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Record W181187632 · doi:10.1139/tcsme-2010-0014

A NEW ALGORITHM FOR U-SHAPED TWO-SIDED ASSEMBLY LINE BALANCING

2010· article· en· W181187632 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2010
Typearticle
Languageen
FieldEngineering
TopicAssembly Line Balancing Optimization
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsAlgorithmAssembly lineLine (geometry)ScheduleComputer scienceSimple (philosophy)Product (mathematics)Flow (mathematics)Mathematical optimizationMathematicsEngineeringGeometry

Abstract

fetched live from OpenAlex

This study introduces a new hybrid design for a specific case of assembly lines, and proposes a multi-pass random assignment algorithm to find the minimum number of stations required. The algorithm also finds the sequence and the schedule of the tasks assigned. The new design is a combination of two-sided lines and U-shaped lines, which benefits from the advantages of both designs at the same time. One side of the line is arranged in U-shape allowing stations with crossovers, and the other side of the line is balanced like a traditional straight flow. Depending on product direction, either Left or Right side of the line can be designed in U-shape. Small and large-sized two-sided assembly line test-bed problems were solved using the algorithm. Optimal results are achieved for all small-sized problems. Due to the novelty of the design, results of largesized problems are compared to findings of studies on simple two-sided balancing. Algorithm produced better results in most of the cases.

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: Methods
Teacher disagreement score0.434
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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 head0.007
GPT teacher head0.211
Teacher spread0.204 · 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