Moritz Glatt

1.0k total citations
68 papers, 641 citations indexed

About

Moritz Glatt is a scholar working on Industrial and Manufacturing Engineering, Mechanical Engineering and Automotive Engineering. According to data from OpenAlex, Moritz Glatt has authored 68 papers receiving a total of 641 indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Industrial and Manufacturing Engineering, 18 papers in Mechanical Engineering and 16 papers in Automotive Engineering. Recurrent topics in Moritz Glatt's work include Manufacturing Process and Optimization (27 papers), Digital Transformation in Industry (21 papers) and Additive Manufacturing and 3D Printing Technologies (15 papers). Moritz Glatt is often cited by papers focused on Manufacturing Process and Optimization (27 papers), Digital Transformation in Industry (21 papers) and Additive Manufacturing and 3D Printing Technologies (15 papers). Moritz Glatt collaborates with scholars based in Germany, United States and Brazil. Moritz Glatt's co-authors include Jan C. Aurich, Li Yi, Matthias Klar, Bahram Ravani, Barbara Linke, Wentao Duan, Hans D. Schotten, Dirk Bähre, Benjamin Kirsch and Daniel Werner Kull and has published in prestigious journals such as The Lancet, Journal of Cleaner Production and Additive manufacturing.

In The Last Decade

Moritz Glatt

64 papers receiving 602 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Moritz Glatt Germany 15 426 151 133 70 58 68 641
Jumyung Um South Korea 13 422 1.0× 129 0.9× 84 0.6× 29 0.4× 42 0.7× 53 638
Yilin Fang China 11 574 1.3× 75 0.5× 62 0.5× 41 0.6× 72 1.2× 36 723
Eoin P. Hinchy Ireland 11 421 1.0× 162 1.1× 61 0.5× 86 1.2× 53 0.9× 20 780
Kaipu Wang China 16 836 2.0× 103 0.7× 117 0.9× 30 0.4× 154 2.7× 29 982
Christopher Sacco United States 8 288 0.7× 161 1.1× 95 0.7× 53 0.8× 36 0.6× 10 573
Tariku Sinshaw Tamir China 13 170 0.4× 133 0.9× 206 1.5× 78 1.1× 52 0.9× 27 482
Éric Coatanéa Finland 16 316 0.7× 366 2.4× 214 1.6× 34 0.5× 48 0.8× 83 720
Kendrik Yan Hong Lim Singapore 6 498 1.2× 56 0.4× 52 0.4× 41 0.6× 62 1.1× 12 690
Ian Stroud Switzerland 16 477 1.1× 325 2.2× 159 1.2× 68 1.0× 53 0.9× 34 800

Countries citing papers authored by Moritz Glatt

Since Specialization
Citations

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

Fields of papers citing papers by Moritz Glatt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Moritz Glatt

This figure shows the co-authorship network connecting the top 25 collaborators of Moritz Glatt. A scholar is included among the top collaborators of Moritz Glatt 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 Moritz Glatt. Moritz Glatt 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.
Yi, Li, Moritz Glatt, Matthias Klar, et al.. (2024). Experimental evaluation of 5G performance based on a digital twin of a machine tool. CIRP journal of manufacturing science and technology. 55. 141–152. 8 indexed citations
2.
Glatt, Moritz, et al.. (2024). Engaging human-centered design to maintain part manufacturing under reduced workforce restrictions. Production Engineering. 2 indexed citations
3.
Glatt, Moritz, et al.. (2024). Tool condition monitoring in drilling processes using anomaly detection approaches based on control internal data. Procedia CIRP. 121. 216–221. 10 indexed citations
4.
Klar, Matthias, et al.. (2024). Transferable multi-objective factory layout planning using simulation-based deep reinforcement learning. Journal of Manufacturing Systems. 74. 487–511. 6 indexed citations
5.
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
6.
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
7.
Yi, Li, et al.. (2023). Reusable unit process life cycle inventory for manufacturing: high speed laser directed energy deposition. Production Engineering. 17(5). 715–731. 3 indexed citations
8.
Kirsch, Benjamin, et al.. (2023). Investigation of the Process Windows of PBF-LB/Ti6Al4V for Variable Laser Spot Diameters. SSRN Electronic Journal.
9.
Glatt, Moritz, et al.. (2023). CAD-based data augmentation and transfer learning empowers part classification in manufacturing. The International Journal of Advanced Manufacturing Technology. 125(11-12). 5605–5618. 7 indexed citations
10.
Yi, Li, et al.. (2023). Service provision process scheduling using quantum annealing for technical product-service systems. Procedia CIRP. 116. 330–335. 2 indexed citations
11.
Yi, Li, et al.. (2023). Evaluating the environmental impact of high-speed laser directed energy deposition: A life cycle assessment. Procedia CIRP. 120. 1606–1611. 4 indexed citations
12.
Glatt, Moritz, et al.. (2023). Energy supply scheduling in manufacturing systems using Quantum Annealing. Manufacturing Letters. 38. 47–51.
13.
Glatt, Moritz, et al.. (2022). Designing Resilient Manufacturing Systems using Cross Domain Application of Machine Learning Resilience. Procedia CIRP. 115. 83–88. 3 indexed citations
14.
Tashakor, Nima, et al.. (2022). Evaluation of 5G-capable framework for highly mobile, scalable human-machine interfaces in cyber-physical production systems. Journal of Manufacturing Systems. 64. 578–593. 21 indexed citations
15.
Klar, Matthias, et al.. (2022). Scalability investigation of Double Deep Q Learning for factory layout planning. Procedia CIRP. 107. 161–166. 12 indexed citations
16.
Glatt, Moritz. (2021). Video Data for "Development and implementation of a system for the automated removal of parts produced by Fused Deposition Modeling". Data Archiving and Networked Services (DANS). 1. 1 indexed citations
17.
Glatt, Moritz, et al.. (2020). Modelle als Grundlage für den Digitalen Zwilling. Zeitschrift für wirtschaftlichen Fabrikbetrieb. 115(5). 340–343. 3 indexed citations
18.
Glatt, Moritz, et al.. (2020). Rahmenwerk zur Einordnung Digitaler Zwillinge in Produktionssystemen. Zeitschrift für wirtschaftlichen Fabrikbetrieb. 115(6). 429–433. 2 indexed citations
19.
Yi, Li, et al.. (2020). A method for energy modeling and simulation implementation of machine tools of selective laser melting. Journal of Cleaner Production. 263. 121282–121282. 27 indexed citations
20.
Glatt, Moritz & Jan C. Aurich. (2019). Physical modeling of material flows in cyber-physical production systems. Procedia Manufacturing. 28. 10–17. 11 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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