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Record W2008060519 · doi:10.1115/1.4006439

A Co-Evolution Model for Prediction and Synthesis of New Products and Manufacturing Systems

2012· article· en· W2008060519 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

VenueJournal of Mechanical Design · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicProduct Development and Customization
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsComputer scienceSet (abstract data type)ImperfectProduct (mathematics)Artificial intelligenceMathematics

Abstract

fetched live from OpenAlex

A model for predicting the future codevelopment of new products and manufacturing systems is presented. The model incorporates a set of manufacturing co-evolution hypotheses that promote association between manufacturing systems and product variants throughout their shared evolution courses based on a biological analogy. It shows the impact of the different co-evolution states particularly the imperfect co-evolution, which can be remedied by predicting new systems and products. A novel mathematical technique for co-evolution knowledge synthesis is used to analyze the relationships between manufacturing capabilities and product features and discover the human synthesis knowledge implicit in their codevelopment. A set of rules and linear system of equations is formulated to discover such knowledge. The co-evolution model is mathematically established using Cladistics and trees reconciliation techniques that are used extensively in Biology. The model is validated by data sets of milling machine tools and the corresponding machined prismatic parts. The application of the developed model yields suggested directions for the future planning and development of the analyzed machine tools and potential new products features, products and variants that would further sustain and prolong the useful life of the current manufacturing capabilities and systems.

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)0.000
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: none
Teacher disagreement score0.896
Threshold uncertainty score0.266

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 communication0.0000.001
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 head0.043
GPT teacher head0.225
Teacher spread0.182 · 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