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Record W4385508744 · doi:10.1002/iis2.12979

The Power of Connection between Systems Engineering and 3D Wire Harness: Model‐Based Wire Harness Engineering at Lockheed Martin Skunk Works

2022· article· en· W4385508744 on OpenAlexaff
Chris Meeker, Clifton Davies, Pascal Fontanié, Saulius Pavalkis, Axelle Sery, Zhen Yang

Bibliographic record

VenueINCOSE International Symposium · 2022
Typearticle
Languageen
FieldEngineering
TopicSystems Engineering Methodologies and Applications
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsCable harnessEngineeringSystems Modeling LanguageMechatronicsEngineering design processConnection (principal bundle)Systems engineeringMechanical engineeringComputer scienceElectrical engineeringUnified Modeling Language

Abstract

fetched live from OpenAlex

Abstract Lockheed Martin Skunk Works has extended their digital engineering approach for wire harness engineering to span system architecture, logical design, 3D design and manufacturing representation. Their Model‐Based Wire Harness Engineering realizes the promise of Model‐Based Systems Engineering through significant improvements in integrating SysML models and 3D designs.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0040.005
Open science0.0020.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0110.003

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 head0.015
GPT teacher head0.229
Teacher spread0.214 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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
Published2022
Admission routes1
Has abstractyes

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