MétaCan
Menu
Back to cohort
Record W2731705301 · doi:10.4050/f-0070-2014-9650

Transitioning to MBSE in a Large Systems Engineering Organization that Develops Complex Mission System for Helicopters

2014· article· en· W2731705301 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSystems Engineering Methodologies and Applications
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsSystems engineeringComputer scienceEngineering

Abstract

fetched live from OpenAlex

Transitioning from a Document Based Systems Engineering approach to a Model Based Systems Development (MBSD) approach in a large systems engineering organization with both legacy and start up programs presents a serious challenge. MBSD differs from Model Based Systems Engineering (MBSE) in that it applies across the design disciplines (SW, I&T, HW, CM). Barriers include concerns about increased cost and schedule to new programs and minimizing impacts to legacy programs with a large investment in non-model based artifacts. In spite of these concerns, future programs will demand a systems engineering environment that enhances the ability of the engineering team to collaborate across both disciples and geography. For this reason Lockheed Martin's Mission Systems and Training (MST) facility in Owego NY, whose primary product includes complex mission systems for manned and unmanned helicopter systems, has begun the transition from a Document Based Approach to a Model Based Approach. Several key goals associated with the transition include providing a turnkey approach to programs, automated generation of systems engineering work products from the model and support for reusable software components. This paper discusses the approach to defining and achieving these goals and provides recommendations for organizations that are interested in transitioning to MBSD.

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: none
Teacher disagreement score0.851
Threshold uncertainty score0.727

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 head0.043
GPT teacher head0.246
Teacher spread0.203 · 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