Fernando Castaño

1.4k total citations
48 papers, 990 citations indexed

About

Fernando Castaño is a scholar working on Industrial and Manufacturing Engineering, Mechanical Engineering and Electrical and Electronic Engineering. According to data from OpenAlex, Fernando Castaño has authored 48 papers receiving a total of 990 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Industrial and Manufacturing Engineering, 17 papers in Mechanical Engineering and 14 papers in Electrical and Electronic Engineering. Recurrent topics in Fernando Castaño's work include Advanced machining processes and optimization (16 papers), Manufacturing Process and Optimization (14 papers) and Digital Transformation in Industry (13 papers). Fernando Castaño is often cited by papers focused on Advanced machining processes and optimization (16 papers), Manufacturing Process and Optimization (14 papers) and Digital Transformation in Industry (13 papers). Fernando Castaño collaborates with scholars based in Spain, Cuba and Poland. Fernando Castaño's co-authors include Rodolfo E. Haber, Alberto Villalonga, Gerardo Beruvides, Ramón Quiza, Luca Fumagalli, Elisa Negri, Marco Macchi, José L. Martínez Lastra, Wael M. Mohammed and Javier Herranz and has published in prestigious journals such as IEEE Access, Sensors and Sustainability.

In The Last Decade

Fernando Castaño

44 papers receiving 963 citations

Author Peers

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

Author Last Decade Papers Cites
Fernando Castaño 475 203 185 139 98 48 990
Chuang Wang 626 1.3× 114 0.6× 256 1.4× 66 0.5× 55 0.6× 61 1.2k
Jianjun Yi 231 0.5× 104 0.5× 171 0.9× 69 0.5× 75 0.8× 79 836
Robert Harrison 884 1.9× 164 0.8× 84 0.5× 122 0.9× 58 0.6× 118 1.5k
Christopher Irgens 543 1.1× 271 1.3× 81 0.4× 161 1.2× 71 0.7× 8 1.1k
Shilong Wang 773 1.6× 251 1.2× 127 0.7× 109 0.8× 34 0.3× 70 1.4k
Ji Zhou 554 1.2× 163 0.8× 56 0.3× 94 0.7× 83 0.8× 28 985
Seung‐Jun Shin 714 1.5× 281 1.4× 257 1.4× 54 0.4× 38 0.4× 65 1.2k
Yong Xie 187 0.4× 466 2.3× 161 0.9× 183 1.3× 140 1.4× 59 1.4k
Zhiqian Sang 596 1.3× 137 0.7× 53 0.3× 137 1.0× 49 0.5× 18 938
Chien‐Yi Huang 427 0.9× 88 0.4× 277 1.5× 57 0.4× 49 0.5× 61 840

