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Record W1998248566 · doi:10.1017/s0890060407000261

Making sense of engineering design review activities

2007· article· en· W1998248566 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

VenueArtificial intelligence for engineering design analysis and manufacturing · 2007
Typearticle
Languageen
FieldEngineering
TopicDesign Education and Practice
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsComputer scienceNew product developmentProcess (computing)Engineering design processSet (abstract data type)Coding (social sciences)Product designProduct (mathematics)Knowledge managementProcess managementEngineering

Abstract

fetched live from OpenAlex

Abstract Engineering design reviews, which take place at predetermined phases of the product development process, are fundamental elements for the evaluation and control of engineering activities. These meetings are also acknowledged as unique opportunities for all the parties involved to share information about the product and related engineering processes. For product development teams, the knowledge generated during a design review is not as secondary as it may seem; key design decisions, design experiences, and associated rationale are frequently made explicit. Useful work has been carried out on the design review process itself, but little work has been undertaken about the detailed content of the meeting activity; it is argued that understanding the transactions that take place during a meeting is critical to building an effective knowledge-oriented recording strategy. To this effect, an extensive research program based on case studies in the aerospace engineering domain has been carried out. The work reported in this paper focuses on a set of tools and methods developed to characterize and analyze in depth the transactions observed during a number of case studies. The first methodology developed, the transcript coding scheme, uses an intelligent segmentation of meeting discourse transcriptions. The second approach, which bypasses the time consuming transcribing operation, is based on a meeting capture template developed to enable a meeting observer to record the transactions as the meeting takes place. A third method, the information mapping technique, has also been developed to interpret the case study data in terms of decisions, actions, rationale, and lessons learned, effectively generating qualitative measures of the information lost in the formal records of design reviews. Overall, the results generated by the set of tools presented in this paper have fostered a practical strategy for the knowledge intensive capture of the contents of design reviews. The concluding remarks also discuss possible enhancements to the meeting analysis tools presented in this paper and future work aimed at the development of a computer supported capture software for design reviews.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.897
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.075
GPT teacher head0.314
Teacher spread0.239 · 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