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Record W1838147031 · doi:10.1109/tdcllm.2000.882854

Reliability centered maintenance implementation in Hydro-Quebec transmission system

2000· article· en· W1838147031 on OpenAlex
C. Rajotte, A. Jolicoeur

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower System Reliability and Maintenance
Canadian institutionsHydro-Québec
Fundersnot available
KeywordsTask (project management)Reliability engineeringReliability (semiconductor)Computer sciencePreventive maintenanceInterval (graph theory)Order (exchange)Maintenance engineeringRisk analysis (engineering)Selection (genetic algorithm)Operations researchEngineeringSystems engineeringBusinessArtificial intelligence

Abstract

fetched live from OpenAlex

In today's competitive market, utilities want to optimize their maintenance efforts in order to maximize equipment reliability and availability at lowest cost. Thus, utilities want to know as much as possible the real condition of equipment by the use of an optimal SPM (systematic preventive maintenance) program. An SPM program usually defines "what to do" and "when to do" SPM actions. The "what" and the "when" are of course closely related because for any inappropriate task selection, there won't be any appropriate task interval that will prevent failure. Inversely, appropriate actions performed at an inappropriate interval will lead to a nonoptimized SPM program (too expensive or poor apparatus reliability). The RCM method is very effective to select "what to do" in a SPM program. Optimal task interval ("when to do") is rather defined by the use of historical data and experience or, for some utilities, by economical evaluation.

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.

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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.809
Threshold uncertainty score0.849

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.215
Teacher spread0.210 · 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

Quick stats

Citations3
Published2000
Admission routes2
Has abstractyes

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