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Record W303161768 · doi:10.5957/jsp.2008.24.4.221

A Computer Simulation Approach to Improving Tugboat Shipbuilding Design and Development Productivity

2008· article· en· W303161768 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

VenueJournal of Ship Production · 2008
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsDalhousie University
Fundersnot available
KeywordsShipbuildingShipyardVendorNaval architecturePipingManufacturing engineeringProductivityEngineeringProcess (computing)Operations researchComputer scienceEngineering drawingMarine engineeringMechanical engineering

Abstract

fetched live from OpenAlex

Tugboat shipbuilding design drawings are currently prepared with insufficient and untimely information of material/equipment availability, resulting in drawing changes and errors, increased labor and material costs, and lengthening of ship completion time. It is proposed that the design drawings are only prepared after confirmation of material/equipment availability from vendors to deal with the problem. The concept of concurrent engineering is introduced by integrating design and vendor activities through adequate and timely vendor-furnished information (VFI) to deal with the problem. The PERT (program evaluation and review technique) computer simulation models were employed through the use of a simulation package AweSim to analyze the work activity networks of piping drawings. A cost savings of about $1,389,700 would be possible through a 10% reduction in total design and including piping drawings and development labor costs and construction labor and material costs. The completion time for preparing design drawings and ship construction can be reduced by about 186 days or 19.5% of the total throughput time for a tugboat shipbuilding process.

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)0.001
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: none
Teacher disagreement score0.373
Threshold uncertainty score0.419

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.039
GPT teacher head0.221
Teacher spread0.182 · 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