A constraint-based product configurator for mass customisation
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
To stay competitive, many manufacturers have to adapt their business models to mass customisation, which enables customers to order customised products tailored to their specific needs. One of the key enabling technologies for the successful implementation of mass customisation is the product configurator, a software tool that automatically generates the customised product designs based on the customer requirements and design constraints. A constraint-based product configurator has advantages of flexibility and generality in product modelling and problem solving. Its ability to deal with discrete constraints has been well studied. However, the requirement for handling numeric constraints expressed as mathematical formulas posts a new challenge. This paper proposes a constraint model for n-ary numeric constraints and effective search algorithms. It also presents a system design approach on modelling domain-specific product knowledge, integrating the domain-specific product models into generic search algorithms and presenting configuration results to the end users.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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