Module planning for open architecture product
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.
Bibliographic record
Abstract
Product diversity and market competition have promoted the demand of personalized products.The traditional product architecture cannot meet requirements of low cost and individualization.Open architecture allows products have the advantage of mass customization to meet the personalized requirements of customers.Modules of the open architecture product(OAP)consist of common module,customized module and personalized module.Module partition and module planning are important steps in the open architecture product design.A module planning method was proposed for the OAP design which utilized the axiomatic design as the analysis framework and quality function deployment(QFD)as the basic model.Axiomatic design was adopted to map the relationship between functional requirements and conceptual structures.The design relationship matrix of product was established by analyzing the function,spatial and flow correlations between components.A hierarchical clustering method was used to cluster elements in the design relationship matrix.QFD was used to plan the type of components and the module type planning guideline was established.The module type was decided based on the type of parts.A toy painting machine was designed using the proposed method with the open architecture,which showed the feasibility of the module planning.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it