Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Generative AI in AI-Based Digital Twins for Fault Diagnosis for Predictive Maintenance in Industry 4.0/5.0
202531 citationsEmilia Mikołajewska, Dariusz Mikołajewski et al.Applied Sciencesprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Tomasz Paczkowski
Since
Specialization
Citations
This map shows the geographic impact of Tomasz Paczkowski'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 Tomasz Paczkowski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tomasz Paczkowski more than expected).
Fields of papers citing papers by Tomasz Paczkowski
This network shows the impact of papers produced by Tomasz Paczkowski. 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 Tomasz Paczkowski. The network helps show where Tomasz Paczkowski may publish in the future.
Co-authorship network of co-authors of Tomasz Paczkowski
This figure shows the co-authorship network connecting the top 25 collaborators of Tomasz Paczkowski.
A scholar is included among the top collaborators of Tomasz Paczkowski 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 Tomasz Paczkowski. Tomasz Paczkowski 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.
Mikołajewska, Emilia, Dariusz Mikołajewski, Tadeusz Mikołajczyk, & Tomasz Paczkowski. (2025). Generative AI in AI-Based Digital Twins for Fault Diagnosis for Predictive Maintenance in Industry 4.0/5.0. Applied Sciences. 15(6). 3166–3166.31 indexed citations breakdown →
Paczkowski, Tomasz, et al.. (2012). Computer aided electrochemical shaping of curvilinear surfaces. Journal of Polish CIMAC. 7(3). 261–267.1 indexed citations
12.
Paczkowski, Tomasz, et al.. (2011). Boundary conditions analysis of ECM machining for curvilinear sufraces. Journal of Polish CIMAC. 6(3). 193–198.5 indexed citations
13.
Paczkowski, Tomasz. (2011). Theoretical analysis of electrochemical machining ECM using tool electrode with complex translatory motion. Postępy Technologii Maszyn i Urządzeń. 35. 41–54.
14.
Paczkowski, Tomasz, et al.. (2010). Adaptive control of ECM curvilinear surfaces. Journal of Machine Engineering.1 indexed citations
15.
Paczkowski, Tomasz, et al.. (2010). Electrode tool designing in the ECM machining for curvilinear surfaces. Journal of Machine Engineering.6 indexed citations
16.
Paczkowski, Tomasz. (2010). Urządzenie technologiczne do obróbki ECM powierzchni krzywoliniowych. 16–19.
17.
Paczkowski, Tomasz. (2010). Numerical simulation for ECM machining of nonlinear shaped surfaces. Journal of Polish CIMAC. 5(3). 121–132.1 indexed citations
18.
Paczkowski, Tomasz. (2007). Modelowanie obróbki ECM powierzchni o zarysie krzywoliniowym. 64–73.4 indexed citations
19.
Paczkowski, Tomasz, et al.. (2007). System komputerowy dla obróbki ECM krzywoliniowych powierzchni kształtowych. 74–81.1 indexed citations
20.
Paczkowski, Tomasz & J. Sawicki. (2002). Symulacja komputerowa procesu ECM w oparciu o dwuwymiarowy model przepływu elektrolitu między płaskimi elektrodami. 171–180.1 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.