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Record W3051936404 · doi:10.1016/j.procir.2020.02.169

Objective based process model for enhancing the product maturity level in the early phase of a development process

2020· article· en· W3051936404 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

VenueProcedia CIRP · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicProduct Development and Customization
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsProcess (computing)Process managementNew product developmentSelection (genetic algorithm)Systems engineeringProcess modelingPhase (matter)Computer scienceProduct (mathematics)EngineeringCapability Maturity ModelIndustrial engineeringManagement scienceWork in processOperations managementArtificial intelligenceSoftwareBusinessMathematics

Abstract

fetched live from OpenAlex

In the early phase of a development process, several concept variations are developed to overcome technical problems. Despite this, only one concept makes the final selection. In this study, a theoretical process model providing an early-phase, structured proceeding guideline was adapted for use in a development process in order to simplify concept selection. This adapted process model enables a more time-efficient and transparent early-phase development process. Furthermore, it presents an opportunity for the relationship between design engineers and simulation engineers to be improved. The adapted process model was validated by using a combination of simulated models and expert interviews.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.756
Threshold uncertainty score0.572

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.052
GPT teacher head0.274
Teacher spread0.222 · 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