An interactive product customization framework for freeform shapes
Bibliographic record
Abstract
Purpose The purpose of this paper is to establish new computer-aided-design (CAD) framework to design custom product that is fabricated additive manufacturing (AM), which can produce complex three-dimensional (3D) object without additional tool or fixture. Additive manufacturing (AM) enables the fabrication of three-dimensional (3D) objects with complex shapes without additional tools and refixturing. However, it is difficult for user to use traditional computer-aided design tools to design custom products. Design/methodology/approach In this paper, the authors presented a design system to help user design custom 3D printable products based on some reference freeform shapes. The user can define and edit styling curves on the reference model using the interactive geometric operations for styling curve. Incorporating with the reference models, these curves can be converted into 3D printable models through the fabrication interface. Findings The authors tested their system with four design applications including a hollow patterned bicycle helmet, a T-rex with skin frame structure, a face mask with Voronoi patterns and an AM-specific night dress with hollow patterns. Originality/value The executable prototype of the presented design framework used in the customization process is publicly available.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".