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.
Machine tool calibration: Measurement, modeling, and compensation of machine tool errors
2023127 citationsWei Gao, Soichi Ibaraki et al.International Journal of Machine Tools and Manufactureprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Andreas Archenti
Since
Specialization
Citations
This map shows the geographic impact of Andreas Archenti'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 Andreas Archenti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andreas Archenti more than expected).
Fields of papers citing papers by Andreas Archenti
This network shows the impact of papers produced by Andreas Archenti. 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 Andreas Archenti. The network helps show where Andreas Archenti may publish in the future.
Co-authorship network of co-authors of Andreas Archenti
This figure shows the co-authorship network connecting the top 25 collaborators of Andreas Archenti.
A scholar is included among the top collaborators of Andreas Archenti 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 Andreas Archenti. Andreas Archenti is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Gao, Wei, Soichi Ibaraki, M A. Donmez, et al.. (2023). Machine tool calibration: Measurement, modeling, and compensation of machine tool errors. International Journal of Machine Tools and Manufacture. 187. 104017–104017.127 indexed citations breakdown →
Archenti, Andreas, et al.. (2018). Online vibration condition monitoring of gas circulation fans in hardening process. 21(1). 25–29.1 indexed citations
14.
Archenti, Andreas, et al.. (2017). Hybrid machining: abrasive waterjet technologies used in combination with conventional metal cutting. Journal of Machine Engineering. 17(3). 85–96.3 indexed citations
15.
Archenti, Andreas, et al.. (2015). Performance evaluation of machining strategy for engine-block manufacturing. Journal of Machine Engineering. 15(4). 81–102.2 indexed citations
16.
Nicolescu, Mihai, et al.. (2015). New Paradigm in Control of Machining System’s Dynamics. Journal of Machine Engineering. 15(3).2 indexed citations
17.
Archenti, Andreas, et al.. (2013). Operational Modal Analysis During Milling Of Workpiece, Fixed On A Stiffness Controllable Joint. Journal of Machine Engineering. 13(2). 69–78.1 indexed citations
18.
Archenti, Andreas, et al.. (2013). Extending stability limits by designed-in damping. Journal of Machine Engineering. 13(1). 37–48.4 indexed citations
19.
Nicolescu, Mihai & Andreas Archenti. (2013). Dynamic parameter identification in nonlinear machining systems. Journal of Machine Engineering. 13(3). 91–116.1 indexed citations
20.
Archenti, Andreas, et al.. (2010). Design and Dynamic Characterization of Composite Material Dampers for Parting-Off Tools. Journal of Machine Engineering. 10(2). 57–70.
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.