Countries citing papers authored by Fernando Castaño

Since Specialization
Citations

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

Fields of papers citing papers by Fernando Castaño

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fernando Castaño

This figure shows the co-authorship network connecting the top 25 collaborators of Fernando Castaño. A scholar is included among the top collaborators of Fernando Castaño 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 Fernando Castaño. Fernando Castaño 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.
Villalonga, Alberto, et al.. (2025). Edge-Computing Framework for Human-Robot Collaboration in Industry 5.0: Enhancing Operator Well-Being and Efficiency in Manufacturing. DIGITAL.CSIC (Spanish National Research Council (CSIC)). 1–10.
2.
Alonso, Rubén, et al.. (2025). Automation and Robotics Pilot Lines in the Context of Industry 5.0. Applied Sciences. 15(5). 2510–2510. 1 indexed citations
3.
Villalonga, Alberto, et al.. (2024). Agent-Based Supervision for Service-Oriented Industrial Cyber–Physical Systems. IEEE Transactions on Industrial Informatics. 21(3). 2719–2728.
4.
Alonso, Rubén, Rodolfo E. Haber, Fernando Castaño, & Diego Reforgiato Recupero. (2024). Interoperable software platforms for introducing artificial intelligence components in manufacturing: A meta-framework for security and privacy. Heliyon. 10(4). e26446–e26446. 2 indexed citations
5.
Villalonga, Alberto, et al.. (2024). Enhancing Quality Inspection in Zero-Defect Manufacturing Through Robotic-Machine Collaboration. DIGITAL.CSIC (Spanish National Research Council (CSIC)). 1–6. 1 indexed citations
6.
Castaño, Fernando, et al.. (2024). Self-Reconfiguration for Smart Manufacturing Based on Artificial Intelligence: A Review and Case Study. DIGITAL.CSIC (Spanish National Research Council (CSIC)). 121–144. 6 indexed citations
7.
8.
Kossakowska, Joanna, et al.. (2021). Needs, Requirements and a Concept of a Tool Condition Monitoring System for the Aerospace Industry. Sensors. 21(15). 5086–5086. 18 indexed citations
9.
Castaño, Fernando, et al.. (2020). Quality monitoring of complex manufacturing systems on the basis of model driven approach. Smart Structures and Systems. 26(4). 495–506. 23 indexed citations
10.
Haber, Rodolfo E., et al.. (2020). Digital twin-based Optimization on the basis of Grey Wolf Method. A Case Study on Motion Control Systems. UPM Digital Archive (Technical University of Madrid). 469–474. 7 indexed citations
11.
Villalonga, Alberto, Elisa Negri, Luca Fumagalli, et al.. (2020). Local Decision Making based on Distributed Digital Twin Framework. IFAC-PapersOnLine. 53(2). 10568–10573. 24 indexed citations
12.
Haber, Rodolfo E., Ramón Quiza, Alberto Villalonga, Javier O. Pinzón-Arenas, & Fernando Castaño. (2019). Digital Twin-Based Optimization for Ultraprecision Motion Systems With Backlash and Friction. IEEE Access. 7. 93462–93472. 73 indexed citations
13.
Villalonga, Alberto, et al.. (2018). Condition-based Monitoring Architecture for CNC Machine Tools based on Global Knowledge. IFAC-PapersOnLine. 51(11). 200–204. 14 indexed citations
14.
Castaño, Fernando, Raúl M. del Toro, Rodolfo E. Haber, & Gerardo Beruvides. (2015). Conductance sensing for monitoring micromechanical machining of conductive materials. Sensors and Actuators A Physical. 232. 163–171. 18 indexed citations
15.
Beruvides, Gerardo, Ramón Quiza, Marcelino Rivas, Fernando Castaño, & Rodolfo E. Haber. (2014). A fuzzy-genetic system to predict the cutting force in microdrilling processes. 2. 34–37. 1 indexed citations
16.
Beruvides, Gerardo, Ramón Quiza, Raúl M. del Toro, Fernando Castaño, & Rodolfo E. Haber. (2014). Correlation of the holes quality with the force signals in a microdrilling process of a sintered tungsten-copper alloy. International Journal of Precision Engineering and Manufacturing. 15(9). 1801–1808. 16 indexed citations
17.
Castaño, Fernando, Rodolfo E. Haber, Raúl M. del Toro, & Gerardo Beruvides. (2014). Application of hybrid incremental modeling for predicting surface roughness in micromachining processes. 220. 54–59. 3 indexed citations
18.
Castaño, Fernando, Daniel Gaines, & Caroline C. Hayes. (1996). Improving Feature Extraction Through Closely-Coupled Integration of Fixture Analysis. 13–28. 1 indexed citations
19.
Gaines, Daniel, Fernando Castaño, & Caroline C. Hayes. (1996). Reconfigurable Feature Recognition for an Adaptable, Maintainable CAD/CAPP Integration. 1 indexed citations
20.
Castaño, Fernando. (1969). Complete circular dichroism tensor parameter in uniaxial crystals—I theory. Spectrochimica Acta Part A Molecular Spectroscopy. 25(2). 401–405. 8 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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