MétaCan
Menu
Back to cohort
Record W1999741095 · doi:10.1504/ijssci.2010.029864

A heuristic model and software development for SMT line balancing: a case study

2009· article· en· W1999741095 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 Services Sciences · 2009
Typearticle
Languageen
FieldEngineering
TopicAssembly Line Balancing Optimization
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsWorkloadAutomationComputer scienceSoftwareAssembly lineHeuristicManufacturing engineeringPrinted circuit boardIndustrial engineeringEngineeringOperating systemArtificial intelligence

Abstract

fetched live from OpenAlex

Printed circuit board assembly (PCBA) is the major portion of manufacturing processes of electronic manufacturing services (EMS) industry, where surface mounting technology (SMT) has become the primary assembly method. Two series-connected SMT placement machines in a SMT assembly line are often the bottlenecks due to the unevenly distributed workloads. This paper studies the line balancing of the SMT assembly line focusing on the workload distribution between the two placement machines. A heuristic approach is proposed to reduce the workload difference of the two machines without increasing the total machine setup time. A software, which can be used as an effective automation tool for a company, is then developed based on the heuristic model. This will increase the quality of the service that the company provides to its customers.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.294

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 head0.019
GPT teacher head0.290
Teacher spread0.271 · 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