Jungyub Woo

677 total citations
23 papers, 475 citations indexed

About

Jungyub Woo is a scholar working on Industrial and Manufacturing Engineering, Information Systems and Renewable Energy, Sustainability and the Environment. According to data from OpenAlex, Jungyub Woo has authored 23 papers receiving a total of 475 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Industrial and Manufacturing Engineering, 6 papers in Information Systems and 6 papers in Renewable Energy, Sustainability and the Environment. Recurrent topics in Jungyub Woo's work include Manufacturing Process and Optimization (13 papers), Flexible and Reconfigurable Manufacturing Systems (8 papers) and Digital Transformation in Industry (7 papers). Jungyub Woo is often cited by papers focused on Manufacturing Process and Optimization (13 papers), Flexible and Reconfigurable Manufacturing Systems (8 papers) and Digital Transformation in Industry (7 papers). Jungyub Woo collaborates with scholars based in United States, South Korea and France. Jungyub Woo's co-authors include Seung‐Jun Shin, Sudarsan Rachuri, SangSu Choi, Wonchul Seo, Ju Yeon Lee, Jun Kim, David Lechevalier, Sanjay Jain, Duck Bong Kim and Senthilkumaran Kumaraguru and has published in prestigious journals such as Journal of Cleaner Production, Expert Systems with Applications and Sensors.

In The Last Decade

Jungyub Woo

22 papers receiving 451 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Jungyub Woo 345 106 93 70 65 23 475
Stefan Braunreuther 269 0.8× 83 0.8× 37 0.4× 62 0.9× 65 1.0× 58 451
Annalisa Santolamazza 176 0.5× 48 0.5× 47 0.5× 49 0.7× 64 1.0× 15 396
Gerrit Posselt 175 0.5× 118 1.1× 41 0.4× 25 0.4× 30 0.5× 20 408
Johannes Wagner 227 0.7× 23 0.2× 39 0.4× 28 0.4× 85 1.3× 56 493
Egon Müller 419 1.2× 127 1.2× 54 0.6× 36 0.5× 88 1.4× 55 615
Deogratias Kibira 266 0.8× 43 0.4× 38 0.4× 30 0.4× 71 1.1× 40 435
Martin Ruskowski 368 1.1× 14 0.1× 63 0.7× 43 0.6× 36 0.6× 90 565
Jan Schlechtendahl 319 0.9× 34 0.3× 32 0.3× 33 0.5× 54 0.8× 14 458
Emmanuel Adam 239 0.7× 35 0.3× 20 0.2× 15 0.2× 25 0.4× 19 361
Nicole Stricker 643 1.9× 28 0.3× 44 0.5× 14 0.2× 138 2.1× 57 816

Countries citing papers authored by Jungyub Woo

Since Specialization
Citations

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

Fields of papers citing papers by Jungyub Woo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jungyub Woo

This figure shows the co-authorship network connecting the top 25 collaborators of Jungyub Woo. A scholar is included among the top collaborators of Jungyub Woo 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 Jungyub Woo. Jungyub Woo 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.
Choi, SangSu, et al.. (2022). Building Korean DMZ Metaverse Using a Web-Based Metaverse Platform. Applied Sciences. 12(15). 7908–7908. 25 indexed citations
2.
Choi, SangSu, et al.. (2021). A Survey and Analysis of Research on Digital Twin in Korea. 26(1). 59–69. 5 indexed citations
3.
Choi, SangSu, et al.. (2021). User-Friendly Method of Digital Twin Application based on Cloud Platform for Smart Manufacturing. Transactions of the Korean Society of Mechanical Engineers A. 45(2). 175–184. 2 indexed citations
4.
Woo, Jungyub, et al.. (2020). A Cloud-based Digital Twin Manufacturing System based on an Interoperable Data Schema for Smart Manufacturing. International Journal of Computer Integrated Manufacturing. 33(12). 1259–1276. 55 indexed citations
5.
Shin, Seung‐Jun, Jungyub Woo, Sudarsan Rachuri, & Wonchul Seo. (2019). An energy-efficient process planning system using machine-monitoring data: A data analytics approach. Computer-Aided Design. 110. 92–109. 17 indexed citations
6.
Shin, Seung‐Jun, et al.. (2018). Standard Data-Based Predictive Modeling for Power Consumption in Turning Machining. Sustainability. 10(3). 598–598. 15 indexed citations
7.
Woo, Jungyub, et al.. (2018). Developing a big data analytics platform for manufacturing systems: architecture, method, and implementation. The International Journal of Advanced Manufacturing Technology. 99(9-12). 2193–2217. 53 indexed citations
8.
Shin, Seung‐Jun, Jungyub Woo, & Wonchul Seo. (2017). Development of a Data and Model-Interconnected Holonic Architecture for Intelligent Decision-Making on Cyber-Physical Production Systems. Journal of Korean Institute of Industrial Engineers. 43(6). 451–463. 2 indexed citations
9.
Shin, Seung‐Jun, et al.. (2017). Energy Prediction Modeling for Numerical Control Programs Using MTConnect. Journal of the Korean Society for Precision Engineering. 34(5). 355–362. 4 indexed citations
10.
Shin, Seung‐Jun, Jungyub Woo, & Sudarsan Rachuri. (2017). Energy efficiency of milling machining: Component modeling and online optimization of cutting parameters. Journal of Cleaner Production. 161. 12–29. 86 indexed citations
11.
Shin, Seung‐Jun, Jungyub Woo, & Wonchul Seo. (2016). Developing a Big Data Analytics Platform Architecture for Smart Factory. Journal of Korea Multimedia Society. 19(8). 1516–1529. 2 indexed citations
12.
Jain, Sanjay, David Lechevalier, Jungyub Woo, & Seung‐Jun Shin. (2015). Towards a Virtual Factory Prototype | NIST. Winter Simulation Conference. 2 indexed citations
13.
Jain, Sanjay, David Lechevalier, Jungyub Woo, & Seung‐Jun Shin. (2015). Towards a virtual factory prototype. Winter Simulation Conference. 2207–2218. 11 indexed citations
14.
Shin, Seung‐Jun, Jungyub Woo, Duck Bong Kim, Senthilkumaran Kumaraguru, & Sudarsan Rachuri. (2015). Developing a virtual machining model to generate MTConnect machine-monitoring data from STEP-NC. International Journal of Production Research. 54(15). 4487–4505. 37 indexed citations
15.
Jain, Sanjay, David Lechevalier, Jungyub Woo, & Seung‐Jun Shin. (2015). Towards a virtual factory prototype. 2015 Winter Simulation Conference (WSC). 2015. 2207–2218. 17 indexed citations
16.
Libes, Don, Seung‐Jun Shin, & Jungyub Woo. (2015). Considerations and recommendations for data availability for data analytics for manufacturing. 68–75. 8 indexed citations
17.
Shin, Seung‐Jun, Jungyub Woo, & Sudarsan Rachuri. (2014). Predictive Analytics Model for Power Consumption in Manufacturing. Procedia CIRP. 15. 153–158. 92 indexed citations
18.
Durand, Jacques, et al.. (2011). XTemp: Event-driven Testing and Monitoring of Business processes. Balisage series on markup technologies. 7. 2 indexed citations
19.
Woo, Jungyub, et al.. (2007). JESS-based web interface for XML document validation. Expert Systems with Applications. 36(1). 683–689. 1 indexed citations
20.
Kulvatunyou, Boonserm, Jungyub Woo, & Hyunbo Cho. (2003). Collaborative Evolution of Process Plans in Distributed Manufacturing. 1 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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