Impact of Quality Grading and Uncertainty on Recovery Behaviour in a Remanufacturing Environment
Bibliographic record
Abstract
This research considers a remanufacturing enterprise that constitutes a stage in a closed loop supply chain. Each returned item is precisely tested and assigned a quality grade between zero and a hundred. Consequently, acceptance to the facility, acquisition price and remanufacturing cost are all quality dependants. The research implements the newsvendor modeling techniques to model the system when a single remanufacturing facility satisfies a single market's demand or when multiple remanufacturing facilities satisfy multiple markets' demand. Thus, non-linear programming or mixed integer non- linear programming models are proposed to maximize the total profit by selecting facilities to operate, optimal minimum quality to accept into each operating facility and market's demand to satisfy from each operating facility. Returns' quality is considered to be stochastic, while markets' demand could be either stochastic or deterministic. The impact of changing returns, quality and demand uncertainties, and transportation cost on remanufacturing systems are studied.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".