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Record W2002779342 · doi:10.1108/13552510710829498

Availability analysis of a generalized maintainable three‐state device parallel system with human error and common‐cause failures

2007· article· en· W2002779342 on OpenAlex

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.

Bibliographic record

VenueJournal of Quality in Maintenance Engineering · 2007
Typearticle
Languageen
FieldEngineering
TopicReliability and Maintenance Optimization
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsRedundancy (engineering)Reliability engineeringCommon cause failureHuman errorComputer scienceReliability (semiconductor)Failure mode and effects analysisState (computer science)Markov chainEngineeringCommon cause and special causeDistributed computingAlgorithmOperations management

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to study the combined effect of human error, common‐cause failure, redundancy, and maintenance policies on the performance of a system composed of three‐state devices. Design/methodology/approach Generalized expressions for time‐dependent and steady state availability of a generalized maintainable three‐state device parallel system subjected to human errors and common‐cause failures are developed in the paper under two maintenance policies: Type I repair policy (i.e. only the completely failed system is repaired); and Type II repair policy (i.e. both partially and completely failed system is repaired). The Markov method is used to develop general and special case expressions for state probabilities, and system time‐dependent and steady state availabilities. Findings In the case of three‐state devices, it is demonstrated that by increasing the number of redundant devices in parallel do not necessarily lead to the improvement in the system availability. In fact, the availability of the system depends significantly on the dominant failure mode of the devices (i.e. short‐mode or open‐mode). When comparing the effect of maintenance policies on the system availability, it is observed that the Type II repair policy does not lead to an improvement in the system availability. Furthermore, it is observed that both human error and common‐cause failure independently lead to lower system availability. Practical implications This study will help maintenance engineers and reliability practitioners to become aware of the combined impact of redundancy, human error, common‐cause failure, and maintenance policies on the performance of the three‐state device systems. Consequently, they will make better maintenance related decisions in organizations such as oil refineries and power stations that use three state devices quite extensively. Originality/value Most of the past models have independently studied the effects of redundancy, human error, and common‐cause failure on maintainable system made up of three‐state devices. This effort is one of the first attempts to study the combined effects of all these factors in a parallel system composed of three state devices.

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)0.004
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.309
Threshold uncertainty score0.892

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.273
Teacher spread0.254 · 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