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Record W2495129274 · doi:10.4271/2016-01-2104

Unique Material Handling and Automated Metrology Systems Provides Backbone of Accurate Final Assembly Line for Business Jet

2016· article· en· W2495129274 on OpenAlexaff
Robert Flynn, Kevin Payton-Stewart, Patrick Brewer, Ryan W. Davidge

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2016
Typearticle
Languageen
FieldEngineering
TopicManufacturing Process and Optimization
Canadian institutionsBombardier (Canada)
Fundersnot available
KeywordsMetrologyLine (geometry)Jet (fluid)Computer scienceAssembly lineEngineering drawingManufacturing engineeringMechanical engineeringEngineeringOpticsPhysicsAerospace engineering

Abstract

fetched live from OpenAlex

<div class="section abstract"><div class="htmlview paragraph"><figure id="F1" class="figure"><div class="graphic-wrapper"><img class="article-figure figure" src="2016-01-2104_fig0001.jpg" alt="Global 7000 Business Jet. Photo credit: Robert Backus."/></div><span class="label">Figure 1</span><figcaption class="caption"><span class="title">Global 7000 Business Jet. Photo credit: Robert Backus.</span></figcaption></figure></div><div class="htmlview paragraph">The customer’s assembly philosophy demanded a fully integrated flexible pulse line for their Final Assembly Line (FAL) to assemble their new business jets. Major challenges included devising a new material handling system, developing capable positioners and achieving accurate joins while accommodating two different aircraft variants (requiring a “flexible” system). An additional requirement was that the system be easily relocated to allow for future growth and reorganization.</div><div class="htmlview paragraph">Crane based material handling presents certain collision and handover risks, and also present a logistics challenge as cranes can become overworked. Automated guided vehicles can be used to move large parts such as wings, but the resulting sweep path becomes a major operational limitation. The customer did not like the trade-offs for either of these approaches. A unique conveyance system (ATLAS) based on in-floor rails was developed to offer a solution that provides highly controlled, low risk and accurate moves that allow workers and tools to remain in the assembly area. Positioners were developed, some of which include a driven passive axis (DP axis), useful in certain conditions for driving positioners in their passive axis.</div><div class="htmlview paragraph">Accurate and rapid joins required an advanced metrology solution. Integrating this automated metrology based positioning system posed a challenge. The accuracy requirement meant that the system had to measure and accommodate slight differences between the incoming parts i.e., be an “adaptive” system. A Human Machine Interface (HMI) was developed to enable de-skilled automated metrology and to communicate with the metrology and PLC systems. The HMI presents a virtual task checklist and restricts the user from deviating from the order of operations or omitting any tasks. Established tolerances must be achieved before proceeding to the next task. A robust architecture allows failed tasks to be re-attempted without restarting the join process, resulting in a forgiving and flexible process. Integrated supervisor-override privileges make it possible to execute alignment adjustments if dictated by engineering or circumstance.</div></div>

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.

How this classification was reachedexpand

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.969
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.016
GPT teacher head0.243
Teacher spread0.227 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2016
Admission routes1
Has abstractyes

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