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Record W6989824584

Calculating the reliability of a zero-energy state system

2024· article· en· W6989824584 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectrical Fault Detection and Protection
Canadian institutionsnot available
Fundersnot available
KeywordsHazardous wasteReliability (semiconductor)Control (management)ResidualState (computer science)Risk assessmentWork (physics)
DOInot available

Abstract

fetched live from OpenAlex

In Canada and other industrialized countries, workers who are required to carry out tasks in the hazardous zone of a machine when performing repairs, maintenance or unjamming activities must follow lockout procedures, unless safe alternative methods exist and can be applied. In Quebec the occupational health and safety regulation has been updated recently and several articles have been added on lockout procedures. That regulation allows for alternative control methods in addition to the traditional lockout/tagout, as long as the risk assessment deems the residual risk level to be acceptable. In Canada the CSA Z460 standard in the control of hazardous energies is viewed as a reference in the area. Lockout procedures have been extended to the construction sector for the control of hazardous energies as well. The lockout procedure consists of the following steps: stopping the equipment, isolating the energies, applying individual locks, dissipating residual energies, and verifying the absence of energies. Lockout procedures require lockout devices as well as training and audits. An important step in the lockout procedure is the verification step. Workers often neglect that step for various reasons. This article focuses on the use of dedicated safety electronic systems as an alternative to achieving a zero-energy state. These systems, rather than eliminating energy, control it to ensure workers’ safety. They are characterized by their reliability and typically involve safeguards such as interlocking devices, safety scanners, light curtains, and other safety mechanisms, during operational tasks. The article also introduces a method for calculating the reliability of these zero-energy-state system, based on the ISO 13849 standard. This method aims to help businesses comply with both the local regulation and the CSA Z460 standard. It builds upon the work of Poisson et al. (2016) [1], who calculated a zero-energy-state system in scenarios involving complex energy return recuperation systems. This innovative approach could potentially replace the need for voltage testing or machine startups following a lockout procedure. This development is particularly relevant given the increased complexity of modern machinery and the challenges in ensuring that no other energy sources that could harm workers are present post-lockout. This approach could significantly change how businesses ensure worker safety and regulatory compliance.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.202
Teacher spread0.197 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2024
Admission routes1
Has abstractyes

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