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Record W7057159162

Improving new product development using process simulation

2014· dissertation· en· W7057159162 on OpenAlexaff

Bibliographic record

VenueOpen MIND · 2014
Typedissertation
Languageen
FieldMaterials Science
TopicThermal properties of materials
Canadian institutionsMcGill University
Fundersnot available
KeywordsAerospaceProcess (computing)New product developmentProduct (mathematics)Critical path methodWork (physics)Order (exchange)Quality (philosophy)Automotive industry
DOInot available

Abstract

fetched live from OpenAlex

Bombardier Aerospace currently puts more effort into developing new products at a faster pace. The goal of this thesis is to study the effect of sharing an aeroelastic model between the Loads and Dynamics departments at Bombardier Aerospace as well as to seek out other opportunities in order to reduce total effort. The work in this thesis is based on a previous project that was conducted two years ago in order to establish process maps for the two departments and to simulate the aeroelastic model sharing scenario.In the present thesis, two types of strategies are applied: (1) add resources to the tasks located on the critical path to shorten project span time; (2) seek opportunities for sharing design processes which in turn reduce total effort. Firstly, the process maps for the two departments were updated and verified. Secondly, the critical tasks were identified on the process maps. In addition, the process maps were shown to the engineers in both departments to look for potentially sharable design processes. Thirdly, the scenarios with additional resources and with shared processes were simulated. The benefits of the scenarios were observed by comparing two factors: (1) project span time and (2) effort. Afterwards, the quality of the inputs and the design processes was investigated. Finally, this thesis concludes with validated simulation results, suggested optimal solutions to reduce the span time and effort, and guidance for future work.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.123
Threshold uncertainty score1.000

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 communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.002

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 head0.071
GPT teacher head0.348
Teacher spread0.277 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2014
Admission routes1
Has abstractyes

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