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Record W4403060869 · doi:10.1109/tmech.2024.3440658

Piezoceramic Actuation for Precision Enhancement in a Multistage Industrial Motion System

2024· article· en· W4403060869 on OpenAlexafffund
Yazan M. Al-Rawashdeh, Mohammad Al Saaideh, Mohammad Al Janaideh

Bibliographic record

VenueIEEE/ASME Transactions on Mechatronics · 2024
Typearticle
Languageen
FieldComputer Science
TopicOptical measurement and interference techniques
Canadian institutionsUniversity of GuelphMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsMotion (physics)Computer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

In this letter, a multistage design that is the result of integrating a uni-axial fine positioning piezo-actuated stage and an existing precision motion system is taken into consideration, with the fine stage being predicted to improve the overall system's precision. In an effort to account for relevant piezoceramics dynamic behavior and hysteresis, mechanical coupling between the involved stages is taken into consideration when developing the fine stage feedforward controller based on the rate–dependent Prandtl–Ishlinskii model inverse. The required multistage design steps in accordance with the above-suggested technique are described with reference to semiconductor production. The outcomes demonstrate that the suggested piezo-actuated fine stage does enhance the overall motion system's scanning accuracy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.972
Threshold uncertainty score0.747

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.053
GPT teacher head0.291
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2024
Admission routes2
Has abstractyes

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