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Record W2045219456 · doi:10.1504/ijde.2009.030179

A liaison model for disassembly-reassembly product ecodesign

2009· article· en· W2045219456 on OpenAlex
Christian Mascle, Ke Xing

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Journal of Design Engineering · 2009
Typearticle
Languageen
FieldEngineering
TopicManufacturing Process and Optimization
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEcodesignEngineeringProduct (mathematics)Fuzzy logicAutomationCADProduct modelManufacturing engineeringSystems engineeringService (business)Engineering drawingIndustrial engineeringComputer scienceMechanical engineeringSoftware engineeringArtificial intelligenceMathematics

Abstract

fetched live from OpenAlex

This paper focuses on non-destructive disassembly for mechanical products as part of environment friendly manufacturing. An original approach using a clustering method for assembly and the introduction of a mathematical model, describing the fuzzy liaisons between the components, allow us to design the product for disassembly, service, recycling, upgrading and assembly. They also facilitate the determination of the problems related to the automation of assembly and disassembly sequences generation. To do so, the modelling of functional liaisons between parts helps to distinguish a simple contact from an attachment and subsets from subassemblies. Liaisons between components are described by matrices of fuzzy half degrees of liaison. The virtual locking liaisons could be extracted automatically from a B-rep model of a mechanical product on CAD and attachment liaisons are deduced from a fuzzy evaluation of their strength and condition changes.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.865
Threshold uncertainty score0.615

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)0.0000.000

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 head0.020
GPT teacher head0.243
Teacher spread0.223 · 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