A Sustainable Multicriteria Decision Framework for Obsolescence Resolution Strategy Selection
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
Parts obsolescence has an important impact on the product life cycle, the manufacturing system and the environment leading to operational, logistical, reliability and cost implications. While current resolution models are cost-oriented, multiple studies have revealed that technological obsolescence is strongly involved in the electronic waste problem. In this study, based on academic literature and expert opinions, a sustainable decision framework for obsolescence resolution strategy (ORS) selection is proposed. It consists of economic, environmental, social and technological dimensions, integrating a total of fifteen criteria. Multicriteria decision-making (MCDM) methods are suggested to select the most sustainable solution. A case study was performed where the criteria weights and the alternatives performance were judged by five experts from the fields of environment, economy, human resources and obsolescence and operations management. Results from different MCDM methods were compared to the actual decision to evaluate their effectiveness. Using the suggested framework improved the decision process as integrating sustainability had a drastic impact on the selected strategy and consequently on the company’s performance. In addition to its managerial insights, this paper provides a new research perspective to sustainable and robust obsolescence management to effectively handle the increasing number and severity of obsolete components.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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