Jan C. Aurich

10.1k total citations · 1 hit paper
448 papers, 7.0k citations indexed

About

Jan C. Aurich is a scholar working on Mechanical Engineering, Industrial and Manufacturing Engineering and Biomedical Engineering. According to data from OpenAlex, Jan C. Aurich has authored 448 papers receiving a total of 7.0k indexed citations (citations by other indexed papers that have themselves been cited), including 259 papers in Mechanical Engineering, 175 papers in Industrial and Manufacturing Engineering and 145 papers in Biomedical Engineering. Recurrent topics in Jan C. Aurich's work include Advanced machining processes and optimization (175 papers), Advanced Surface Polishing Techniques (136 papers) and Manufacturing Process and Optimization (90 papers). Jan C. Aurich is often cited by papers focused on Advanced machining processes and optimization (175 papers), Advanced Surface Polishing Techniques (136 papers) and Manufacturing Process and Optimization (90 papers). Jan C. Aurich collaborates with scholars based in Germany, United States and Brazil. Jan C. Aurich's co-authors include Benjamin Kirsch, Christian Fuchs, Christian Wagenknecht, Moritz Glatt, Li Yi, Fritz Klocke, E. Brinksmeier, Eric Schweitzer, Marco Zimmermann and H. Ohmori and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Cleaner Production and Journal of the American Ceramic Society.

In The Last Decade

Jan C. Aurich

423 papers receiving 6.7k citations

Hit Papers

align trajectories

Peers

Jan C. Aurich

ME

BE

IME

EEE

MARKE

Konstantinos Salonitis United Kingdom

David Dornfeld United States

I.S. Jawahir United States

George Chryssolouris Greece

Joost R. Duflou Belgium

Dazhong Wu United States

Eckart Uhlmann Germany

Huajun Cao China

P. Venkateswara Rao India

Wen Feng Lu Singapore

Konstantinos Salonitis United Kingdom

Jan C. Aurich

2.6k ×0.6

ME

870 ×0.3

BE

1.7k ×1.0

IME

807 ×0.5

EEE

359 ×0.5

MARKE

Citations per year, relative to Jan C. Aurich Jan C. Aurich (= 1×) peers Konstantinos Salonitis

Countries citing papers authored by Jan C. Aurich

Since Specialization

Citations

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

Fields of papers citing papers by Jan C. Aurich

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jan C. Aurich. 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 Jan C. Aurich. The network helps show where Jan C. Aurich may publish in the future.

Co-authorship network of co-authors of Jan C. Aurich

This figure shows the co-authorship network connecting the top 25 collaborators of Jan C. Aurich. A scholar is included among the top collaborators of Jan C. Aurich 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 Jan C. Aurich. Jan C. Aurich 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

1.

Klar, Matthias, et al.. (2025). Selection of manufacturing processes using graph neural networks. Journal of Manufacturing Systems. 80. 176–193. 3 indexed citations

2.

Aurich, Jan C., et al.. (2024). Investigation on different laser beam profiles in high-speed directed energy deposition. Procedia CIRP. 126. 609–614. 1 indexed citations

3.

Kirsch, Benjamin, et al.. (2024). Investigation on different laser-powder alignments and their influence on part properties in high-speed Directed Energy Deposition. Procedia CIRP. 124. 190–193.

4.

Aurich, Jan C., et al.. (2024). A Comparative Analysis of Axis Drive Current Measurements in CNC Machine Tools for Machine Learning Assisted Process Monitoring. Procedia CIRP. 130. 214–219. 1 indexed citations

5.

Hill, Michael R., et al.. (2023). Experimental study on the effect of the milling condition of an aluminum alloy on subsurface residual stress. The International Journal of Advanced Manufacturing Technology. 127(11-12). 5487–5501. 8 indexed citations

6.

Klar, Matthias, et al.. (2023). Explainable generative design in manufacturing for reinforcement learning based factory layout planning. Journal of Manufacturing Systems. 72. 74–92. 12 indexed citations

7.

Klar, Matthias, et al.. (2023). Multi-objective Quantum Annealing approach for solving flexible job shop scheduling in manufacturing. Journal of Manufacturing Systems. 72. 142–153. 19 indexed citations

8.

D’Elia, Christopher R., Daniel Weber, Benjamin Kirsch, et al.. (2022). The Effect of Bulk Residual Stress on Milling-Induced Residual Stress and Distortion. Experimental Mechanics. 62(8). 1437–1459. 11 indexed citations

9.

Blinn, Bastian, Marek Smaga, Marco Zimmermann, et al.. (2021). Influence of microstructural defects and the surface topography on the fatigue behavior of “additively‐subtractively” manufactured specimens made of AISI 316L. Materialwissenschaft und Werkstofftechnik. 52(5). 561–577. 4 indexed citations

10.

D’Elia, Christopher R., Daniel Weber, Benjamin Kirsch, et al.. (2021). Intermethod Comparison and Evaluation of Measured Near Surface Residual Stress in Milled Aluminum. Experimental Mechanics. 61(8). 1309–1322. 21 indexed citations

11.

Eifler, Matthias, et al.. (2020). Determination of the surface topography of ball end micro milled material measures. Engineering Science and Technology an International Journal. 24(2). 543–555. 8 indexed citations

12.

Hotz, Hendrik, et al.. (2020). Improving the tribological properties of radial shaft seal countersurfaces using experimental micro peening and classical shot peening processes. Tribology International. 155. 106764–106764. 20 indexed citations

13.

Kirsch, Benjamin, et al.. (2020). Formulation of sub-zero metalworking fluids for cutting processes: Influence of additives. CIRP journal of manufacturing science and technology. 31. 25–33. 11 indexed citations

14.

Kirsch, Benjamin, et al.. (2019). Micro hardness determination on a rough surface by using combined indentation and topography measurements. Surface Topography Metrology and Properties. 7(4). 45021–45021. 8 indexed citations

15.

Blinn, Bastian, et al.. (2019). Influence of the Chemical Composition of the Used Powder on the Fatigue Behavior of Additively Manufactured Materials. Metals. 9(12). 1285–1285. 10 indexed citations

16.

Blinn, Bastian, et al.. (2018). An Investigation of the Microstructure and Fatigue Behavior of Additively Manufactured AISI 316L Stainless Steel with Regard to the Influence of Heat Treatment. Metals. 8(4). 220–220. 102 indexed citations

17.

Hotz, Hendrik, et al.. (2017). Estimation of Heat Transfer Properties for the FE Simulation of Cryogenic Turning. PAMM. 17(1). 401–402. 1 indexed citations

18.

Aurich, Jan C., et al.. (2016). Turning of aluminum metal matrix composites: influence of the reinforcement and the cutting condition on the surface layer of the workpiece. Advances in Manufacturing. 4(3). 225–236. 17 indexed citations

19.

Aurich, Jan C., et al.. (2014). Polishing of Porcelain Tiles in Industrial- and Laboratory-scale. Repositori UJI (Universitat Jaume I). 3 indexed citations

20.

Aurich, Jan C. & D. A. Dornfeld. (2010). Burrs - analysis, control and removal : proceedings of the CIRP International Conference on Burrs, 2nd-3rd April, 2009, University of Kaiserslautern, Germany. Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)). 7 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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