323
Maheshwaran Gopalakrishnan Sweden 12 160 0.6× 125 1.0× 79 1.5× 32 0.9× 6 0.2× 22 323
Tehseen Aslam Sweden 11 138 0.5× 65 0.5× 49 1.0× 43 1.2× 19 0.5× 25 260
Robert Glawar Austria 8 192 0.7× 55 0.4× 38 0.7× 19 0.5× 17 0.5× 19 348
Szilárd Jaskó Hungary 8 255 0.9× 48 0.4× 23 0.5× 12 0.3× 21 0.6× 19 381
Tanja Nemeth Austria 7 313 1.1× 124 1.0× 82 1.6× 24 0.7× 17 0.5× 9 494

Countries citing papers authored by Mukund Subramaniyan

Since Specialization
Citations

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

Fields of papers citing papers by Mukund Subramaniyan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mukund Subramaniyan

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

All Works

16 of 16 papers shown
1.
Skoogh, Anders, Matthias Thürer, Mukund Subramaniyan, Andréa Matta, & Christoph Roser. (2023). Throughput bottleneck detection in manufacturing: a systematic review of the literature on methods and operationalization modes. Production & Manufacturing Research. 11(1). 3 indexed citations
2.
Bokrantz, Jon, Mukund Subramaniyan, & Anders Skoogh. (2023). Realising the promises of artificial intelligence in manufacturing by enhancing CRISP-DM. Production Planning & Control. 35(16). 2234–2254. 17 indexed citations
3.
Subramaniyan, Mukund, et al.. (2021). Artificial intelligence for throughput bottleneck analysis – State-of-the-art and future directions. Journal of Manufacturing Systems. 60. 734–751. 39 indexed citations
4.
Gopalakrishnan, Maheshwaran, Mukund Subramaniyan, & Anders Skoogh. (2020). Data-driven machine criticality assessment – maintenance decision support for increased productivity. Production Planning & Control. 33(1). 1–19. 27 indexed citations
5.
Subramaniyan, Mukund, Anders Skoogh, Azam Sheikh Muhammad, et al.. (2020). A data-driven approach to diagnosing throughput bottlenecks from a maintenance perspective. Computers & Industrial Engineering. 150. 106851–106851. 21 indexed citations
6.
Subramaniyan, Mukund, Anders Skoogh, Azam Sheikh Muhammad, et al.. (2020). A generic hierarchical clustering approach for detecting bottlenecks in manufacturing. Journal of Manufacturing Systems. 55. 143–158. 55 indexed citations
7.
Subramaniyan, Mukund, et al.. (2019). Adaptive Stream-based Shifting Bottleneck Detection in IoT-based Computing Architectures. Chalmers Research (Chalmers University of Technology). 36. 993–1000. 3 indexed citations
8.
Gopalakrishnan, Maheshwaran, et al.. (2019). Data Analytics in Maintenance Planning – DAIMP. Chalmers Research (Chalmers University of Technology).
9.
Subramaniyan, Mukund, Anders Skoogh, Azam Sheikh Muhammad, Jon Bokrantz, & Ebru Turanoğlu Bekar. (2019). A prognostic algorithm to prescribe improvement measures on throughput bottlenecks. Journal of Manufacturing Systems. 53. 271–281. 17 indexed citations
10.
Subramaniyan, Mukund, et al.. (2019). Stream-IT: Continuous and dynamic processing of production systems data - throughput bottlenecks as a case-study. Chalmers Research (Chalmers University of Technology). 36. 1328–1333. 1 indexed citations
11.
Subramaniyan, Mukund, et al.. (2018). A data-driven algorithm to predict throughput bottlenecks in a production system based on active periods of the machines. Computers & Industrial Engineering. 125. 533–544. 75 indexed citations
12.
Subramaniyan, Mukund, et al.. (2018). Data-driven algorithm for throughput bottleneck analysis of production systems. Production & Manufacturing Research. 6(1). 225–246. 33 indexed citations
13.
Skoogh, Anders, et al.. (2018). Applications of Big Data analytics and Related Technologies in Maintenance—Literature-Based Research. Machines. 6(4). 54–54. 21 indexed citations
14.
Subramaniyan, Mukund, et al.. (2016). Analysis of Critical Factors for Automatic Measurement of OEE. Procedia CIRP. 57. 128–133. 61 indexed citations
15.
Subramaniyan, Mukund, et al.. (2016). Real-time data-driven average active period method for bottleneck detection. International Journal of Design & Nature and Ecodynamics. 11(3). 428–437. 15 indexed citations
16.
Subramaniyan, Mukund, et al.. (2016). An algorithm for data-driven shifting bottleneck detection. Cogent Engineering. 3(1). 34 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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