3-S BOM: Pioneering Sustainability-Scoring-System for Multi-Functional Product Configurations Based on ESG and Circularity
Bibliographic record
Abstract
The Bill of Materials (BOM) is the primary place where product configurations are formulated and designed. Despite its critical role, the BOM falls short in addressing sustainability concerns. The current state of the art does not capture data on the sustainability performance of suppliers of listed components. Furthermore, the BOM neglects synthetic information on reusability and circularity of components. To overcome these limitations, this study proposes the introduction of a Sustainability-Scoring-System (3-S BOM). The aim is to upscale the traditional BOM to the new sustainability market demand. The 3-S BOM has two purposes: to integrate synthetic data on sustainability and to allow further configurations of products based on diversified sustainability profiles. Specifically, each component, sub-assembly and assembly within the BOM is assigned an Overall Sustainability Score (OSS), which covers three key sustainability areas On the supplier side, an ESG score will be representative of the supplier’s level of sustainability, while on the component side, a Hazardous Substances and Virgin Materials (HV) indicator and a Hazardous Substances and Virgin Materials Circularity (HVci) indicator will assess the sustainability of the components, taking into account their composition and circularity. The customer is actively involved in defining the sustainability profile of the purchased product by defining how the ESG, HV and HVci must influence the final assembly of the purchased product, choosing between different levels of specificity.
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.
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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
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".