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Record W2012051422 · doi:10.1115/detc2012-70430

Disassembly Sequence Planning for Product Maintenance

2012· article· en· W2012051422 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicManufacturing Process and Optimization
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsProduct (mathematics)Product lifecyclePlan (archaeology)Product design specificationComputer scienceProduct designProduct engineeringRepresentation (politics)New product developmentManufacturing engineeringProduct managementSystems engineeringReliability engineeringEngineeringBusiness

Abstract

fetched live from OpenAlex

Environmental and sustainable issues have brought more and more attention to industries in product design and manufacturing. It is important for a product to meet its lifecycle requirements in repairing, replacing and recycling. Disassembly is required in product maintenance and recycling. An efficient disassembly plan can reduce the cost of product maintenance and minimize the product repair time. This paper introduces an efficient method for selective disassembly planning for the need of product maintenance and recycling to reduce the product operation time and cost. The method is based on an efficient product representation and effective sequence searching. It considers the product structure, removing direction of components, operation constraints and complex in the product representation and sequencing planning. An example is used to verify the proposed method. Challenges and further work are also discussed.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.908
Threshold uncertainty score0.199

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 head0.032
GPT teacher head0.261
Teacher spread0.230 · 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

Citations10
Published2012
Admission routes1
Has abstractyes

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