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Record W2093571777 · doi:10.1080/00207540701529543

Grouping operations in cellular manufacturing considering alternative routings and the impact of run length on product quality

2008· article· en· W2093571777 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

VenueInternational Journal of Production Research · 2008
Typearticle
Languageen
FieldEngineering
TopicAdvanced Manufacturing and Logistics Optimization
Canadian institutionsConcordia UniversityUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsQuality (philosophy)Cellular manufacturingProduct (mathematics)Manufacturing engineeringComputer scienceEngineeringIndustrial engineeringEngineering drawingMathematical optimizationOperations managementMathematics

Abstract

fetched live from OpenAlex

When a production lot is split into alternative routes, the production run in each route will be shortened. Merging sub-lots from different alternative routes to one selected route will result in a longer production run in the selected route. Such variation in product run length could have impacts on product quality. The paper formulates a mathematical programming model for optimal lot splitting into alternative routes to account for the impact of production run length on product quality in a cellular manufacturing environment. A genetic algorithm is developed to solve the proposed model efficiently. Numerical examples are presented to demonstrate the features of the proposed model and computational efficiency of the solution method. It further proposes extensions of the developed model and solution procedure to consider cell formation decisions when the impact of splitting production lots into alternative routes on product quality is considered.

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)0.002
metaresearch head score (Gemma)0.001
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: Empirical
Teacher disagreement score0.896
Threshold uncertainty score0.289

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 integrity0.0000.001
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 head0.099
GPT teacher head0.391
Teacher spread0.292 · 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