Renan Bonnard

494 total citations
20 papers, 350 citations indexed

About

Renan Bonnard is a scholar working on Industrial and Manufacturing Engineering, Automotive Engineering and Mechanical Engineering. According to data from OpenAlex, Renan Bonnard has authored 20 papers receiving a total of 350 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Industrial and Manufacturing Engineering, 9 papers in Automotive Engineering and 7 papers in Mechanical Engineering. Recurrent topics in Renan Bonnard's work include Manufacturing Process and Optimization (15 papers), Additive Manufacturing and 3D Printing Technologies (9 papers) and Digital Transformation in Industry (6 papers). Renan Bonnard is often cited by papers focused on Manufacturing Process and Optimization (15 papers), Additive Manufacturing and 3D Printing Technologies (9 papers) and Digital Transformation in Industry (6 papers). Renan Bonnard collaborates with scholars based in Brazil, United States and France. Renan Bonnard's co-authors include Jean-Yves Hascoët, Pascal Mognol, Alberto J. Álvares, Eduardo Zancul, Márcio da Silva Arantes, Ian Stroud, Saša Živanović, Linda Lee Ho, Luiz Fernando C. S. Durão and Pierre de Saqui‐Sannes and has published in prestigious journals such as SHILAP Revista de lepidopterología, The International Journal of Advanced Manufacturing Technology and Journal of Manufacturing Systems.

In The Last Decade

Renan Bonnard

20 papers receiving 337 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Renan Bonnard Brazil 10 253 179 142 32 28 20 350
Alberto J. Álvares Brazil 12 282 1.1× 103 0.6× 132 0.9× 87 2.7× 19 0.7× 62 446
Anhua Peng China 7 139 0.5× 167 0.9× 153 1.1× 44 1.4× 14 0.5× 16 342
Zuowei Zhu China 12 279 1.1× 227 1.3× 233 1.6× 13 0.4× 13 0.5× 19 421
Achim Kampker Germany 11 114 0.5× 108 0.6× 93 0.7× 34 1.1× 16 0.6× 61 385
Lazhar Homri France 12 330 1.3× 144 0.8× 157 1.1× 33 1.0× 10 0.4× 39 467
Fred Proctor United States 11 359 1.4× 66 0.4× 146 1.0× 41 1.3× 18 0.6× 28 444
Yufan Zheng Canada 13 226 0.9× 191 1.1× 162 1.1× 33 1.0× 8 0.3× 23 466
Alexandre Durupt France 10 195 0.8× 62 0.3× 77 0.5× 23 0.7× 22 0.8× 33 311
Cong Lu China 14 464 1.8× 76 0.4× 133 0.9× 40 1.3× 8 0.3× 52 532
Vincent Thomson Canada 10 177 0.7× 38 0.2× 133 0.9× 33 1.0× 40 1.4× 36 371

Countries citing papers authored by Renan Bonnard

Since Specialization
Citations

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

Fields of papers citing papers by Renan Bonnard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Renan Bonnard

This figure shows the co-authorship network connecting the top 25 collaborators of Renan Bonnard. A scholar is included among the top collaborators of Renan Bonnard 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 Renan Bonnard. Renan Bonnard 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.
Xiao, Jinhua, Nabil Anwer, Hailong Huang, et al.. (2024). Information exchange and knowledge discovery for additive manufacturing digital thread: a comprehensive literature review. International Journal of Computer Integrated Manufacturing. 38(8). 1052–1077. 5 indexed citations
2.
Latif, Kamran, et al.. (2023). New system architecture and algorithm design for indirect STEP-NC implementation. International Journal on Interactive Design and Manufacturing (IJIDeM). 17(4). 1895–1903. 1 indexed citations
3.
Latif, Kamran, et al.. (2023). Expert system to implement STEP-NC data interface model on CNC machine. The International Journal of Advanced Manufacturing Technology. 129(11-12). 5371–5385. 2 indexed citations
4.
Arantes, Márcio da Silva, et al.. (2021). A novel unsupervised method for anomaly detection in time series based on statistical features for industrial predictive maintenance. International Journal of Data Science and Analytics. 12(4). 383–404. 14 indexed citations
5.
Bonnard, Renan, et al.. (2021). Big data/analytics platform for Industry 4.0 implementation in advanced manufacturing context. The International Journal of Advanced Manufacturing Technology. 117(5-6). 1959–1973. 23 indexed citations
6.
Bonnard, Renan, et al.. (2019). A Big Data/Analytics Platform for Industry 4.0 Implementation in SMEs. 4 indexed citations
7.
Álvares, Alberto J., et al.. (2019). Design and dimensional synthesis of a Linear Delta robot with single legs for additive manufacturing. Journal of the Brazilian Society of Mechanical Sciences and Engineering. 41(11). 18 indexed citations
8.
Durão, Luiz Fernando C. S., et al.. (2019). Optimizing additive manufacturing parameters for the fused deposition modeling technology using a design of experiments. Progress in Additive Manufacturing. 4(3). 291–313. 46 indexed citations
9.
Živanović, Saša, et al.. (2019). STEP-NC-based machining architecture applied to industrial robots. Journal of the Brazilian Society of Mechanical Sciences and Engineering. 41(8). 9 indexed citations
10.
Bonnard, Renan, Jean-Yves Hascoët, & Pascal Mognol. (2019). Data model for additive manufacturing digital thread: state of the art and perspectives. International Journal of Computer Integrated Manufacturing. 32(12). 1170–1191. 44 indexed citations
11.
Bonnard, Renan, Jean-Yves Hascoët, Pascal Mognol, & Ian Stroud. (2018). STEP-NC digital thread for additive manufacturing: data model, implementation and validation. International Journal of Computer Integrated Manufacturing. 31(11). 1141–1160. 42 indexed citations
12.
Bonnard, Renan, et al.. (2018). PROGRESSES IN THE DEVELOPMENT OF A STEP-NC COMPLIANT ADDITIVE MANUFACTURING SYSTEM. SHILAP Revista de lepidopterología. 1 indexed citations
13.
Arantes, Márcio da Silva, et al.. (2018). General architecture for data analysis in industry 4.0 using SysML and model based system engineering. 1–6. 18 indexed citations
14.
Rodriguez, Efrain E., Renan Bonnard, & Alberto J. Álvares. (2018). AVANCES EN EL DESARROLLO DE UN SISTEMA DE MANUFACTURA ADITIVA BASADO EN STEP-NC. Americanae (AECID Library). 4(1). 39–53. 3 indexed citations
15.
Bonnard, Renan, Jean-Yves Hascoët, Pascal Mognol, Eduardo Zancul, & Alberto J. Álvares. (2018). Hierarchical object-oriented model (HOOM) for additive manufacturing digital thread. Journal of Manufacturing Systems. 50. 36–52. 45 indexed citations
16.
Rodriguez, Efrain E., Renan Bonnard, & Alberto J. Álvares. (2017). PROPOSAL OF AN ADVANCED DATA MODEL FOR STEP-NC COMPLIANT ADDITIVE MANUFACTURING. 5 indexed citations
17.
Živanović, Saša, et al.. (2017). A STEP-NC compliant robotic machining platform for advanced manufacturing. The International Journal of Advanced Manufacturing Technology. 95(9-12). 3839–3854. 30 indexed citations
18.
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20.
Bonnard, Renan, Pascal Mognol, & Jean-Yves Hascoët. (2010). A new digital chain for additive manufacturing processes. Virtual and Physical Prototyping. 5(2). 75–88. 37 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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