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Record W2887746617 · doi:10.24908/pceea.v0i0.10185

WHICH DESIGN METHODOLOGIES ARE EFFECTIVE TO SUPPORT A CAPSTONE PROJECT IN AEROSPACE DESIGN ENGINEERING?

2018· article· en· W2887746617 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.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicQuality Function Deployment in Product Design
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of CanadaConcordia University
KeywordsCapstoneQuality function deploymentAerospaceContext (archaeology)Engineering managementTRIZEngineeringSystems engineeringSoftware deploymentEngineering design processConcurrent engineeringManufacturing engineeringComputer scienceSoftware engineeringMechanical engineeringOperations managementAerospace engineering

Abstract

fetched live from OpenAlex

Abstract – Considering the challenges in the aerospace industry, the NSERC (Natural Sciences and Engineering Research Council of Canada) Chair in Aerospace Design Engineering (NCADE) has launched its own version of a final year undergraduate engineering capstone project at Concordia University. NCADE’s objective is to expose students to the immense complexity of an aircraft design, thereby better meeting the industry needs of newly graduated students. Four design methodologies (i.e., systems engineering – SE, quality function deployment – QFD, theory of inventive problem solving – TRIZ, and environment-based design – EBD) were evaluated in the context of the NCADE project to answer the research question such as "to what extent do these methodologies provide effective support across the activities in the capstone project?" The evaluation was subjective discussing whether the design methodologies support the activities in the project. From the evaluation, it can be concluded that the studied design methodologies perform poorly to support the activities in the capstone project. Therefore, future research should investigate a better support for the capstone project to achieve NCADE’s goals.

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)0.004
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.544
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
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 head0.040
GPT teacher head0.270
Teacher spread0.230 · 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