MétaCan
Menu
Back to cohort
Record W2538040492

Feasibility study of maintenance cost reduction in redundant customer delivery systems

2005· article· en· W2538040492 on OpenAlexaff
G. Hamoud, J. Toneguzzo, Chuck Yung

Bibliographic record

VenueProbabilistic Methods Applied to Power Systems, 2004 International Conference on · 2005
Typearticle
Languageen
FieldEngineering
TopicPower System Reliability and Maintenance
Canadian institutionsHydro One (Canada)
Fundersnot available
KeywordsCorrective maintenanceReliability engineeringPredictive maintenancePreventive maintenanceCost reductionReliability (semiconductor)Planned maintenanceRedundancy (engineering)Proactive maintenanceOperational maintenanceOperations managementMaintenance engineeringRisk analysis (engineering)EngineeringBusinessComputerized maintenance management systemMarketing
DOInot available

Abstract

fetched live from OpenAlex

Maintenance is carried out on various transmission system components to keep their performance within acceptable standards and to maintain their average life expectancy. The cost associated with maintenance work is largely dependent on how often maintenance routines are performed and on the level of work to be done. Current maintenance routines on transmission system components are normally performed in accordance with equipment manufacturer's guidelines and modified by field experts as maintenance experience is gained. The implementation of the reliability-centred maintenance (RCM) in the electricity industry has reengineered the maintenance practices and has resulted in a significant saving to the industry. One area where an additional maintenance cost saving can be made is the customer delivery system with a redundancy in supply. In this system, the loss of one supply path would not adversely affect the reliability of supply to customers. By doing less frequent maintenance on one or both supply paths, some cost saving can be made without jeopardizing the reliability of supply to customers. This paper describes the study that was performed recently at Hydro One to assess the impact of reduced component maintenance cycles on the reliability' of redundant customer delivery systems. A cost/benefit analysis was performed to determine the possible consequences of reduced maintenance and to decide whether or not to stretch out the component maintenance cycle

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.565
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.060
GPT teacher head0.337
Teacher spread0.277 · 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.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

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

Citations0
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueProbabilistic Methods Applied to Power Systems, 2004 International Conference onSame topicPower System Reliability and MaintenanceFrench-language works237,207