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Record W2045401621 · doi:10.1243/0954405011519231

Calculation of product architecture metrics within a solid modeller

2001· article· en· W2045401621 on OpenAlexaff
Johnathan Line, Mark Steiner

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture · 2001
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicProduct Development and Customization
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsComputer scienceModular designArchitectureProduct (mathematics)Measure (data warehouse)Function (biology)MODELLERData miningMathematicsProgramming language

Abstract

fetched live from OpenAlex

The architecture of a product is defined as the scheme in which functions are mapped to physical components. Architecture affects how a product satisfies design objectives. There are several ways to measure architecture, and one is implemented into a solid modelling program that will do the quantification automatically. The software used is the I-DEAS solid modelling package, for which an internal program file was created to perform the calculations automatically. This program works by counting the parts that the user has created and then uses an internal I-DEAS function to find all of the joined parts. The program counts the joints and then prompts the user for the strength of each joint. With this information, an adjusted parts connectivity and average joint strength are calculated and can be used to evaluate the degree to which the architecture of a product is either integral or modular. Several case studies are presented that were used to evaluate the effectiveness of the program.

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)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.011
GPT teacher head0.196
Teacher spread0.185 · 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 designSimulation or modeling
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
Published2001
Admission routes1
Has abstractyes

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Same venueProceedings of the Institution of Mechanical Engineers Part B Journal of Engineering ManufactureSame topicProduct Development and CustomizationFrench-language works237,207